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Note 7 | 12 Months Ended
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Dec. 31, 2021
Risk Management [Abstract] |
Disclosure of risk management [Text Block] | Risk managementRisk factors BBVA Group has processes in place for identifying risks and analyzing scenarios in order to enable the Group to manage risks in a dynamic and proactive way. The risk identification processes are forward looking to seek the identification of emerging risks and take into account the concerns of both the business areas, which are close to the reality of the different geographical areas, and the corporate areas and senior management. Risks are identified and measured consistently using the methodologies deemed appropriate in each case. Their measurement includes the design and application of scenario analyzes and stress testing and considers the controls to which the risks are subjected. As part of this process, a forward projection of the Risk Appetite Framework (RAF) variables in stress scenarios is conducted in order to identify possible deviations from the established thresholds. If any such deviations are detected, appropriate measures are taken to keep the variables within the target risk profile. In this context, there are a number of emerging risks that could affect the evolution of the Group's business. These risks are included in the following blocks: Risk associated with the COVID-19 pandemic The COVID-19 (coronavirus) pandemic has adversely affected the world economy, and economic activity and conditions in the countries in which the Group operates. Despite the gradual improvement experienced in 2021 driven by the increase in the rate of vaccination, new waves of contagion continue to be a source of concern and the emergence of new strains remains a risk. Among other challenges, these countries are still dealing with high unemployment levels, weak activity, supply disruptions and increasing inflationary pressures, while public debt has increased significantly due to the support and spending measures implemented by the government authorities. Furthermore, there has been an increase in loan losses from both companies and individuals, which has so far been slowed down by the impact of government support measures, including bank payment deferrals, credit with public guarantee and direct aid measures. Likewise, volatility in the financial markets has affected exchange rates - mainly in emerging economies- and the value of assets and investments, which has adversely affected the Group's results in the past, and could do so again. There are still uncertainties about the final future impact of the COVID-19 pandemic, mainly if there is an increase in infections caused by the new variants of the coronavirus. Furthermore, the Group has been and may be affected during the following quarters or years by the measures or recommendations adopted by regulatory authorities in the banking sector, such as variations in reference interest rates, the modification of prudential requirements, the temporary suspension of dividend payments, the modification of the deferral of monthly installments for certain loans and the granting of guarantees or public guarantees to new credit operations for companies and self-employed persons, the adoption of further similar measures or the termination of those already approved, as well as any changes in financial assets purchase programs by the ECB. Since the outbreak of the pandemic, the Group has experienced a decline in its activity. For example, the granting of new loans to individuals has generally decreased. In addition, the Group faces various risks, such as an increased risk of volatility in the value of its assets (including financial instruments valued at fair value, which may suffer significant fluctuations) and of the securities held for liquidity reasons, a possible increase in the NPL ratio and risk-weighted assets, as well as a negative impact on the Group's cost of financing and on its access to financing (especially in an environment where credit ratings are affected). Following the generalized lifting of mobility restrictions and the increasing resumption of normal operations, greater emphasis is being placed on the particular circumstances of each customer, in addition to its respective industry or sector. Furthermore, the pandemic could continue to adversely affect the business and transactions of third parties that provide critical services to the Group and, in particular, the higher demand and/or the lower availability of certain resources could, in some cases, make it more difficult for the Group to maintain the required service levels. In addition, the widespread use of remote work has increased the risks related to cybersecurity, as the use of non-corporate networks has increased. Macroeconomic and geopolitical risks In 2021 the global economy has grown significantly, recovering in part from the crisis caused by the pandemic, which caused a sharp fall in global GDP in 2020. The significant upturn in global growth has been due to progress in the vaccination against COVID-19 and important economic stimuli adopted by public authorities. Activity indicators show, however, that the economic recovery process has lost momentum in recent months. The recent slowdown in economic growth is taking place in an environment marked by a sharp increase in infections caused by new variants of the COVID-19, although the increasing immunization of the world population has helped to generally prevent the adoption of mobility restrictions, which would have had a greater impact on the economy. The effects of reduced production due to the pandemic and its persistence, coupled with fiscal stimuli and strong demand for goods, once restrictions have been lifted, contribute to maintaining the problems in global supply chains observed since the beginning of 2021 which, in addition to negatively affecting economic activity, generate significant upward pressure on prices. Against this backdrop, annual inflation in December 2021 stood at 7.0% in the United States and 5.0% in the Eurozone. In both geographical areas, long-term inflation expectations from markets and surveys have been adjusted upwards, although in the case of the Eurozone they remain generally below the European Central Bank’s 2% target. High inflation rates and their increased persistence have put pressure on central banks to withdraw monetary stimuli earlier than they had originally anticipated. The United States Federal Reserve, in particular, has begun the rollback in its bond-buying program and has suggested that monetary policy interest rates will adjust upwards earlier and faster than expected by financial markets and financial analysts, and also that a downsizing of its balance sheet may soon begin. In the Eurozone, the ECB will complete the pandemic emergency purchase program (PEPP) in March 2022. Although the asset purchase program (APP) is maintained, asset purchases will be moderated over the course of 2022. However, unlike the Federal Reserve, the ECB has continued to maintain that it rules out an increase in benchmark interest rates in 2022. According to BBVA Research, the global economic recovery process is expected to continue in the coming months, albeit at a slightly slower pace than expected in autumn of 2021, due to the persistence of the pandemic, but also due to a higher-than-estimated impact of supply chain problems and inflationary pressures. All this against a background of reduced fiscal and monetary stimulus. GDP growth would therefore moderate, from an estimated 5.6% in 2021 to about 4.2% in 2022 in the United States, from 5.1% in 2021 to 3.7% in 2022 in the Eurozone and from 8.0% in 2021 to 5.2% in 2022 in China. The likely rise in monetary policy interest rates in the United States, which could reach 1.25% by the end of 2022, as well as a progressive control of the pandemic and a moderation of supply chain problems, would allow inflation to be moderated throughout the year; although inflation is expected to remain high, particularly in the United States. Risks arising from this economic scenario expected by BBVA Research are significant and are biased downwards in the case of activity, and include more persistent inflation, financial turbulence caused by a more aggressive withdrawal of monetary stimuli, the emergence of new variants of the coronavirus that bypass current vaccines, a more intense slowdown in the Chinese economy, as well as social and geopolitical tensions. Likewise, the countries in which the Group operates face various idiosyncratic risks, beyond those related to the global environment. Regulatory and reputational risks Financial institutions are exposed to a complex and ever-changing regulatory environment defined by governments and regulators. This can affect their ability to grow and the capacity of certain businesses to develop, and result in stricter liquidity and capital requirements with lower profitability ratios. The Group constantly monitors changes in the regulatory framework that allow for anticipation and adaptation to them in a timely manner, adopt industry practices and more efficient and rigorous criteria in its implementation. The financial sector is under ever closer scrutiny by regulators, governments and society itself. In the course of activities, situations which might cause relevant reputational damage to the entity could raise and might affect the regular course of business. The attitudes and behaviors of the Group and its members are governed by the principles of integrity, honesty, long-term vision and industry practices through, inter alia, the internal control model, the Code of Conduct, the Corporate Principles in tax matters and Responsible Business Strategy of the Group. Business, operational and legal risks New technologies and forms of customer relationships: Developments in the digital world and in information technologies pose significant challenges for financial institutions, entailing threats (new competitors, disintermediation, etc.) but also opportunities (new framework of relations with customers, greater ability to adapt to their needs, new products and distribution channels, etc.). Digital transformation is a priority for the Group as it aims to lead digital banking of the future as one of its objectives. Technological risks and security breaches: The Group is exposed to new threats such as cyber-attacks, theft of internal and customer databases, fraud in payment systems, etc. that require major investments in security from both the technological and human point of view. The Group gives great importance to the active operational and technological risk management and control. Regarding legal risks, the financial sector faces an environment of increasing regulatory and litigious pressure, and thus, the various Group entities are usually party to individual or collective judicial proceedings (including class actions) resulting from their activity and operations, as well as arbitration proceedings. The Group is also party to other government procedures and investigations, such as those carried out by the antitrust authorities in certain countries which, among other things, have in the past and could in the future result in sanctions, as well as lead to claims by customers and others. In addition, the regulatory framework, in the jurisdictions in which the Group operates, is evolving towards a supervisory approach more focused on the opening of sanctioning proceedings while some regulators are focusing their attention on consumer protection and behavioral risk. In Spain and in other jurisdictions where the Group operates, legal and regulatory actions and proceedings against financial institutions, prompted in part by certain judgments in favor of consumers handed down by national and supranational courts (with regards to matters such as credit cards and mortgage loans), have increased significantly in recent years and this trend could continue in the future. The legal and regulatory actions and proceedings faced by other financial institutions in relation to these and other matters, especially if such actions or proceedings result in favorable resolutions for the consumer, could also adversely affect the Group. All of the above may result in a significant increase in operating and compliance costs or even a reduction of revenues, and it is possible that an adverse outcome in any proceedings (depending on the amount thereof, the penalties imposed or the procedural or management costs for the Group) could damage the Group's reputation, generate a knock-on effect or otherwise adversely affect the Group. It is difficult to predict the outcome of legal and regulatory actions and proceedings, both those to which the Group is currently exposed and those that may arise in the future, including actions and proceedings relating to former Group subsidiaries or in respect of which the Group may have indemnification obligations. Any of such outcomes could be significantly adverse to the Group. In addition, a decision in any matter, whether against the Group or against another credit entity facing similar claims as those faced by the Group, could give rise to other claims against the Group. In addition, these actions and proceedings attract resources from the Group and may occupy a great deal of attention on part of the Group's management and employees. As of December 31, 2021, the Group had €623 million in provisions for the proceedings it is facing (included in the line "Provisions for litigation and pending tax cases" in the consolidated balance sheet) (see Note 24), of which €533 million correspond to legal contingencies and €90 million to tax related matters. However, the uncertainty arising from these proceedings (including those for which no provisions have been made, either because it is not possible to estimate them or for other reasons) makes it impossible to guarantee that the possible losses arising from these proceedings will not exceed, where applicable, the amounts that the Group currently has provisioned and, therefore, could affect the Group's consolidated results in a given period. As a result of the above, legal and regulatory actions and proceedings currently faced by the Group or to which it may become subject in the future or otherwise affected by, individually or in the aggregate, if resolved in whole or in part adversely to the Group's interests, could have a material adverse effect on the Group’s business, financial condition and results of operations. Spanish judicial authorities are investigating the activities of Centro Exclusivo de Negocios y Transacciones, S.L. (Cenyt). Such investigation includes the provision of services by Cenyt to the Bank. On 29th July, 2019, the Bank was named as an investigated party (investigado) in a criminal judicial investigation (Preliminary Proceeding No. 96/2017 – Piece No. 9, Central Investigating Court No. 6 of the National High Court) for alleged facts which could be constitutive of bribery, revelation of secrets and corruption. On February 3, 2020, the Bank was notified by the Central Investigating Court No. 6 of the National High Court of the order lifting the secrecy of the proceedings. Certain current and former officers and employees of the Group, as well as former directors have also been named as investigated parties in connection with this investigation. The Bank has been and continues to be proactively collaborating with the Spanish judicial authorities, including sharing with the courts the relevant information obtained in the internal investigation hired by the entity in 2019 to contribute to the clarification of the facts. As of the date of the approval of the Consolidated Financial Statements, no formal accusation against the Bank has been made. This criminal judicial proceeding is at the pre-trial phase. Therefore, it is not possible at this time to predict the scope or duration of such proceeding or any related proceeding or its or their possible outcomes or implications for the Group, including any fines, damages or harm to the Group’s reputation caused thereby. Credit risk Credit risk is the potential loss assumed by the Group as a result of the failure by the Group´s counterparties to meet their contractual obligations. The general principles governing credit risk management in the BBVA Group are: –Risks taken should comply with the general risk policy established by the Board of Directors of BBVA. –Risks taken should be in line with the level of equity and generation of recurring revenue of the BBVA Group prioritizing risk diversification and avoiding relevant concentrations. –Risks taken should be identified, measured and assessed and there should be management and monitoring procedures, in addition to mitigation and control mechanisms. –Risks should be managed in a prudent and integrated manner during their life cycle and their treatment should be based on the type of risk. In addition, portfolios should be actively managed on the basis of a common metric (economic capital). –The main criterion when granting credit risks is the capability of the borrower or obligor to fulfill on a timely basis all financial obligations with its business income or source of income without depending upon guarantors, bondsmen or pledged assets. –Improve the financial health of our clients, help them in their decision making and in the daily management of their finances based on personalized advice. –Help our clients in the transition towards a sustainable future, with a focus on climate change and inclusive and sustainable social development. Credit risk management in the Group has an integrated structure for all its functions, allowing decisions to be taken objectively and independently throughout the life cycle of the risk. –At Group level: frameworks for action and standard rules of conduct are defined for handling risk, specifically, the channels, procedures, structure and supervision. –At the business area level: they are responsible for adapting the Group's criteria to the local realities of each geographical area and for direct management of risk according to the decision-making channel: a.Retail risks: in general, the decisions are formalized according to the scoring tools, within the general framework for action of each business area, with regard to risks. The changes in weighting and variables of these tools must be validated by the GRM area. b.Wholesale risks: in general, the decisions are formalized by each business area within its general framework for action with regard to risks, which incorporates the delegation rule and the Group's corporate policies. The risk function has a decision-making process supported by a structure of committees with a solid governance scheme, which describes their purposes and functioning for a proper performance of their tasks. This governance scheme has been key in the management of the COVID-19 crisis in all the geographical areas where the Group operates, in which it has been possible to support the maintenance of the flow of funds required for the operation of the economies while analyzing and monitoring the credit quality of exposures. COVID-19 support measures Since the beginning of the pandemic, the Group offered COVID-19 support measures to its customers (individuals, SMEs and wholesale) in all the geographic areas where it operates, consisting of both deferrals on existing loans and new public-guaranteed lending. These measures were extended to individual customers and, in the case of legal entities, to different sectors, with Leisure and Real Estate being the sectors that have used them most. Deferral support schemes have expired in all geographical areas Deferrals were both legislative (based on national laws) and non-legislative (based on sectorial or individual schemes) and were aimed at mitigating the effects of COVID-19 and deferring the payment of principal and/or interest, while maintaining the original contracts. The detail of legislative deferrals by geographical area is as follows: Spain: –Mainly covered by Royal Decree Laws (hereinafter "RDL") 8/2020 and 11/2020, as well as by the sector agreement promoted by the Spanish Banking Association (hereinafter "AEB") to which BBVA adhered. –Legislative deferrals consisted of a three-month deferral of principal and interest payments and were aimed, by type of client, at individuals, sole proprietors or the self-employed and, by type of product, at mortgages, personal loans or consumer loans. –In addition, once the legal deferral expired, customers could adhere to the sector agreement for the remaining term up to the limit established in that agreement. –Deferrals granted under the AEB sectorial agreement had a duration of up to 12 months of principal deferral in the case of mortgage loans and up to 6 months in personal loans. –Under RDL 26/2020, the possibility of deferring the principal and/or interests was offered for companies in the transport sector for up to 6 months and for companies in the tourism sector for up to 12 months. Mexico: –The National Banking and Securities Commission (hereinafter, "CNBV") published the official records P285/2020 dated March 26, 2020 and P293/2020 dated April 15, 2020, allowing the granting of deferrals on principal and interest for a term of 4 months, extendable for 2 months more. The main beneficiaries of these measures were individuals and companies, impacting mortgage loans, personal loans and consumer loans, including credit cards. Turkey: –The Banking Regulation and Supervisory Agency (hereinafter, "BRSA") instructed banks to support customers through deferrals, consisting of deferring payments for a period of 3 months, with a potential extension of up to 6 months. These support measures were granted to individual custome r s. Colombia: –The binding legislation for deferrals is provided by the Financial Superintendence of Colombia, specifically by its Circulars 07/2020 and 14/2020, as well as Resolution No. 385. The deferrals offered consisted of the deferral of principal and interest payments for up to 6 months. Peru: –Several measures were approved by the Superintendence of Banking and Insurance (SBS) of Peru, allowing the deferral of principal and interest payments, initially for up to 6 months and later extended for up to 12 months, mainly for individuals, self-employed and small companies. Argentina: –Based on state legislation such as Royal Decree 544/2020 or Decree 319/2020, as well as on various regulations from the Central Bank. Deferral for up to 3 months of principal and interest. With regard to new financing with public guarantees, the Group's involvement in the following is noteworthy: Spain: –The Official Credit Institute (hereinafter, ICO) published several aid programs aimed at the self-employed, small and medium-sized enterprises (hereinafter "SMEs") and companies, through which a guarantee of between 60% and 80% (in SMEs always 80%) was granted for a term of up to 5 years for new financing granted (RDL Mar/2020). –The amount and duration of the guarantee depended on the size of the company and the type of aid to which it applied, and could be extended for up to a maximum term of 3 additional years and the grace period could be extended for up to 12 additional months with respect to the terms and grace periods initially agreed (RDL Nov/2020). –Likewise, facilities were provided in term extensions (up to a maximum term of 10 years), conversion of financing operations into Participative Loans as well as debt forgiveness in part of the financing (RDL 5/2021 and Code of Good Practices). –The ICO has also subsidized for individuals the amount of the rent for up to 6 months in loans of up to 6 years. –Almost all of the ICO loans with the expired grace period have resumed payment on a regular basis or canceled their debt. –ICO loan extensions represented around 25% of all ICO financing. Turkey: –Public support programs have been registered guaranteeing up to 80% of loans to companies for a term of 1 year. Colombia: –Different public support programs (FNG, Bancoldex, Finagro, Findeter) provide for guarantees covering between 50-90%. Peru: –There were public support programs such as Reactiva, Crecer or FAE aimed at companies and micro-enterprises with guaranteed amounts ranging from 60% to 98%, depending on the program and the type of company. –For loans granted under the Reactiva program, it was possible to extend both the maturity date and the grace period of the loans. Argentina: –Guarantees of up to 100% for micro-SMEs or self-employed and up to 25% for other companies in loans of up to 1 year The outstanding balance of existing loans for which a payment deferral was granted (split by those existing at year-end and those that were completed by year-end) under EBA standards and for which financing was granted with public guarantees given at a Group level, as well as the number of customers of both measures, as of December 31, 2021 and 2020 are as follows:
Amount of payment deferral and financing with public guarantees of the Group (Millions of Euros)
| Payment deferral | Financing with public guarantees |  |
| Existing | Completed | Total | Number of customers | Total | Number of customers | Total payment deferral and guarantees | (%) credit investment
December 2021 | 189 | 21,743 | 21,931 | 2,188,720 | 16,093 | 264,809 | 38,025 | 10.9 | %
December 2020 (*) | 6,536 | 21,868 | 28,405 | 2,779,964 | 16,053 | 249,458 | 44,458 | 12.9 | %
(*) Figures as of December 2020 do not include the companies sold in the United States in 2021. The outstanding balance of existing loans for which a payment deferral was granted (split by those existing at year-end and those that were completed by year-end) under EBA standards and for which financing was granted with public guarantees given at a Group level, broken down by segment, as of December 31, 2021 and 2020 are as follows:
Amount of payment deferral and financing with public guarantees by concept (Millions of Euros)
| Payment deferral | Financing with public guarantees
| Existing | Completed | Total
| 2021 |  | 2020 (*) | 2021 |  | 2020 (*) | 2021 |  | 2020 (*) | 2021 |  | 2020 (*)
Group | 189 |  | 6,536 | 21,743 |  | 21,868 | 21,931 |  | 28,405 | 16,093 |  | 16,053
Households | 107 |  | 4,503 | 14,904 |  | 14,550 | 15,011 |  | 19,052 | 1,376 |  | 1,235
Of which: Mortgages | 97 |  | 3,587 | 10,195 |  | 7,471 | 10,291 |  | 11,059 | 6 |  | 1
SMEs | 44 |  | 1,023 | 3,950 |  | 4,743 | 3,994 |  | 5,766 | 10,911 |  | 10,573
Non-financial corporations | 37 |  | 961 | 2,766 |  | 2,397 | 2,803 |  | 3,358 | 3,788 |  | 4,232
Other | — |  | 50 | 122 |  | 179 | 122 |  | 229 | 18 |  | 13
(*) Figures as of December 2020 do not include the companies sold in the United States in 2021.
Amount of payment deferral by stages (Millions of Euros)
| Stage 1 | Stage 2 | Stage 3 | Total
| 2021 |  | 2020 (*) | 2021 |  | 2020 (*) | 2021 |  | 2020 (*) | 2021 |  | 2020 (*)
Group | 13,236 |  | 18,602 | 6,252 |  | 7,736 | 2,444 |  | 2,066 | 21,931 |  | 28,405
Households | 9,167 |  | 12,336 | 3,707 |  | 4,997 | 2,137 |  | 1,719 | 15,011 |  | 19,052
Of which: Mortgages | 6,360 |  | 7,347 | 2,444 |  | 2,844 | 1,487 |  | 867 | 10,291 |  | 11,059
SMEs | 2,609 |  | 4,147 | 1,131 |  | 1,327 | 254 |  | 292 | 3,994 |  | 5,766
Non-financial corporations | 1,364 |  | 1,903 | 1,387 |  | 1,399 | 53 |  | 56 | 2,803 |  | 3,358
Other | 95 |  | 216 | 27 |  | 13 | — |  | — | 122 |  | 229
(*) Figures as of December 2020 do not include the companies sold in the United States in 2021. Deferrals involved the temporary suspension, in whole or in part, of contractual obligations and their deferral for a specific period of time. Considering that the payment deferrals granted in connection with COVID -19 provide temporary relief to the debtors and that the economic value of the affected loans was not significantly impacted, no contractual modifications were considered and, therefore, the modified loans are accounted for as a continuation of the original loans. During 2020, the loss of temporary value of the deferrals that did not trigger the right to collect interest was included under the heading "Impairment or reversal of impairment on financial assets not measured at fair value through profit or loss or net gains by modification” of the consolidated income statement, amounting to €304 million, of which €300 million had been already recognized as higher interest margin at such date. During 2021, the amount recognized was not significant. Regarding the classification of exposures according to their credit risk, the Group has continued to apply IFRS 9 when granting the payment deferrals and has reinforced the procedures for monitoring credit risk both throughout the life of the transactions and at their maturity. This means that the payment deferrals granting does not imply in itself an automatic trigger for a significant increase in risk and that the transactions subject to the payment deferrals are initially classified in the stage in which they had previously been classified, unless, based on their risk profile, they should be classified in a worse stage. On the other hand, as evidence of payment has ceased to exist or has been reduced, the Group has introduced additional indicators or segmentations to identify the significant increase in risk or impairment that may have occurred in some transactions or a set of them and, where appropriate, they have been classified in Stage 2 or Stage 3. Furthermore, the indications provided by the European Banking Authority (EBA) have been taken into account to not consider as "forbearance" the payment deferrals that meet a series of requirements. All this without prejudice to maintaining its consideration as a forbearance if it was previously qualified as such or classifying the exposure in the corresponding stage previously stated. On the other hand, the treatment planned for the payment deferrals that expire and may require additional support will be in accordance with the updated evaluation of the customer's credit quality and the characteristics of the solution granted. If applicable, they will be treated as Refinancing or Restructuring as described in Note 7.2.7 of the Financial Statements. Regarding public support for lending, it does not affect the evaluation of the significant increase in risk since risk is valued based on the credit quality of the relevant instrument. However, in estimating the expected loss, the existence of the guarantor implies a possible reduction in the level of provisions necessary since, for the hedged part, the loss that would be incurred in the foreclosure of the guarantee is taken into account. The public guarantees granted in the different geographies in which the Group operates have been considered as an integral part of the terms and conditions of the loans granted under the consideration that the guarantees are granted at the same time that the financing is granted to the client and in a way inseparable from it. The quantitative information on refinancing and restructuring operations is presented in Appendix VIII: "Quantitative information on refinancing and restructuring operations and other requirement under Bank of Spain Circular 6/2012". Measurement of Expected Credit Loss IFRS 9 requires determining the Expected Credit Loss (hereinafter "ECL") of a financial instrument in a way that reflects an unbiased estimation removing any conservatism or optimism, including the time value of money and a forward-looking perspective (including the economic forecast), all this based on the information that is available at a certain point in time and that is reasonable and bearable with respect to future economic conditions. Therefore, the recognition and measurement of ECL is highly complex and involves the use of significant analysis and estimation including formulation and incorporation of forward-looking economic conditions into the ECL model. The modeling of the ECL calculation is subject to a governance system that is common to the entire Group. Within this common framework, each geography makes the necessary adaptations to capture its particularities. The methodology, assumptions and observations used by each geography are reviewed annually, and after a validation and approval process, the outcome of this review is incorporated into the ECL calculations. Risk parameters by homogeneous groups Expected losses can be estimated both individually and collectively. Regarding the collective estimate, the instruments are distributed in homogeneous groups (segments) that share similar risk characteristics. Following the guidelines established by the Group for the development of models under IFRS 9, each geography performs the grouping based on the information available, its representativeness or relevance and compliance with the necessary statistical requirements. Depending on the portfolio or the parameter being estimated, one risk driver or another will apply and different segments will reflect differences in PDs and LGDs. Thus, in each segment, changes in the level of credit risk will respond to the impact of changing conditions on the common range of credit risk drivers. The effect on the Group’s credit risk in response to changes in forward-looking information will be considered as well. Macroeconomic modeling for each segment is carried out using some of the shared risk characteristics. These segments share credit risk characteristics such that changes in credit risk in a part of the portfolio are not concealed by the performance of other parts of the portfolio. In that sense, the methodology developed for ECL estimation indicates the risk drivers that have to be taken into account for PD segmentation purposes, depending on whether the estimation is for retail or wholesale portfolios. As an example of the variables that can be taken into consideration to determine the final models, the following stand out: –PD - Retail: Contractual residual maturity, credit risk scoring, type of product, days past due, forbearance, time on books, time to maturity, nationality of the debtor, sale channel, original term, indicator of credit card activity, percentage of initial drawn balance in credit cards. –PD - Wholesale: Credit Risk Rating, type of product, watch-list level, forbearance (client), time to maturity, industry sector, updated balance (y/n), written off, grace period. –LGD – retail: credit Risk Scoring, segment, type of product, secured / unsecured, type of collateral, sales channel, nationality, business area, debtor’s commercial segment, forbearance (account) EAD (this risk driver could be correlated with the time on books or the LTV so, before including it, an assessment should be done in order to avoid a double counting effect), time on default of the account (for defaulted exposures), geographical location. –LGD - wholesale: credit Risk Rating, geographical location, segment, type of product, secured / Unsecured, type of collateral, business area, forbearance (client), debtor’s commercial segment time on default of the deal (for defaulted exposures). –CCF: wholesale/retail, percentage of initial drawn balance, debtor’s commercial segment, days past due, forbearance, credit limit activity, time on books. In the BBVA Group, the expected losses calculated are based on the internal models developed for all the Group's portfolios, unless clients are subject to individualized estimates. Low Default Portfolios, which include portfolios with high credit quality such as exposures to other credit institutions, sovereign debt or corporates and small client's portfolios with high exposures such as specialized lending or fixed income, are characterized by a low number of defaults, so the Group's historical bases do not contain sufficiently representative information to build impairment models based on them. However, there are external sources of information that, based on broader observations, are capable of providing the necessary inputs to develop models of expected losses. Therefore, based on the rating assigned to these exposures and taking into account the inputs obtained from these sources, the calculations of expected losses are developed internally, including their projection based on the macroeconomic perspectives. Individual estimation of Expected Credit Losses The Group periodically and individually reviews the situation and credit rating of its customers, regardless of their classification, taking into consideration the information deemed necessary to do so. It also has procedures in place within the risk management framework to identify the factors that may lead to increased risk and, consequently, to a greater need for provisions. The monitoring model established by the Group consists of continuously monitoring the risks to which it is exposed, which guarantees their proper classification in the different categories of IFRS 9. The original analysis of the exposures is reviewed through the procedures for updating the rating tools (rating and scoring), which periodically review the financial situation of clients, influencing the classification by stages of exposures. Within this credit risk management framework, the Group has procedures that seek to guarantee the review, at least annually, of all its wholesale counterparties through the so-called financial programs, which include the current and proposed positioning of the Group with the customer in terms of credit risk. This review is based on a detailed analysis of the client's up-to-date financial situation, which is complemented by other information available in relation to individual perspectives on business performance, industry trends, macroeconomic prospects or other public data. As a result of this analysis, the preliminary rating of the client is obtained, which, after undergoing the internal procedure, can be revised down if deemed appropriate (for example, general economic environment or evolution of the sector). These factors in addition to the information that the client can provide are used to review the ratings even before the scheduled financial plan reviews are conducted if circumstances so warrant. Additionally, the Group has established procedures to identify wholesale customers in the internal Watch List category, which is defined as that risk in which, derived from an individualized credit analysis, an increase in credit risk is observed, either due to economic or financial difficulties or because they have suffered, or are expected to suffer, adverse situations in their environment, without meeting the criteria for classification as impaired risk. Under this procedure, all a customer's Watch List exposures are considered stage 2 regardless of when they originated, if as a result of the analysis the customer is considered to have significantly increased risk. Finally, the Group has Workout Committees, both local and corporate, which analyze not only the situation and evolution of significant clients in Watch List and impaired situations, but also those significant clients in which, although not on Watch List, may present some stage 2 rated exposure for a quantitative reason (PD comparison from origination). This analysis is carried out in order to decide if, derived from this situation, all the client's exposures should be considered in the Watch List category, which would imply the migration of all the client's operations to stage 2 regardless of the date on which they originated. With this, the Group supports an individualized review of the credit quality of its wholesale counterparties, identifying the situations in which a change in the risk profile of these clients may have occurred and proceeding, where appropriate, to estimate individualized credit losses. Along with this review, the Group individually estimates the expected losses of those clients whose total exposure exceeds certain thresholds, including those that part of their operations may be classified in stage 1 and part in stage 2. In setting thresholds, each geography determines the minimum amount of a client's exposure whose expected losses must be estimated individually taking into account the following: –For clients with exposures in stage 3. The analysis of clients with total risk above this threshold implies analyzing at least 40% of the total risk of the wholesale portfolio in stage 3. Although the calibration of the threshold is done on the wholesale portfolio, clients of other portfolios must be analyzed if they exceed the threshold, staying in Stage 3. –For all other situations. The analysis of clients with total risk above this threshold implies analyzing at least 20% of the total risk of the Watch List wholesale portfolio. Although the threshold calibration is carried out on the exposure classified as Watch List, wholesale clients or clients belonging to other portfolios that have exposures classified in stage 2 and whose total exposure exceeds the mentioned threshold must be analyzed individually, considering both the exposures classified in stage 1 as in stage 2. Regarding the methodology for the individual estimation of expected losses, it should be mentioned, firstly, that these are measured as the difference between the asset’s carrying amount and the estimated future cash flows discounted at the financial asset’s effective interest rate. The estimated recoverable amount should correspond to the amount calculated under the following method: –The present value of estimated future cash flows discounted at the financial asset’s original effective interest rate; and –The estimation of the recoverable amount of a collateralized exposure reflects the cash flows that may result from the settlement of the collateral, as well as prospective information the analyst may implicitly include in the analysis. The estimated future cash flows depend on the type of approach applied, which can be: –Going concern scenario: when the entity has updated and reliable information about the solvency and ability of payment of the holders or guarantors. The operating cash flows of the debtor, or the guarantor, continue and can be used to repay the financial debt to all creditors. In addition, collateral may be exercised to the extent it does not influence operating cash flows. The following aspects should be taken into account: a.Future operating cash flows should be based on the financial statements of the debtor. b.When the projections made on these financial statements assume a growth rate, a constant or decreasing growth rate must be used over a maximum growth period of 3 to 5 years, and subsequently constant cash flows. c.The growth rate should be based on the analysis of the evolution of the debtor's financial statements or on applicable business restructuring plan, taking into account the resulting changes in the structure of the company (for example, due to divestments or the interruption of unprofitable lines of business). d.(Re)-investments that are needed to preserve cash flows should be considered, as well as any foreseeable future cash-flow changes (e.g. if a patent or a long-term loan expires). e.When the recoverability of the exposure relies on the realization of the disposal of some assets by the debtor, the selling price should reflect the estimated future cash flows that may result from the sale of the assets less the estimated costs associated with the disposal. –Gone concern scenario: when the entity does not have updated and reliable information, it should consider that the estimation of loan receivable flows is highly uncertain. Estimation should be carried out through the estimation of recoverable amounts from the effective real guarantees received. It will not be admissible as effective guarantees, those whose effectiveness depends substantially on the creditworthiness of the debtor or economic group in which it takes part. Under a gone concern scenario, the collateral is exercised and the operating cash flows of the debtor cease. This could be the case if: a.The exposure has been past due for a long period. There is a rebuttable presumption that the allowance should be estimated under a gone concern criterion when arrears are greater than 18 months. b.Future operating cash flows of the debtor are estimated to be low or negative. c.Exposure is significantly collateralized, and this collateral is central to cash-flow generation. d.There is a significant degree of uncertainty surrounding the estimation of the future cash flows. This would be the case if the earnings before interest, taxes, depreciation and amortization (EBITDA) of the two previous years had been negative, or if the business plans of the previous years had been flawed (due to material discrepancies in the backtesting). e.Insufficient information is available to perform a going concern analysis. Significant increase in credit risk As indicated in Note 2.2, the criteria for identifying the significant increase in risk are applied consistently throughout the Group, distinguishing between quantitative reasons or by comparison of probabilities of default and qualitative reasons (more than 30 days of default, watch list consideration or non-impaired refinancing). To manage credit risk, the Group uses all relevant information that is available and that may affect the credit quality of the exposures. This information may come mainly from the internal processes of admission, analysis and monitoring of operations, from the strategy defined by the Group regarding the price of operations or distribution by geographies, products or sectors of activity, from the observance of the macroeconomic environment, from market data such as interest rate curves, or prices of the different financial instruments, or from external sources of credit rating. This set of information is the basis for determining the rating and scoring (see Note 7.2.4 for more information on rating and scoring systems) corresponding to each of the exposures and which are assigned a probability of default (PD) that, as already mentioned, is subject to an annual review process that assesses its representativeness (backtesting) and is updated with new observations. Furthermore, the projection of these PDs over time has been modeled based on macroeconomic expectations, which allows obtaining the probabilities of default throughout the life of the operations. Based on this common methodology, and in accordance with the provisions of IFRS 9 and the EBA guidelines on credit risk management practices, each geography has established absolute and relative thresholds for identifying whether the expected changes in the probabilities of default have increased significantly compared to the initial moment, adapted to the particularities of each one of them in terms of origination levels, product characteristics, distribution by sectors or portfolios, and macroeconomic situation. To establish the aforementioned thresholds, a series of general principles are considered, such as: –Uniformity: Based on the rating and scoring systems that, in a homogeneous manner, are implemented in the Group's units. –Stability: The thresholds must be established to identify the significant increase in risk produced in exposures since their initial recognition and not only to identify those situations in which it is already foreseeable that they will reach the level of impairment. For this reason, it is to be expected that of the total exposures there will always be a representative group for which said increased risk is identified. –Anticipation: The thresholds must consider the identification of the increased risk in advance with respect to the recognition of the exposures as impaired or even before a real default occurs. The calibration of the thresholds should minimize the cases in which the instruments are classified in stage 3 without having previously been recognized as stage 2. –Indicators or metrics: It is expected that the classification of the exposures in stage 2 will have sufficient permanence to be able to develop an anticipatory management plan with respect to them before, where applicable, they end up migrating to stage 3. –Symmetry: IFRS 9 provides for a symmetric treatment both to identify the significant increase in risk and to identify that it has disappeared, so the thresholds also work to improve the credit classification of exposures. In this sense, it is expected that the cases in which the exhibitions that improve from stage 3 are directly classified into stage 1 will be minimal. –The identification of the significant increase in risk from the comparison of the probabilities of default should be the main reason why exposures in stage 2 are recognized. Specifically, a contract will be transferred to stage 2 when the following two conditions are met by comparing the current PD values and the origination PD values: (current PD) / (Origination PD) - 1*100 >Relative Threshold (%) and Current PD – Origination PD > Absolute threshold (bps) These absolute and relative thresholds are consistently established for each geography and for each portfolio, taking into account their particularities and based on the principles described. The thresholds set by each geography are included within the annual review process and, generally speaking, are in the range of 150% to 250% for the relative threshold and from 10 to 150 basis points for the absolute threshold. The establishment of absolute and relative thresholds, as well as their different levels, comply with the provisions of IFRS 9 when it indicates that a certain change, in absolute terms, in the risk of a default will be more significant for a financial instrument with a lower initial risk of default compared to a financial instrument with higher initial risk of default. For existing contracts before the implementation of IFRS 9, given the limitations in the information available on them, the thresholds are calibrated based on the PDs obtained from the prudential or economic models for calculating capital. Risk Parameters Adjusted by Macroeconomic Scenarios Expected Credit Loss (ECL) must include forward looking information, in accordance with IFRS 9, which states that the comprehensive credit risk information must incorporate not only historical information but also all relevant credit information, also including forward-looking macroeconomic information. BBVA uses the typical credit risk parameters PD, LGD and EAD in order to calculate the ECL for the credit portfolios. BBVA methodological approach in order to incorporate the forward looking information aims to determine the relation between macroeconomic variables and risk parameters following three main steps: –Step 1: Analysis and transformation of time series data. –Step 2: For each dependent variable find conditional forecasting models that are economically consistent. –Step 3: Select the best conditional forecasting model from the set of candidates defined in Step 2, based on their forecasting capacity. How economic scenarios are reflected in calculation of ECL The forward looking component is added to the calculation of the ECL through the introduction of macroeconomic scenarios as an input. Inputs highly depend on the particular combination of region and portfolio, so inputs are adapted to available data regarding each of them. Based on economic theory and analysis, the main indicators most directly relevant for explaining and forecasting the selected risk parameters (PD, LGD and EAD) are: –The net income of families, corporates or public administrations. –The outstanding payment amounts on the principal and interest on the financial instruments. –The value of the collateral assets pledged to the loan. BBVA Group approximates these variables by using a proxy indicator from the set included in the macroeconomic scenarios provided by the BBVA Research department. Only a single specific indicator for each of the three categories can be used and only one of the following core macroeconomic indicators should be chosen as first option: –The real GDP growth for the purpose of conditional forecasting can be seen as the only “factor” required for capturing the influence of all potentially relevant macro-financial scenarios on internal PDs and LGD. –The most representative short term interest rate (typically the policy rate or the most liquid sovereign yield or interbank rate) or exchange rates expressed in real terms. –A comprehensive and representative index of the price of real estate properties expressed in real terms in the case of mortgage loans and a representative and real term index of the price of the relevant commodity for corporate loan portfolios concentrated in exporters or producers of such commodity. Real GDP growth is given priority over any other indicator not only because it is the most comprehensive indicator of income and economic activity but also because it is the central variable in the generation of macroeconomic scenarios. Multiple scenario approach IFRS 9 requires calculating an unbiased probability weighted measurement of ECL by evaluating a range of possible outcomes, including forecasts of future economic conditions. The BBVA Research teams within the BBVA Group produce forecasts of the macroeconomic variables under the baseline scenario, which are used in the rest of the related processes of the Group, such as budgeting, ICAAP and risk appetite framework, stress testing, etc. Additionally, the BBVA Research teams produce alternative scenarios to the baseline scenario so as to meet the requirements under the IFRS 9 standard. Alternative macroeconomic scenarios –For each of the macro-financial variables, BBVA Research produces three scenarios. –BBVA Research tracks, analyzes and forecasts the economic environment to provide a consistent forward looking assessment about the most likely scenario and risks that impact BBVA’s footprint. To build economic scenarios, BBVA Research combines official data, econometric techniques and expert judgment. –Each of these scenarios corresponds to the expected value of a different area of the probabilistic distribution of the possible projections of the economic variables. –The non-linearity overlay is defined as the ratio between the probability-weighted ECL under the alternative scenarios and the baseline scenario, where the scenario’s probability depends on the distance of the alternative scenarios from the base one. –BBVA Group establishes equally weighted scenarios, being the probability 34% for the baseline scenario, 33% for the unfavorable alternative scenario and 33% for the favorable alternative scenario. The approach in the BBVA Group consists on using the scenario that is the most likely scenario, which is the baseline scenario, consistent with the rest of internal processes (ICAAP, Budgeting, etc.) and then applying an overlay adjustment that is calculated by taking into account the weighted average of the ECL determined by each of the scenarios. This effect is calculated taking into account the average weight of the expected loss determined for each scenario. It is important to note that in general, it is expected that the effect of the overlay is to increase the ECL. It is possible to obtain an overlay that does not have that effect, whenever the relationship between macro scenarios and losses is linear. On the other hand, the BBVA Group also takes into account the range of possible scenarios when defining its significant increase in credit risk. Thus, the PDs used in the quantitative process to identify the significant increase in credit risk will be those that result from making a weighted average of the PDs calculated under the three scenarios. Macroeconomic scenarios The COVID-19 pandemic generated uncertainty over macroeconomic outlooks, having a direct impact on the credit risk of entities, particularly, on the expected credit losses under IFRS 9. The situation remains unclear, including the remaining duration of the pandemic. At the outset of the pandemic, the expectation was that this situation would provoke a severe recession followed by an economic recovery, but which would not achieve the pre-crisis GDP levels in the short-term, supported by the measures issued by governments and monetary authorities. This situation prompted the accounting authorities and the banking supervisors to adopt measures in order to mitigate the impacts that the crisis would have on the calculation of expected credit losses under IFRS 9 as well as on solvency, urging: –the entities to evaluate all the available information, weighing more the long-term forecasts against the short-term economic factors –the governments to adopt measures to avoid the effects of impairment, –the entities to develop managerial measures as the design of specific products adapted to the situation which could occur during this crisis. Almost all accounting and prudential authorities issued recommendations or measures within the COVID-19 crisis framework regarding the estimation of the expected losses under IFRS 9 in a coordinated manner. The common denominator of all of these recommendations was that, given the difficulty of establishing reliable macroeconomic forecasts, the transitory nature of the economic shock and the need to incorporate the effect of the mitigating measures issued by the governments, a review of the automatic application of the models in order to increase the weight of the long-term macroeconomic forecasts in the calculation of the expected losses was needed. As a result thereof, the expected outcome over the lifetime of the transactions had more weight than the short-term macroeconomic impact. In this respect, the BBVA Group took into account those recommendations in the calculation of the expected credit losses under IFRS 9, considering that the economic situation caused by the COVID-19 pandemic is transitory and is expected to be followed by a recovery, even if there is uncertainty over the level and the time period of such recovery. As a consequence, different scenarios have been taken into consideration in the calculation of expected losses, resulting in the model management believes suits best the current economic situation and the combined recommendations issued by the authorities. In 2021, once the most critical phase of the pandemic has been overcome, the forward looking information incorporated in the calculation of expected losses is in line with the macroeconomic perspectives published by BBVA Research as was usual until the beginning of the pandemic. However, certain management adjustments are maintained as described in the section "Additional adjustments to expected loss measurement" to cover exposures that are estimated even with a greater degree of uncertainty. BBVA Research forecasts a maximum of five years for the macroeconomic variables. The following estimates for the next five years of the Gross Domestic Product (GDP) growth, of the unemployment rate and of the House Price Index (HPI), for the most relevant countries where it represents a significant factor, are determined by BBVA Research and have been used at the time of the calculation of the ECL as of December 31, 2021:
Positive scenario of GDP, unemployment rate and HPI for the main geographies
| Spain | Mexico | Turkey |  |  |
Date | GDP | Unemployment | HPI | GDP | Unemployment | HPI | GDP | Unemployment |  |  |  |  |  |
2021 | 5.52 % | 14.42 % | 0.33 % | 6.39 % | 4.18 % | 2.35 % | 11.63 % | 11.90 % |  |  |  |  |  |
2022 | 6.14 % | 12.50 % | 4.70 % | 4.07 % | 3.89 % | 5.38 % | 5.60 % | 11.35 % |  |  |  |  |  |
2023 | 5.13 % | 10.05 % | 3.06 % | 2.81 % | 3.75 % | 3.85 % | 5.80 % | 11.93 % |  |  |  |  |  |
2024 | 2.61 % | 8.48 % | 1.87 % | 2.17 % | 3.69 % | 3.07 % | 3.62 % | 12.66 % |  |  |  |  |  |
2025 | 2.22 % | 7.49 % | 1.56 % | 1.88 % | 3.64 % | 4.08 % | 3.66 % | 12.94 % |  |  |  |  |  |
2026 | 2.19 % | 6.71 % | 1.19 % | 1.83 % | 3.59 % | 3.95 % | 3.66 % | 13.05 % |  |  |  |  |  |
|  |  |  | Peru | Argentina | Colombia
Date |  |  |  |  |  |  |  |  | GDP | Unemployment | GDP | Unemployment | GDP | Unemployment
2021 |  |  |  |  |  |  |  |  | 13.60 % | 11.33 % | 9.91 % | 15.12 % | 9.89 % | 15.36 %
2022 |  |  |  |  |  |  |  |  | 4.91 % | 7.50 % | 6.69 % | 11.34 % | 5.33 % | 13.60 %
2023 |  |  |  |  |  |  |  |  | 3.78 % | 6.82 % | 3.02 % | 9.48 % | 3.38 % | 13.22 %
2024 |  |  |  |  |  |  |  |  | 2.76 % | 6.55 % | 2.09 % | 7.99 % | 3.30 % | 12.31 %
2025 |  |  |  |  |  |  |  |  | 2.34 % | 6.52 % | 2.16 % | 6.89 % | 3.44 % | 11.58 %
2026 |  |  |  |  |  |  |  |  | 2.28 % | 6.47 % | 2.12 % | 6.88 % | 3.51 % | 11.32 %
Base scenario of GDP, unemployment rate and HPI for the main geographies
| Spain | Mexico | Turkey
Date | GDP | Unemployment | HPI | GDP | Unemployment | HPI | GDP | Unemployment
2021 | 5.23 % | 14.93 % | (0.20) % | 5.98 % | 4.22 % | 2.46 % | 9.46 % | 12.43 %
2022 | 5.49 % | 13.98 % | 2.91 % | 3.19 % | 4.05 % | 5.30 % | 1.98 % | 12.80 %
2023 | 4.89 % | 11.68 % | 2.04 % | 2.54 % | 3.92 % | 3.68 % | 5.04 % | 12.93 %
2024 | 2.59 % | 10.08 % | 1.50 % | 2.09 % | 3.83 % | 3.07 % | 3.49 % | 13.03 %
2025 | 2.22 % | 9.05 % | 1.10 % | 1.87 % | 3.77 % | 4.08 % | 3.54 % | 13.13 %
2026 | 2.19 % | 8.15 % | 0.74 % | 1.82 % | 3.71 % | 3.93 % | 3.53 % | 13.23 %
| Peru | Argentina | Colombia
Date | GDP | Unemployment | GDP | Unemployment | GDP | Unemployment
2021 | 12.22 % | 11.38 % | 7.49 % | 15.50 % | 9.17 % | 15.44 %
2022 | 2.32 % | 7.70 % | 2.30 % | 12.35 % | 4.02 % | 13.86 %
2023 | 3.05 % | 7.06 % | 2.04 % | 10.40 % | 3.13 % | 13.51 %
2024 | 2.76 % | 6.76 % | 1.98 % | 8.60 % | 3.29 % | 12.60 %
2025 | 2.34 % | 6.70 % | 2.03 % | 7.38 % | 3.44 % | 11.87 %
2026 | 2.28 % | 6.64 % | 1.99 % | 7.38 % | 3.51 % | 11.53 %
Negative scenario of GDP, unemployment rate and HPI for the main geographies
| Spain | Mexico | Turkey |  |  |
Date | GDP | Unemployment | HPI | GDP | Unemployment | HPI | GDP | Unemployment |  |  |  |  |  |
2021 | 4.95 % | 15.41 % | (0.82) % | 5.58 % | 4.27 % | 2.54 % | 7.29 % | 12.94 % |  |  |  |  |  |
2022 | 4.88 % | 15.41 % | 1.31 % | 2.33 % | 4.23 % | 5.13 % | (1.87) % | 14.26 % |  |  |  |  |  |
2023 | 4.68 % | 13.25 % | 1.09 % | 2.26 % | 4.10 % | 3.48 % | 4.09 % | 13.99 % |  |  |  |  |  |
2024 | 2.54 % | 11.65 % | 0.99 % | 2.03 % | 3.99 % | 2.92 % | 3.40 % | 13.41 % |  |  |  |  |  |
2025 | 2.18 % | 10.62 % | 0.35 % | 1.82 % | 3.90 % | 4.05 % | 3.47 % | 13.31 % |  |  |  |  |  |
2026 | 2.15 % | 9.61 % | (0.01) % | 1.78 % | 3.84 % | 3.93 % | 3.46 % | 13.40 % |  |  |  |  |  |
|  |  |  | Peru | Argentina | Colombia
Date |  |  |  |  |  |  |  |  | GDP | Unemployment | GDP | Unemployment | GDP | Unemployment
2021 |  |  |  |  |  |  |  |  | 10.84 % | 11.43 % | 5.14 % | 15.86 % | 8.43 % | 15.52 %
2022 |  |  |  |  |  |  |  |  | (0.28) % | 7.90 % | (2.34) % | 13.33 % | 2.72 % | 14.12 %
2023 |  |  |  |  |  |  |  |  | 2.31 % | 7.30 % | 0.85 % | 11.29 % | 2.83 % | 13.79 %
2024 |  |  |  |  |  |  |  |  | 2.76 % | 6.98 % | 1.86 % | 9.19 % | 3.29 % | 12.87 %
2025 |  |  |  |  |  |  |  |  | 2.34 % | 6.91 % | 1.88 % | 7.83 % | 3.43 % | 12.13 %
2026 |  |  |  |  |  |  |  |  | 2.28 % | 6.85 % | 1.83 % | 7.85 % | 3.51 % | 11.71 %
The estimate for the next five years of the following rates, used in the measurement of the expected loss as of December 31, 2020, consistent with the latest estimates made public at that date, was:
Positive scenario of GDP, unemployment rate and HPI for the main geographies
| Spain | Mexico | Turkey
Date | GDP | Unemployment | HPI | GDP | Unemployment | HPI | GDP | Unemployment
2020 | (11.20)% | 16.44% | (1.44)% | (8.85)% | 4.57% | 1.71% | 2.07% | 13.45%
2021 | 6.63% | 16.03% | (3.28)% | 4.58% | 5.40% | (1.23)% | 9.08% | 12.60%
2022 | 6.27% | 12.72% | 4.56% | 3.80% | 5.17% | 0.32% | 5.30% | 11.58%
2023 | 2.95% | 10.82% | 5.79% | 1.62% | 5.04% | 0.31% | 4.13% | 11.58%
2024 | 2.07% | 9.58% | 3.66% | 1.47% | 4.91% | 1.01% | 4.11% | 11.19%
2025 | 2.01% | 8.55% | 3.57% | 1.47% | 4.76% | 1.72% | 4.10% | 10.85%
| Peru | Argentina | Colombia
Date | GDP | Unemployment | GDP | Unemployment | GDP | Unemployment
2020 | (11.74) % | 12.75 % | (10.64) % | 13.60 % | (6.80) % | 18.14 %
2021 | 12.56 % | 10.29 % | 9.95 % | 14.39 % | 6.80 % | 16.14 %
2022 | 5.25 % | 10.00 % | 3.52 % | 11.88 % | 3.70 % | 14.53 %
2023 | 3.68 % | 8.73 % | 2.08 % | 8.99 % | 3.15 % | 14.28 %
2024 | 3.58 % | 7.23 % | 2.11 % | 7.69 % | 3.27 % | 12.49 %
2025 | 3.35 % | 6.88 % | 2.14 % | 6.78 % | 3.60 % | 12.28 %
Base scenario of GDP, unemployment rate and HPI for the main geographies
| Spain | Mexico | Turkey
Date | GDP | Unemployment | HPI | GDP | Unemployment | HPI | GDP | Unemployment
2020 | (11.48) | % | 16.95 | % | (1.98) | % | (9.25) | % | 4.62 | % | 1.81 | % | (0.01) | % | 13.98 | %
2021 | 5.99 | % | 17.51 | % | (5.08) | % | 3.71 | % | 5.57 | % | (1.32) | % | 5.52 | % | 14.05 | %
2022 | 6.04 | % | 14.35 | % | 3.48 | % | 3.53 | % | 5.35 | % | 0.15 | % | 4.53 | % | 12.58 | %
2023 | 2.93 | % | 12.41 | % | 5.44 | % | 1.55 | % | 5.19 | % | 0.31 | % | 4.01 | % | 11.95 | %
2024 | 2.07 | % | 11.14 | % | 3.20 | % | 1.45 | % | 5.03 | % | 1.02 | % | 3.99 | % | 11.38 | %
2025 | 2.01 | % | 9.99 | % | 3.12 | % | 1.46 | % | 4.88 | % | 1.71 | % | 3.98 | % | 11.03 | %
| Peru | Argentina | Colombia
Date | GDP | Unemployment | GDP | Unemployment | GDP | Unemployment
2020 | (13.04) % | 12.80 % | (13.00) % | 13.98 % | (7.51) % | 18.23 %
2021 | 10.05 % | 10.48 % | 5.54 % | 15.40 % | 5.48 % | 16.40 %
2022 | 4.52 % | 10.23 % | 2.54 % | 12.80 % | 3.46 % | 14.83 %
2023 | 3.69 % | 8.93 % | 1.98 % | 9.60 % | 3.15 % | 14.57 %
2024 | 3.58 % | 7.41 % | 1.98 % | 8.18 % | 3.27 % | 12.78 %
2025 | 3.35 % | 7.06 % | 2.01 % | 7.28 % | 3.60 % | 12.55 %
Negative scenario of GDP, unemployment rate and HPI for the main geographies
| Spain | Mexico | Turkey
Date | GDP | Unemployment | HPI | GDP | Unemployment | HPI | GDP | Unemployment
2020 | (11.76) % | 17.44 % | (2.60) % | (9.64) % | 4.67 % | 1.89 % | (2.10) % | 14.49 %
2021 | 5.37 % | 18.94 % | (6.69) % | 2.84 % | 5.75 % | (1.48) % | 1.75 % | 15.51 %
2022 | 5.82 % | 15.92 % | 2.49 % | 3.25 % | 5.53 % | (0.06) % | 3.56 % | 13.64 %
2023 | 2.88 % | 13.99 % | 4.94 % | 1.48 % | 5.34 % | 0.17 % | 3.92 % | 12.33 %
2024 | 2.03 % | 12.70 % | 2.45 % | 1.41 % | 5.17 % | 0.99 % | 3.91 % | 11.56 %
2025 | 1.97 % | 11.45 % | 2.36 % | 1.41 % | 5.02 % | 1.70 % | 3.91 % | 11.20 %
| Peru | Argentina | Colombia
Date | GDP | Unemployment | GDP | Unemployment | GDP | Unemployment
2020 | (14.33) % | 12.85 % | (15.28) % | 14.34 % | (8.25) % | 18.31 %
2021 | 7.53 % | 10.69 % | 0.89 % | 16.38 % | 4.16 % | 16.66 %
2022 | 3.78 % | 10.48 % | 1.33 % | 13.69 % | 3.16 % | 15.10 %
2023 | 3.69 % | 9.15 % | 1.86 % | 10.19 % | 3.15 % | 14.84 %
2024 | 3.57 % | 7.62 % | 1.83 % | 8.63 % | 3.27 % | 13.04 %
2025 | 3.35 % | 7.27 % | 1.86 % | 7.75 % | 3.60 % | 12.80 %
Sensitivity to macroeconomic scenarios A sensitivity exercise has been carried out on the expected losses due to variations in the key hypotheses as they are the ones that introduce the greatest uncertainty in estimating such losses. As a first step, GDP and the House Price Index have been identified as the most relevant variables. These variables have been subjected to shocks of +/- 100 bps in their entire window with impact of the macro models. Independent sensitivities have been assessed, under the assumption of assigning a 100% probability to each determined scenario with these independent shocks. Variation in expected loss is determined both by re-staging (that is: in worse scenarios due to the recognition of lifetime credit losses for additional operations that are transferred to stage 2 from stage 1 where 12 months of losses are valued: or vice versa in improvement scenarios) as well as variations in the collective risk parameters (PD and LGD) of each financial instrument due to the changes defined in the macroeconomic forecasts of the scenario.
Expected loss variation as of December 31, 2021
| BBVA Group | Spain | Mexico |  | Turkey |
GDP | Total Portfolio | Retail | Mortgages | Wholesaler | Fixed income | Total Portfolio | Mortgages | Companies | Total Portfolio | Mortgages | Cards | Total Portfolio | Wholesale | Retail
-100pb | 3.44% | 3.18% | 3.43% | 4.87% | 1.87% | 3.33% | 4.03% | 4.16% | 3.73% | 2.06% | 6.57% | 2.39% | 2.03% | 2.67%
+100pb | (3.20)% | (2.96)% | (2.92)% | (4.54)% | (1.82)% | (3.06)% | (3.35)% | (3.97)% | (3.56)% | (1.96)% | (6.07)% | (2.29)% | (2.08)% | (2.47)%
Housing price |  |  |  |  |  |  |  |  |  |  |  |  |  |
-100pb |  |  |  |  |  |  | 5.17% | 0.78% |  | 2.90% |  |  |  |
+100pb |  |  |  |  |  |  | (5.11)% | (0.77)% |  | (2.73)% |  |  |  |
Expected loss variation as of December 31, 2020
| BBVA Group | Spain | Mexico | Turkey
GDP | Total Portfolio | Retail | Mortgages | Wholesaler | Fixed income | Total Portfolio | Mortgages | Companies | Total Portfolio | Mortgages | Cards | Total Portfolio | Wholesale | Retail
-100pb | 3.55% | 3.47% | 3.72% | 3.91% | 1.58% | 3.72% | 4.39% | 3.96% | 3.91% | 2.20% | 6.30% | 1.56% | 1.58% | 1.62%
+100pb | (3.25)% | (3.14)% | (3.03)% | (3.69)% | (1.97)% | (3.32)% | (3.57)% | (3.53)% | (3.64)% | (2.07)% | (5.78)% | (1.47)% | (1.55)% | (1.47)%
Housing price |  |  |  |  |  |  |  |  |  |  |  |  |  |
-100pb |  |  |  |  |  |  | 5.41% | 0.79% |  | 3.13% |  |  |  |
+100pb |  |  |  |  |  |  | (5.35)% | (0.77)% |  | (4.47)% |  |  |  |
Additional adjustments to expected loss measurement In addition to what is described on individualized and collective estimates of expected losses and macroeconomic estimates, the Group may supplement the expected losses if it deems it necessary to account for the effects that may not be included, either by considering risk drivers or by the incorporation of sectorial particularities or that may affect a set of operations or borrowers. These adjustments should be temporary, until the reasons that motivated them disappear or materialize. For this reason, the expected losses have been supplemented with additional amounts that have been considered necessary to collect the particular characteristics of borrowers, sectors or portfolios and that may not be identified in the general process. In order to incorporate those effects that are not included in the impairment models, management adjustments to the expected losses exist, which amounted to €311 million as of December 31, 2021 (€226 million in Spain, €18 million in Peru and €68 million in Mexico). As of December 31, 2020 there were €223 million in Spain. The variation in 2021 in Spain and Peru is driven by an additional provision given the possibility of new extensions in the financing granted or agreements aimed at ensuring business viability as well as a charge in Mexico for the anticipation of the potential credit deterioration following the expiration of payment deferrals. Credit risk exposure In accordance with IFRS 7 “Financial instruments: Disclosures”, the BBVA Group’s credit risk exposure by headings in the balance sheets as of December 31, 2021, 2020 and 2019 is provided below. It does not consider the loss allowances and the availability of collateral or other credit enhancements to enable compliance with payment obligations. The details are broken down by financial instruments and counterparties:
Maximum credit risk exposure (Millions of Euros)
| Notes | December 2021 | Stage 1 | Stage 2 | Stage 3
Financial assets held for trading |  | 92,560 |  |  |
Equity instruments | 10 | 15,963 |  |  |
Debt securities | 10 | 25,790 |  |  |
Loans and advances | 10 | 50,807 |  |  |
Non-trading financial assets mandatorily at fair value through profit or loss |  | 6,086 |  |  |
Equity instruments | 11 | 5,303 |  |  |
Debt securities | 11 | 128 |  |  |
Loans and advances | 11 | 655 |  |  |
Financial assets designated at fair value through profit or loss | 12 | 1,092 |  |  |
Derivatives (trading and hedging) |  | 43,687 |  |  |
Financial assets at fair value through other comprehensive income |  | 60,495 |  |  |
Equity instruments | 13 | 1,320 |  |  |
Debt securities |  | 59,148 | 58,587 | 561 | —
Loans and advances to credit institutions | 13 | 27 | 27 | — | —
Financial assets at amortized cost |  | 383,870 | 334,772 | 34,418 | 14,680
Debt securities |  | 34,833 | 34,605 | 205 | 22
Loans and advances to central banks |  | 5,687 | 5,687 | — | —
Loans and advances to credit institutions |  | 13,295 | 13,285 | 10 | —
Loans and advances to customers |  | 330,055 | 281,195 | 34,203 | 14,657
Total financial assets risk |  | 587,789 |  |  |
Total loan commitments and financial guarantees |  | 165,941 | 152,914 | 12,070 | 957
Loan commitments given | 33 | 119,618 | 112,494 | 6,953 | 171
Financial guarantees given | 33 | 11,720 | 10,146 | 1,329 | 245
Other commitments given | 33 | 34,604 | 30,274 | 3,789 | 541
Total maximum credit exposure |  | 753,730 |  |  |
Maximum credit risk exposure (Millions of Euros)
| Notes | December 2020 | Stage 1 | Stage 2 | Stage 3
Financial assets held for trading |  | 65,696 |  |  |
Equity instruments | 10 | 11,458 |  |  |
Debt securities | 10 | 23,970 |  |  |
Loans and advances | 10 | 30,268 |  |  |
Non-trading financial assets mandatorily at fair value through profit or loss |  | 5,198 |  |  |
Equity instruments | 11 | 4,133 |  |  |
Debt securities | 11 | 356 |  |  |
Loans and advances | 11 | 709 |  |  |
Financial assets designated at fair value through profit or loss | 12 | 1,117 |  |  |
Derivatives (trading and hedging) |  | 46,302 |  |  |
Financial assets at fair value through other comprehensive income |  | 69,537 |  |  |
Equity instruments | 13 | 1,100 |  |  |
Debt securities |  | 68,404 | 67,995 | 410 | —
Loans and advances to credit institutions | 13 | 33 | 33 | — | —
Financial assets at amortized cost |  | 379,857 | 334,552 | 30,607 | 14,698
Debt securities |  | 35,785 | 35,759 | 6 | 20
Loans and advances to central banks |  | 6,229 | 6,229 | — | —
Loans and advances to credit institutions |  | 14,591 | 14,565 | 20 | 6
Loans and advances to customers |  | 323,252 | 277,998 | 30,581 | 14,672
Total financial assets risk |  | 567,705 |  |  |
Total loan commitments and financial guarantees |  | 179,440 | 165,726 | 12,682 | 1,032
Loan commitments given | 33 | 132,584 | 124,104 | 8,214 | 265
Financial guarantees given | 33 | 10,665 | 9,208 | 1,168 | 290
Other commitments given | 33 | 36,190 | 32,414 | 3,300 | 477
Total maximum credit exposure |  | 747,145 |  |  |
Maximum credit risk exposure (Millions of Euros)
| Notes | December 2019 | Stage 1 | Stage 2 | Stage 3
Financial assets held for trading |  | 67,238 |  |  |
Equity instruments | 10 | 8,892 |  |  |
Debt securities | 10 | 26,309 |  |  |
Loans and advances | 10 | 32,037 |  |  |
Non-trading financial assets mandatorily at fair value through profit or loss |  | 5,557 |  |  |
Equity instruments | 11 | 4,327 |  |  |
Debt securities | 11 | 110 |  |  |
Loans and advances | 11 | 1,120 |  |  |
Financial assets designated at fair value through profit or loss | 12 | 1,214 |  |  |
Derivatives (trading and hedging) |  | 39,462 |  |  |
Financial assets at fair value through other comprehensive income |  | 61,293 |  |  |
Equity instruments | 13 | 2,420 |  |  |
Debt securities |  | 58,841 | 58,590 | 250 | —
Loans and advances to credit institutions | 13 | 33 | 33 | — | —
Financial assets at amortized cost |  | 451,640 | 402,024 | 33,624 | 15,993
Debt securities |  | 38,930 | 38,790 | 106 | 33
Loans and advances to central banks |  | 4,285 | 4,285 | — | —
Loans and advances to credit institutions |  | 13,664 | 13,500 | 158 | 6
Loans and advances to customers |  | 394,763 | 345,449 | 33,360 | 15,954
Total financial assets risk |  | 626,404 |  |  |
Total loan commitments and financial guarantees |  | 181,116 | 169,663 | 10,452 | 1,001
Loan commitments given | 33 | 130,923 | 123,707 | 6,945 | 270
Financial guarantees given | 33 | 10,984 | 9,804 | 955 | 224
Other commitments given | 33 | 39,209 | 36,151 | 2,552 | 506
Total maximum credit exposure |  | 807,520 |  |  |
The maximum credit exposure presented in the table above is determined by type of financial asset as explained below: –In the case of financial instruments recognized in the consolidated balance sheets, exposure to credit risk is considered equal to its carrying amount (not including loss allowances) with the only exception of trading and hedging derivatives. –The maximum credit risk exposure on financial commitments and guarantees granted is the maximum that the Group would be liable for if these guarantees were called in, or the higher amount pending to be disposed from the customer in the case of commitments. –The calculation of risk exposure for derivatives is based on the sum of two factors: the derivatives fair value and their potential risk (or "add-on"). The breakdown by geographical location and Stage of the maximum credit risk exposure, the accumulated allowances recorded and the carrying amount of the loans and advances to customers as of December 31, 2021, 2020 and 2019 is shown below:
December 2021 (Millions of Euros)
| Gross exposure | Accumulated allowances | Carrying amount
| Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3
Spain (*) | 201,405 | 171,883 | 21,380 | 8,143 | (5,277) | (722) | (923) | (3,631) | 196,129 | 171,161 | 20,457 | 4,511
Mexico | 57,847 | 51,665 | 4,261 | 1,921 | (2,038) | (740) | (381) | (916) | 55,809 | 50,925 | 3,880 | 1,005
Turkey (**) | 33,472 | 26,497 | 4,134 | 2,841 | (2,058) | (224) | (424) | (1,410) | 31,414 | 26,273 | 3,711 | 1,431
South America (***) | 36,335 | 30,166 | 4,425 | 1,744 | (1,736) | (277) | (362) | (1,096) | 34,599 | 29,889 | 4,062 | 648
Others | 996 | 984 | 3 | 9 | (8) | (1) | — | (7) | 988 | 983 | 3 | 2
Total (****) | 330,055 | 281,195 | 34,203 | 14,657 | (11,116) | (1,964) | (2,091) | (7,061) | 318,939 | 279,231 | 32,112 | 7,596
Of which: individual |  |  |  |  | (2,528) | (4) | (657) | (1,867) |  |  |  |
Of which: collective |  |  |  |  | (8,587) | (1,959) | (1,434) | (5,194) |  |  |  |
(*) Spain includes all countries where BBVA, S.A. operates. (**) Turkey includes all countries in which Garanti BBVA operates. (***) In South America, BBVA Group operates mainly in Argentina, Colombia, Peru and Uruguay. (****) The amount of the accumulated allowances includes the provisions recorded for credit risk over the remaining expected lifetime of purchased financial instruments. Those provisions were determined at the moment of the Purchase Price Allocation and were originated mainly in the acquisition of Catalunya Banc S.A. (as of December 31, 2021, the remaining balance was €266 million). These valuation adjustments are recognized in the consolidated income statement during the residual life of the operations or are applied to the value corrections when the losses materialize.
December 2020 (Millions of Euros)
|  | Gross exposure |  | Accumulated allowances |  | Carrying amount
| Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3
Spain (*) | 195,983 | 171,397 | 16,387 | 8,199 | (5,679) | (753) | (849) | (4,077) | 190,304 | 170,644 | 15,538 | 4,122
Mexico | 52,211 | 46,373 | 4,071 | 1,767 | (2,211) | (685) | (442) | (1,083) | 50,000 | 45,688 | 3,628 | 684
Turkey (**) | 39,633 | 30,832 | 5,806 | 2,995 | (2,338) | (246) | (535) | (1,557) | 37,295 | 30,586 | 5,272 | 1,438
South America (***) | 34,499 | 28,484 | 4,312 | 1,703 | (1,870) | (320) | (460) | (1,090) | 32,629 | 28,165 | 3,852 | 612
Others | 925 | 912 | 5 | 8 | (7) | (1) | — | (6) | 918 | 911 | 4 | 2
Total (****) | 323,252 | 277,998 | 30,581 | 14,672 | (12,105) | (2,005) | (2,287) | (7,813) | 311,147 | 275,993 | 28,294 | 6,860
Of which: individual |  |  |  |  | (2,611) | (10) | (479) | (2,122) |  |  |  |
Of which: collective |  |  |  |  | (9,494) | (1,995) | (1,808) | (5,691) |  |  |  |
(*) Spain includes all countries where BBVA, S.A. operates. (**) Turkey includes all countries in which Garanti BBVA operates. (***) In South America, BBVA Group operates mainly in Argentina, Colombia, Peru and Uruguay. (****) The amount of the accumulated allowances includes the provisions recorded for credit risk over the remaining expected lifetime of purchased financial instruments. Those provisions were determined at the moment of the Purchase Price Allocation and were originated mainly in the acquisition of Catalunya Banc S.A. (as of December 31, 2020 the remaining balance was €363 million). These valuation adjustments are recognized in the consolidated income statement during the residual life of the operations or are applied to the value corrections when the losses materialize.
December 2019 (Millions of Euros)
| Gross exposure | Accumulated allowances | Carrying amount
| Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3
Spain (*) | 197,058 | 173,843 | 14,599 | 8,616 | (5,311) | (712) | (661) | (3,939) | 191,747 | 173,131 | 13,939 | 4,677
The United States | 57,387 | 49,744 | 7,011 | 632 | (688) | (165) | (342) | (182) | 56,699 | 49,580 | 6,670 | 450
Mexico | 60,099 | 54,748 | 3,873 | 1,478 | (2,013) | (697) | (404) | (912) | 58,087 | 54,052 | 3,469 | 566
Turkey (**) | 43,113 | 34,536 | 5,127 | 3,451 | (2,613) | (189) | (450) | (1,974) | 40,500 | 34,347 | 4,677 | 1,477
South America (***) | 36,265 | 31,754 | 2,742 | 1,769 | (1,769) | (366) | (323) | (1,079) | 34,497 | 31,388 | 2,419 | 690
Others | 839 | 824 | 7 | 9 | (8) | (1) | (1) | (6) | 832 | 823 | 6 | 2
Total (****) | 394,763 | 345,449 | 33,360 | 15,954 | (12,402) | (2,129) | (2,181) | (8,093) | 382,360 | 343,320 | 31,179 | 7,861
Of which: individual |  |  |  |  | (2,795) | (6) | (347) | (2,441) |  |  |  |
Of which: collective |  |  |  |  | (9,608) | (2,123) | (1,834) | (5,652) |  |  |  |
(*) Spain includes all countries where BBVA, S.A. operates. (**) Turkey includes all countries in which Garanti BBVA operates. (***) In South America, BBVA Group operates mainly in Argentina, Colombia, Peru and Uruguay. (****) The amount of the accumulated allowances includes the provisions recorded for credit risk over the remaining expected lifetime of purchased financial instruments. Those provisions were determined at the moment of the Purchase Price Allocation and were originated mainly in the acquisition of Catalunya Banc S.A. (as of December 31, 2019 the remaining balance was €433 million). These valuation adjustments are recognized in the consolidated income statement during the residual life of the operations or are applied to the value corrections when the losses materialize. The breakdown by counterparty of the maximum credit risk exposure, the accumulated allowances recorded, as well as the carrying amount by stages of loans and advances to customers as of December 31, 2021, 2020 and 2019 is shown below:
December 2021 (Millions of Euros)
| Gross exposure | Accumulated allowances | Net amount
| Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3
Public administrations | 19,719 | 19,287 | 369 | 62 | (37) | (13) | (5) | (19) | 19,682 | 19,274 | 364 | 43
Other financial corporations | 9,826 | 9,672 | 131 | 24 | (23) | (8) | (6) | (9) | 9,804 | 9,664 | 125 | 15
Non-financial corporations | 146,797 | 120,140 | 19,366 | 7,290 | (5,804) | (759) | (1,306) | (3,738) | 140,993 | 119,381 | 18,060 | 3,552
Households | 153,714 | 132,096 | 14,336 | 7,281 | (5,253) | (1,184) | (773) | (3,295) | 148,461 | 130,912 | 13,563 | 3,986
Loans and advances to customers | 330,055 | 281,195 | 34,203 | 14,657 | (11,116) | (1,964) | (2,091) | (7,061) | 318,939 | 279,231 | 32,112 | 7,596
December 2020 (Millions of Euros)
| Gross exposure | Accumulated allowances | Net amount
| Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3
Public administrations | 19,439 | 19,163 | 200 | 76 | (48) | (14) | (9) | (25) | 19,391 | 19,149 | 191 | 51
Other financial corporations | 9,856 | 9,747 | 95 | 14 | (39) | (25) | (6) | (7) | 9,817 | 9,722 | 88 | 7
Non-financial corporations | 142,547 | 119,891 | 15,179 | 7,477 | (6,123) | (774) | (1,110) | (4,239) | 136,424 | 119,117 | 14,069 | 3,238
Households | 151,410 | 129,196 | 15,108 | 7,106 | (5,895) | (1,192) | (1,161) | (3,542) | 145,515 | 128,005 | 13,946 | 3,564
Loans and advances to customers | 323,252 | 277,998 | 30,581 | 14,672 | (12,105) | (2,005) | (2,287) | (7,813) | 311,147 | 275,993 | 28,294 | 6,860
December 2019 (Millions of Euros)
| Gross exposure | Accumulated allowances | Net amount
| Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3 | Total | Stage 1 | Stage 2 | Stage 3
Public administrations | 28,281 | 27,511 | 682 | 88 | (59) | (15) | (22) | (21) | 28,222 | 27,496 | 660 | 66
Other financial corporations | 11,239 | 11,085 | 136 | 17 | (31) | (19) | (2) | (10) | 11,207 | 11,066 | 134 | 8
Non-financial corporations | 173,254 | 148,768 | 16,018 | 8,468 | (6,465) | (811) | (904) | (4,750) | 166,789 | 147,957 | 15,114 | 3,718
Households | 181,989 | 158,085 | 16,523 | 7,381 | (5,847) | (1,283) | (1,252) | (3,312) | 176,142 | 156,801 | 15,272 | 4,069
Loans and advances to customers | 394,763 | 345,449 | 33,360 | 15,954 | (12,402) | (2,129) | (2,181) | (8,093) | 382,360 | 343,320 | 31,179 | 7,861
The breakdown by counterparty and product of loans and advances, net of loss allowances, as well as the gross carrying amount by type of product, classified in different headings of the assets, as of December 31, 2021, 2020 and 2019 is shown below:
December 2021 (Millions of Euros)
| Central banks | General governments | Credit institutions | Other financial corporations | Non-financial corporations | Households | Total | Gross carrying amount
On demand and short notice | — | 6 | — | 321 | 2,339 | 495 | 3,161 | 3,345
Credit card debt | — | — | — | 1 | 1,504 | 12,523 | 14,030 | 14,949
Commercial debtors |  | 791 | — | 476 | 18,191 | 66 | 19,524 | 19,766
Finance leases | — | 191 | — | 14 | 7,388 | 317 | 7,911 | 8,256
Reverse repurchase loans | 1,192 | — | 2,788 | 23 | — | — | 4,004 | 4,013
Other term loans | 4,174 | 18,440 | 4,004 | 5,413 | 110,204 | 134,505 | 276,739 | 286,127
Advances that are not loans | 315 | 394 | 6,510 | 3,554 | 1,805 | 630 | 13,208 | 13,263
LOANS AND ADVANCES | 5,681 | 19,822 | 13,303 | 9,804 | 141,431 | 148,536 | 338,577 | 349,719
By secured loans |  |  |  |  |  |  |  |
Of which: mortgage loans collateralized by immovable property |  | 324 | — | 220 | 21,531 | 94,821 | 116,897 | 119,980
Of which: other collateralized loans | 1,180 | 1,413 | 2,534 | 390 | 3,512 | 1,950 | 10,979 | 11,335
By purpose of the loan |  |  |  |  |  |  |  |
Of which: credit for consumption |  |  |  |  |  | 42,294 | 42,294 | 45,236
Of which: lending for house purchase |  |  |  |  |  | 95,209 | 95,209 | 96,612
By subordination |  |  |  |  |  |  |  |
Of which: project finance loans |  |  |  |  | 8,863 |  | 8,863 | 9,423
December 2020 (Millions of Euros) |  |  |  |  |  |  |  |
| Central banks | General governments | Credit institutions | Other financial corporations | Non-financial corporations | Households | Total | Gross carrying amount
On demand and short notice | — | 7 | — | 502 | 1,798 | 528 | 2,835 | 3,021
Credit card debt | — | — | — | 2 | 1,485 | 11,605 | 13,093 | 14,220
Commercial debtors |  | 898 | — | 317 | 14,262 | 67 | 15,544 | 15,796
Finance leases | — | 197 | — | 6 | 7,125 | 322 | 7,650 | 8,013
Reverse repurchase loans | 472 | — | 1,914 | — | 71 | — | 2,457 | 2,463
Other term loans | 5,690 | 18,111 | 3,972 | 5,799 | 111,141 | 132,603 | 277,317 | 287,467
Advances that are not loans | 48 | 260 | 8,721 | 3,191 | 1,084 | 473 | 13,777 | 13,833
LOANS AND ADVANCES | 6,209 | 19,475 | 14,608 | 9,817 | 136,966 | 145,598 | 332,672 | 344,813
By secured loans |  |  |  |  |  |  |  |
Of which: mortgage loans collateralized by immovable property |  | 372 | — | 209 | 22,091 | 94,147 | 116,819 | 120,194
Of which: other collateralized loans | 472 | 952 | — | 317 | 3,763 | 2,059 | 7,562 | 7,776
By purpose of the loan |  |  |  |  |  |  |  |
Of which: credit for consumption |  |  |  |  |  | 39,799 | 39,799 | 43,037
Of which: lending for house purchase |  |  |  |  |  | 94,098 | 94,098 | 95,751
By subordination |  |  |  |  |  |  |  |
Of which: project finance loans |  |  |  |  | 10,721 |  | 10,721 | 11,032
December 2019 (Millions of Euros) |  |  |  |  |  |  |  |
| Central banks | General governments | Credit institutions | Other financial corporations | Non-financial corporations | Households | Total | Gross carrying amount
On demand and short notice | — | 9 | — | 118 | 2,328 | 595 | 3,050 | 3,251
Credit card debt | — | 10 | 1 | 3 | 1,940 | 14,401 | 16,355 | 17,608
Commercial debtors |  | 971 | — | 230 | 15,976 | 99 | 17,276 | 17,617
Finance leases | — | 227 | — | 6 | 8,091 | 387 | 8,711 | 9,095
Reverse repurchase loans | — | — | 1,817 | — | 26 | — | 1,843 | 1,848
Other term loans | 4,240 | 26,734 | 4,121 | 7,795 | 137,934 | 160,223 | 341,047 | 351,230
Advances that are not loans | 35 | 865 | 7,743 | 3,056 | 951 | 506 | 13,156 | 13,214
LOANS AND ADVANCES | 4,275 | 28,816 | 13,682 | 11,208 | 167,246 | 176,211 | 401,438 | 413,863
By secured loans |  |  |  |  |  |  |  |
Of which: mortgage loans collateralized by immovable property |  | 1,067 | 15 | 261 | 23,575 | 111,085 | 136,003 | 139,317
Of which: other collateralized loans | — | 10,447 | 93 | 2,106 | 29,009 | 6,893 | 48,548 | 49,266
By purpose of the loan |  |  |  |  |  |  |  |
Of which: credit for consumption |  |  |  |  |  | 46,356 | 46,356 | 49,474
Of which: lending for house purchase |  |  |  |  |  | 110,178 | 110,178 | 111,636
By subordination |  |  |  |  |  |  |  |
Of which: project finance loans |  |  |  |  | 12,259 |  | 12,259 | 12,415
Mitigation of credit risk, collateralized credit risk and other credit enhancementsIn certain cases, maximum credit risk exposure is reduced by collateral, credit enhancements and other actions which mitigate the Group’s exposure. The BBVA Group applies a credit risk hedging and mitigation policy deriving from a banking approach focused on relationship banking. The existence of guarantees could be a necessary but not sufficient instrument for accepting risks, as the assumption of risks by the Group requires prior evaluation of the debtor’s capacity for repayment, or that the debtor can generate sufficient resources to allow the amortization of the risk incurred under the agreed terms. The policy of accepting risks is therefore organized into three different levels in the BBVA Group: –Analysis of the financial risk of the transaction, based on the debtor’s capacity for repayment or generation of funds. –The constitution of guarantees that are adequate, or at any rate generally accepted, for the risk assumed, in any of the generally accepted forms: monetary, secured, personal or hedge guarantees; and finally –Assessment of the repayment risk (asset liquidity) of the guarantees received. This is carried out through a prudent risk policy that consists of the analysis of the financial risk, based on the capacity for reimbursement or generation of resources of the borrower, the analysis of the guarantee, assessing, among others, the efficiency, the robustness and the risk, the adequacy of the guarantee with the operation and other aspects such as the location, currency, concentration or the existence of limitations. Additionally, the necessary tasks for the constitution of guarantees must be carried out - in any of the generally accepted forms (collaterals, personal guarantees and financial hedge instruments) - appropriate to the risk assumed. The procedures for the management and valuation of collateral are set out in the corporate general policies (retail and wholesale), which establish the basic principles for credit risk management, including the management of collaterals assigned in transactions with customers. The criteria for the systematic, standardized and effective treatment of collateral in credit transaction procedures in BBVA Group’s wholesale and retail banking are included in the Specific Collateral Rules. The methods used to value the collateral are in line with the best market practices and imply the use of appraisal of real-estate collateral, the market price in market securities, the trading price of shares in mutual funds, etc. All the collaterals received must be correctly assigned and entered in the corresponding register. They must also have the approval of the Group’s legal units. The valuation of the collateral is taken into account in the calculation of the expected losses. The Group has developed internal models to estimate the realization value of the collaterals received, the time that elapses until then, the costs for their acquisition, maintenance and subsequent sale, from real observations based on its own experience. This modeling is part of the LGD estimation processes that are applied to the different segments, and is included within the annual review and validation procedures. The following is a description of the main types of collateral for each financial instrument class: –Debt instruments held for trading: The guarantees or credit enhancements obtained directly from the issuer or counterparty are implicit in the clauses of the instrument (mainly guarantees of the issuer). –Derivatives and hedging derivatives: In derivatives, credit risk is minimized through contractual netting agreements, where positive- and negative-value derivatives with the same counterparty are offset for their net balance. There may likewise be other kinds of guarantees and collaterals, depending on counterparty solvency and the nature of the transaction (mainly collaterals). The summary of the offsetting effect (via netting and collateral) for derivatives and securities operations as of December 31, 2021 is presented in Note 7.4.2. –Other financial assets designated at fair value through profit or loss and financial assets at fair value through other comprehensive income: The guarantees or credit enhancements obtained directly from the issuer or counterparty are inherent to the structure of the instrument (mainly personal guarantees). As of December 31, 2021, 2020 and 2019, BBVA Group had no credit risk exposure of impaired financial assets at fair value through other comprehensive income (see Note 7.2.2). –Financial assets at amortized cost: a.Loans and advances to credit institutions: These usually have the counterparty’s personal guarantee or pledged securities in the case of repos. b.Loans and advances to customers: Most of these loans and advances are backed by personal guarantees extended by the customer. There may also be collateral to secure loans and advances to customers (such as mortgages, cash collaterals, pledged securities and other collateral), or to obtain other credit enhancements (bonds or insurances). c.Debt securities: The guarantees or credit enhancements obtained directly from the issuer or counterparty are inherent to the structure of the instrument. –Financial guarantees, other contingent risks and drawable by third parties: these have the counterparty’s personal guarantee or other types of collaterals. The disclosure of impaired loans and advances at amortized cost covered by collateral (see Note 7.2.6), by type of collateral, as of December 31, 2021, 2020 and 2019, is the following:
Impaired loans and advances at amortized cost covered by collateral (Millions of Euros)
| Maximum exposure to credit risk | Of which secured by collateral
| Residential properties | Commercial properties | Cash | Others | Financial
December 2021 | 14,657 | 2,875 | 1,068 | 5 | 33 | 886
December 2020 | 14,678 | 2,717 | 789 | 18 | 52 | 575
December 2019 | 15,959 | 3,396 | 939 | 35 | 221 | 542
The value of guarantees received as of December 31, 2021, 2020 and 2019, is the following:
Guarantees received (Millions of Euros) |  |  |  |  |  |  |
| 2021 | 2020 | 2019 |  |  |  |
Value of collateral | 117,362 | 116,900 | 152,454 |  |  |  |
Of which: guarantees normal risks under special monitoring | 11,768 | 11,296 | 14,623 |  |  |  |
Of which: guarantees non-performing risks | 3,981 | 3,577 | 4,590 |  |  |  |
Value of other guarantees | 48,680 | 47,012 | 35,464 |  |  |  |
Of which: guarantees normal risks under special monitoring | 7,404 | 4,045 | 3,306 |  |  |  |
Of which: guarantees non-performing risks | 886 | 575 | 542 |  |  |  |
Total value of guarantees received | 166,042 | 163,912 | 187,918 |  |  |  |
The maximum credit risk exposure of impaired financial guarantees and other commitments at December 31, 2021, 2020 and 2019 amounts to €957, €1,032 and €1,001 million, respectively (see Note 7.2.2). Credit quality of financial assets that are neither past due nor impaired The BBVA Group has tools that enable it to rank the credit quality of its transactions and customers based on an assessment and its correspondence with the probability of default (“PD”) scales. To analyze the performance of PD, the Group has a series of tracking tools and historical databases that collect the pertinent internally generated information. These tools can be grouped together into scoring and rating models. Scoring Scoring is a decision-making model that contributes to both the arrangement and management of retail loans: consumer loans, mortgages, credit cards for individuals, etc. Scoring is the tool used to decide to originate a loan, what amount should be originated and what strategies can help establish the price, because it is an algorithm that sorts transactions by their credit quality. This algorithm enables the BBVA Group to assign a score to each transaction requested by a customer, on the basis of a series of objective characteristics that have statistically been shown to distinguish between the quality and risk of this type of transactions. The advantage of scoring lies in its simplicity and homogeneity: all that is needed is a series of objective data for each customer, and this data is analyzed automatically using an algorithm. There are three types of scoring, based on the information used and on its purpose: –Reactive scoring: measures the risk of a transaction requested by an individual using variables relating to the requested transaction and to the customer’s socio-economic data available at the time of the request. The new transaction is approved or rejected depending on the score. –Behavioral scoring: scores transactions for a given product in an outstanding risk portfolio of the entity, enabling the credit rating to be tracked and the customer’s needs to be anticipated. It uses transaction and customer variables available internally. Specifically, variables that refer to the behavior of both the product and the customer. –Proactive scoring: gives a score at customer level using variables related to the individual’s general behavior with the entity, and to his/her payment behavior in all the contracted products. The purpose is to track the customer’s credit quality and it is used to pre-approve new transactions. Rating Rating tools, as opposed to scoring tools, do not assess transactions but focus on the rating of customers instead: companies, corporations, SMEs, general governments, etc. A rating tool is an instrument that, based on a detailed financial study, helps determine a customer’s ability to meet his/her financial obligations. The final rating is usually a combination of various factors: on one hand, quantitative factors, and on the other hand, qualitative factors. It is a middle road between an individual analysis and a statistical analysis. The main difference between ratings and scorings is that the latter are used to assess retail products, while ratings use a wholesale banking customer approach. Moreover, scorings only include objective variables, while ratings add qualitative information. And although both are based on statistical studies, adding a business view, rating tools give more weight to the business criterion compared to scoring tools. For portfolios where the number of defaults is low (sovereign risk, corporates, financial entities, etc.) the internal information is supplemented by “benchmarking” of the external rating agencies (Moody’s, Standard & Poor’s and Fitch). To this end, each year the PDs compiled by the rating agencies at each level of risk rating are compared, and the measurements compiled by the various agencies are mapped against those of the BBVA master rating scale. The probability of default of transactions or customers is calibrated with a long-term view, since its purpose is to measure the risk quality beyond its time of estimation, seeking to capture information representative of the behavior of the portfolios during a complete economic cycle (a long-term average probability of default). This probability is mapped to the master scale developed by the BBVA Group in order to facilitate a homogeneous classification of its different risk portfolios. The table below shows the abridged scale used to classify the BBVA Group’s outstanding risk as of December 31, 2021:
| Internal rating | Probability of default (basis points)
| Reduced List (22 groups) | Average | Minimum from >= | Maximum
| AAA | 1 | — | 2
| AA+ | 2 | 2 | 3
| AA | 3 | 3 | 4
| AA- | 4 | 4 | 5
| A+ | 5 | 5 | 6
| A | 8 | 6 | 9
| A- | 10 | 9 | 11
| BBB+ | 14 | 11 | 17
| BBB | 20 | 17 | 24
| BBB- | 31 | 24 | 39
| BB+ | 51 | 39 | 67
| BB | 88 | 67 | 116
| BB- | 150 | 116 | 194
| B+ | 255 | 194 | 335
| B | 441 | 335 | 581
| B- | 785 | 581 | 1,061
| CCC+ | 1,191 | 1,061 | 1,336
| CCC | 1,500 | 1,336 | 1,684
| CCC- | 1,890 | 1,684 | 2,121
| CC+ | 2,381 | 2,121 | 2,673
| CC | 3,000 | 2,673 | 3,367
| CC- | 3,780 | 3,367 | 4,243
These different levels and their probability of default were calculated by using as a reference the rating scales and default rates provided by the external agencies Standard & Poor’s and Moody’s. These calculations establish the levels of probability of default for the BBVA Group’s Master Rating Scale. Although this scale is common to the entire Group, the calibrations (mapping scores to PD sections/Master Rating Scale levels) are carried out at tool level for each country in which the Group has tools available. The table below outlines the distribution by probability of default within 12 months and through the lifetime of the asset, and stages of the gross carrying amount of loans and advances to customers in percentage terms of the BBVA Group as of December 31, 2021, 2020 and 2019:
Probability of default (basis points)
| 2021 | 2020 | 2019
| Subject to 12 month ECL (Stage 1) | Subject to lifetime ECL (Stage 2) | Subject to 12 month ECL (Stage 1) | Subject to lifetime ECL (Stage 2) | Subject to 12 month ECL (Stage 1) | Subject to lifetime ECL (Stage 2)
| % | % | % | % | % | %
0 to 2 | 5.8 | — | 4.0 | — | 5.5 | —
2 to 5 | 15.7 | 0.1 | 10.2 | 0.1 | 6.3 | —
5 to 11 | 15.2 | 0.2 | 7.7 | 0.1 | 14.6 | 0.2
11 to 39 | 18.7 | 0.6 | 26.8 | 0.5 | 24.5 | 0.8
39 to 194 | 19.1 | 2.5 | 24.0 | 2.3 | 24.5 | 1.6
194 to 1,061 | 12.2 | 3.8 | 15.1 | 3.4 | 14.0 | 3.6
1,061 to 2,121 | 1.9 | 1.5 | 1.5 | 1.2 | 1.4 | 1.2
> 2,121 | 0.8 | 1.9 | 0.6 | 2.5 | 0.4 | 1.5
Total | 89.4 | 10.6 | 89.9 | 10.1 | 91.0 | 9.0
Impaired loan risks The breakdown of loans and advances within financial assets at amortized cost, by impaired amount, accumulated impairment, gross carrying amount and by counterparties, as of December 31, 2021, 2020 and 2019 is as follows:
December 2021 (Millions of Euros) |  |  |  |
| Gross carrying amount | Impaired loans and advances | Accumulated impairment | Impaired loans and advances as a % of the total
Central banks | 5,687 | — | (6) | — | %
General governments | 19,719 | 62 | (37) | 0.3 | %
Credit institutions | 13,295 | — | (19) | — | %
Other financial corporations | 9,826 | 24 | (23) | 0.2 | %
Non-financial corporations | 146,797 | 7,290 | (5,804) | 5.0 | %
Agriculture, forestry and fishing | 4,077 | 125 | (154) | 3.1 | %
Mining and quarrying | 4,889 | 222 | (130) | 4.5 | %
Manufacturing | 35,058 | 1,003 | (867) | 2.9 | %
Electricity, gas, steam and air conditioning supply | 13,718 | 570 | (489) | 4.2 | %
Water supply | 782 | 22 | (21) | 2.9 | %
Construction | 8,336 | 894 | (619) | 10.7 | %
Wholesale and retail trade | 25,856 | 1,311 | (1,104) | 5.1 | %
Transport and storage | 10,310 | 879 | (400) | 8.5 | %
Accommodation and food service activities | 7,693 | 470 | (405) | 6.1 | %
Information and communications | 6,533 | 117 | (56) | 1.8 | %
Financial and insurance activities | 6,216 | 197 | (181) | 3.2 | %
Real estate activities | 9,438 | 719 | (466) | 7.6 | %
Professional, scientific and technical activities | 3,910 | 185 | (152) | 4.7 | %
Administrative and support service activities | 3,046 | 181 | (132) | 5.9 | %
Public administration and defense; compulsory social security | 203 | 9 | (11) | 4.5 | %
Education | 582 | 43 | (34) | 7.4 | %
Human health services and social work activities | 1,888 | 48 | (41) | 2.5 | %
Arts, entertainment and recreation | 1,011 | 209 | (95) | 20.7 | %
Other services | 3,250 | 84 | (447) | 2.6 | %
Households | 153,714 | 7,281 | (5,253) | 4.7 | %
LOANS AND ADVANCES | 349,037 | 14,657 | (11,142) | 4.2 | %
December 2020 (Millions of Euros) |  |  |  |
| Gross carrying amount | Impaired loans and advances | Accumulated impairment | Impaired loans and advances as a % of the total
Central banks | 6,229 | — | (20) | — | %
General governments | 19,439 | 76 | (48) | 0.4 | %
Credit institutions | 14,591 | 6 | (16) | — | %
Other financial corporations | 9,856 | 14 | (39) | 0.1 | %
Non-financial corporations | 142,547 | 7,477 | (6,123) | 5.2 | %
Agriculture, forestry and fishing | 3,438 | 132 | (108) | 3.8 | %
Mining and quarrying | 4,349 | 47 | (59) | 1.1 | %
Manufacturing | 33,771 | 1,486 | (1,129) | 4.4 | %
Electricity, gas, steam and air conditioning supply | 13,490 | 591 | (509) | 4.4 | %
Water supply | 899 | 17 | (15) | 1.9 | %
Construction | 10,019 | 1,397 | (722) | 13.9 | %
Wholesale and retail trade | 24,594 | 1,456 | (1,223) | 5.9 | %
Transport and storage | 8,117 | 489 | (368) | 6.0 | %
Accommodation and food service activities | 8,337 | 358 | (294) | 4.3 | %
Information and communications | 5,764 | 73 | (60) | 1.3 | %
Financial and insurance activities | 5,298 | 123 | (132) | 2.3 | %
Real estate activities | 10,025 | 617 | (494) | 6.2 | %
Professional, scientific and technical activities | 2,886 | 177 | (124) | 6.1 | %
Administrative and support service activities | 3,955 | 142 | (192) | 3.6 | %
Public administration and defense, compulsory social security | 129 | 5 | (4) | 3.5 | %
Education | 665 | 54 | (43) | 8.1 | %
Human health services and social work activities | 1,812 | 67 | (59) | 3.7 | %
Arts, entertainment and recreation | 1,131 | 46 | (65) | 4.1 | %
Other services | 3,871 | 198 | (523) | 5.1 | %
Households | 151,410 | 7,106 | (5,895) | 4.7 | %
LOANS AND ADVANCES | 344,072 | 14,678 | (12,141) | 4.3 | %
December 2019 (Millions of Euros) |  |  |  |
| Gross carrying amount | Impaired loans and advances | Accumulated impairment | Impaired loans and advances as a % of the total
Central banks | 4,285 | — | (9) | — | %
General governments | 28,281 | 88 | (60) | 0.3 | %
Credit institutions | 13,664 | 6 | (15) | — | %
Other financial corporations | 11,239 | 17 | (31) | 0.2 | %
Non-financial corporations | 173,254 | 8,467 | (6,465) | 4.9 | %
Agriculture, forestry and fishing | 3,758 | 154 | (124) | 4.1 | %
Mining and quarrying | 4,669 | 100 | (86) | 2.1 | %
Manufacturing | 39,517 | 1,711 | (1,242) | 4.3 | %
Electricity, gas, steam and air conditioning supply | 12,305 | 684 | (575) | 5.6 | %
Water supply | 900 | 14 | (16) | 1.6 | %
Construction | 10,945 | 1,377 | (876) | 12.6 | %
Wholesale and retail trade | 27,467 | 1,799 | (1,448) | 6.6 | %
Transport and storage | 9,638 | 507 | (392) | 5.3 | %
Accommodation and food service activities | 8,703 | 279 | (203) | 3.2 | %
Information and communications | 6,316 | 95 | (65) | 1.5 | %
Financial and insurance activities | 6,864 | 191 | (140) | 2.8 | %
Real estate activities | 19,435 | 782 | (527) | 4.0 | %
Professional, scientific and technical activities | 4,375 | 167 | (140) | 3.8 | %
Administrative and support service activities | 3,415 | 118 | (134) | 3.4 | %
Public administration and defense, compulsory social security | 282 | 5 | (6) | 1.7 | %
Education | 903 | 41 | (38) | 4.5 | %
Human health services and social work activities | 4,696 | 66 | (55) | 1.4 | %
Arts, entertainment and recreation | 1,396 | 47 | (39) | 3.4 | %
Other services | 7,671 | 331 | (360) | 4.3 | %
Households | 181,989 | 7,381 | (5,847) | 4.1 | %
LOANS AND ADVANCES | 412,711 | 15,959 | (12,427) | 3.9 | %
The changes during the years 2021, 2020 and 2019 of impaired financial assets and contingent risks are as follows:
Changes in impaired financial assets and guarantees given (Millions of Euros) |  |  |  |  |
|  | 2021 | 2020 | 2019 |  |  |  |  |
Balance at the beginning |  | 15,478 | 16,770 | 17,134 |  |  |  |  |
Additions |  | 8,556 | 9,533 | 9,857 |  |  |  |  |
Decreases (*) |  | (4,555) | (5,024) | (5,874) |  |  |  |  |
Net additions |  | 4,001 | 4,509 | 3,983 |  |  |  |  |
Amounts written-off |  | (3,613) | (3,603) | (3,803) |  |  |  |  |
Exchange differences and other |  | (399) | (968) | (544) |  |  |  |  |
Discontinued operations |  | — | (1,230) | — |  |  |  |  |
Balance at the end |  | 15,467 | 15,478 | 16,770 |  |  |  |  |
(*) Reflects the total amount of impaired loans derecognized from the consolidated balance sheet throughout the year as a result of mortgage foreclosures and real estate assets received in lieu of payment as well as monetary recoveries. The Group estimates that the update in the definition of credit impairment (default) (see Note 2.2.1) led to an increase of €1,262 million in impaired financial assets. Regarding expected credit losses, the impact of this change is not considered to be significant, since most of the affected operations were previously classified within stage 2 and, consequently, their credit risk coverage already corresponded to the expected credit losses throughout the expected lifetime of the operation. For the year ended December 31, 2021, the impairment charges recognized under the heading “Impairment or reversal of impairment on financial assets not measured at fair value through profit or loss or net gains by modification" amounted to €3,034 million (€5,179 million for the year ended December 31, 2020) (see Note 47). During 2021, three factors have contributed to lower impairment charges compared to the previous year: –a favorable demand recovery based on stimuli measures put in place by governments, savings during the pandemic and vaccination, as well as an upward revision in the forecasted GDP growth, which, although positive, has lost momentum by the end of the year due to short-term pressures. Such pressures are likely to be temporary and related to the supply chain and the rise in inflation rates, –improved performance of the underlying business. In particular, limited additions to stage 3 along with recoveries throughout the year, –and, to a lower extent, lower management adjustments, aligned with the improvement of the macroeconomic scenario. The changes during the years 2021, 2020 and 2019 in financial assets derecognized from the accompanying consolidated balance sheet as their recovery is considered unlikely ("write-offs"), is shown below:
Changes in impaired financial assets written-off from the balance sheet (Millions of Euros)
| Notes | 2021 | 2020 | 2019
Balance at the beginning |  | 22,001 | 26,245 | 32,343
Companies held for sale (*) |  | — | (4,646) | —
Increase |  | 3,709 | 3,440 | 4,712
Decrease: |  | (3,605) | (2,715) | (11,039)
Re-financing or restructuring |  | (1) | (7) | (2)
Cash recovery | 47 | (423) | (339) | (919)
Foreclosed assets |  | (17) | (479) | (617)
Sales (**) |  | (2,437) | (1,223) | (8,325)
Debt forgiveness |  | (599) | (607) | (493)
Time-barred debt and other causes |  | (129) | (60) | (682)
Net exchange differences |  | (116) | (323) | 230
Balance at the end |  | 21,990 | 22,001 | 26,245
(*) The amount in 2020 includes the balance of the companies in the United States included in the USA Sale (see Notes 1.3, 3 and 21). (**) Includes principal and interest. As indicated in Note 2.2.1, although they have been derecognized from the consolidated balance sheet, the BBVA Group continues to attempt to collect on these written-off financial assets, until the rights to receive them are fully extinguished, either because it is a time-barred financial asset, the financial asset is forgiven, or other reason. Loss allowances Movements, measured over a 12-month period, in gross accounting balances and accumulated allowances for loan losses during 2021, 2020 and 2019 are recorded on the accompanying consolidated balance sheet as of December 31, 2021, 2020 and 2019, in order to cover the estimated loss allowances in loans and advances and debt securities measured at amortized cost.
Changes in gross accounting balances of loans and advances at amortized cost. Year 2021 (Millions of Euros)
| Stage 1 | Stage 2 | Stage 3 | Total
Balance at the beginning | 298,793 | 30,601 | 14,678 | 344,072
Transfers of financial assets: | (10,785) | 8,640 | 2,145 | —
Transfers from stage 1 to Stage 2 | (14,482) | 14,482 | — | —
Transfers from stage 2 to Stage 1 | 4,905 | (4,905) | — | —
Transfers to Stage 3 | (1,772) | (1,945) | 3,717 | —
Transfers from Stage 3 | 564 | 1,009 | (1,573) | —
Net annual origination of financial assets | 17,876 | (4,729) | 1,217 | 14,364
Becoming write-offs | (74) | (68) | (3,095) | (3,237)
Changes in model / methodology | — | — | — | —
Foreign exchange | (6,054) | (1,902) | (216) | (8,172)
Modifications that do not result in derecognition | 187 | 1,642 | 189 | 2,018
Other | 224 | 29 | (261) | (8)
Balance at the end | 300,167 | 34,213 | 14,657 | 349,037
Changes in allowances of loans and advances at amortized cost. Year 2021 (Millions of Euros)
| Stage 1 | Stage 2 | Stage 3 | Total
Balance at the beginning | (2,037) | (2,289) | (7,815) | (12,141)
Transfers of financial assets: | 187 | 441 | (2,521) | (1,893)
Transfers from stage 1 to Stage 2 | 139 | (602) | — | (463)
Transfers from stage 2 to Stage 1 | (60) | 307 | — | 247
Transfers to Stage 3 | 111 | 802 | (2,775) | (1,862)
Transfers from Stage 3 | (3) | (66) | 254 | 185
Net annual origination of allowances | (563) | (57) | (314) | (933)
Becoming write-offs | 45 | 56 | 2,694 | 2,795
Changes in model / methodology | — | — | — | —
Foreign exchange | 70 | (270) | 719 | 519
Modifications that do not result in derecognition | 12 | (79) | (122) | (189)
Other | 297 | 106 | 298 | 701
Balance at the end | (1,990) | (2,091) | (7,061) | (11,142)
Changes in gross accounting balances of loans and advances at amortized cost. Year 2020 (Millions of Euros)
| Stage 1 | Stage 2 | Stage 3 | Total
Balance at the beginning | 363,234 | 33,518 | 15,959 | 412,711
Transfers of financial assets: | (11,935) | 8,807 | 3,128 | —
Transfers from stage 1 to Stage 2 | (15,843) | 15,843 | — | —
Transfers from stage 2 to Stage 1 | 5,107 | (5,107) | — | —
Transfers to Stage 3 | (1,701) | (2,659) | 4,359 | —
Transfers from Stage 3 | 502 | 729 | (1,231) | —
Net annual origination of financial assets | 16,119 | (827) | 102 | 15,395
Becoming write-offs | (3) | (2) | (2,944) | (2,949)
Changes in model / methodology | — | — | — | —
Foreign exchange | (21,472) | (2,342) | (1,157) | (24,970)
Modifications that do not result in derecognition | (204) | 827 | 511 | 1,134
Other | (283) | (190) | 270 | (204)
Discontinued operations | (46,664) | (9,190) | (1,192) | (57,045)
Balance at the end | 298,793 | 30,601 | 14,678 | 344,072
Changes in allowances of loans and advances at amortized cost. Year 2020 (Millions of Euros)
| Stage 1 | Stage 2 | Stage 3 | Total
Balance at the beginning | (2,149) | (2,183) | (8,094) | (12,427)
Transfers of financial assets: | 184 | (511) | (1,806) | (2,133)
Transfers from stage 1 to stage 2 | 156 | (923) | — | (766)
Transfers from stage 2 to stage 1 | (50) | 253 | — | 202
Transfers to stage 3 | 81 | 218 | (1,950) | (1,652)
Transfers from stage 3 | (3) | (59) | 144 | 83
Net annual origination of allowances | (872) | (795) | (1,329) | (2,996)
Becoming write-offs | — | — | 2,567 | 2,568
Changes in model / methodology | — | — | — | —
Foreign exchange | 227 | 256 | 721 | 1,204
Modifications that do not result in derecognition | 12 | (118) | (177) | (283)
Other | 160 | 618 | 25 | 803
Discontinued operations | 401 | 444 | 278 | 1,123
Balance at the end | (2,037) | (2,289) | (7,815) | (12,141)
Changes in gross accounting balances of loans and advances at amortized cost. Year 2019 (Millions of Euros)
| Stage 1 | Stage 2 | Stage 3 | Total
Balance at the beginning | 352,282 | 30,707 | 16,359 | 399,347
Transfers of financial assets: | (9,021) | 6,279 | 2,741 | —
Transfers from stage 1 to stage 2 | (13,546) | 13,546 | — | —
Transfers from stage 2 to stage 1 | 5,656 | (5,656) | — | —
Transfers to stage 3 | (1,571) | (2,698) | 4,269 | —
Transfers from stage 3 | 440 | 1,087 | (1,527) | —
Net annual origination of financial assets | 20,296 | (2,739) | 246 | 17,804
Becoming write-offs | (152) | (349) | (3,407) | (3,908)
Changes in model / methodology | — | — | — | —
Foreign exchange | 1,611 | 35 | 16 | 1,662
Modifications that do not result in derecognition | (1) | (27) | 15 | (13)
Other | (1,782) | (388) | (11) | (2,180)
Balance at the end | 363,234 | 33,518 | 15,959 | 412,711
Changes in allowances of loans and advances at amortized cost. Year 2019 (Millions of Euros)
| Stage 1 | Stage 2 | Stage 3 | Total
Balance at the beginning | (2,082) | (2,375) | (7,761) | (12,217)
Transfers of financial assets: | 176 | (227) | (1,574) | (1,626)
Transfers from stage 1 to stage 2 | 126 | (649) | — | (523)
Transfers from stage 2 to stage 1 | (38) | 273 | — | 235
Transfers to stage 3 | 89 | 234 | (1,810) | (1,487)
Transfers from stage 3 | (1) | (86) | 236 | 149
Net annual origination of allowances | (542) | (116) | (1,711) | (2,370)
Becoming write-offs | 130 | 337 | 2,789 | 3,256
Changes in model / methodology | — | — | — | —
Foreign exchange | (30) | (18) | 69 | 20
Modifications that do not result in derecognition | (15) | (149) | (89) | (254)
Other | 215 | 366 | 183 | 764
Balance at the end | (2,149) | (2,183) | (8,094) | (12,427)
7.2.7 Refinancing and restructuring transactions Group policies and principles with respect to refinancing and restructuring transactions Refinancing and restructuring transactions (see definition in the Glossary) are carried out with customers who have requested such a transaction in order to meet their current loan payments if they are expected, or may be expected, to experience financial difficulty in making the payments in the future. The basic aim of a refinancing and restructuring transaction is to provide the customer with a situation of financial viability over time by adapting repayment of the loan incurred with the Group to the customer’s new situation of fund generation. The use of refinancing and restructuring for other purposes, such as to delay loss recognition, is contrary to BBVA Group policies. The BBVA Group’s refinancing and restructuring policies are based on the following general principles: –Refinancing and restructuring is authorized according to the capacity of customers to pay the new installments. This is done by first identifying the origin of the payment difficulties and then carrying out an analysis of the customers’ viability, including an updated analysis of their economic and financial situation and capacity to pay and generate funds. If the customer is a company, the analysis also covers the situation of the industry in which it operates. –With the aim of increasing the solvency of the transaction, new guarantees and/or guarantors of demonstrable solvency are obtained where possible. An essential part of this process is an analysis of the effectiveness of both the new and original guarantees. –This analysis is carried out from the overall customer or group perspective. –Refinancing and restructuring transactions do not in general increase the amount of the customer’s loan, except for the expense inherent to the transaction itself. –The capacity to refinance and restructure a loan is not delegated to the branches, but decided on by the risk units. –The decisions made are reviewed from time to time with the aim of evaluating full compliance with refinancing and restructuring policies. These general principles are adapted in each case according to the conditions and circumstances of each geographical area in which the Group operates, and to the different types of customers involved. In the case of retail customers (private individuals), the main aim of the BBVA Group’s policy on refinancing and restructuring a loan is to avoid default arising from a customer’s temporary liquidity problems by implementing structural solutions that do not increase the balance of the customer’s loan. The solution required is adapted to each case and the loan repayment is made easier, in accordance with the following principles: –Analysis of the viability of transactions based on the customer’s willingness and ability to pay, which may be reduced, but should nevertheless be present. The customer must therefore repay at least the interest on the transaction in all cases. No arrangements may be concluded that involve a grace period for both principal and interest. –Refinancing and restructuring of transactions is only allowed on those loans in which the BBVA Group originally entered into. –Customers subject to refinancing and restructuring transactions are excluded from marketing campaigns of any kind. In the case of non-retail customers (mainly companies, enterprises and corporates), refinancing/restructuring is authorized according to an economic and financial viability plan based on: –Forecasted future income, margins and cash flows to allow entities to implement cost adjustment measures (industrial restructuring) and a business development plan that can help reduce the level of leverage to sustainable levels (capacity to access the financial markets). –Where appropriate, the existence of a divestment plan for assets and/or operating segments that can generate cash to assist the deleveraging process. –The capacity of shareholders to contribute capital and/or guarantees that can support the viability of the plan. In accordance with the Group’s policy, the conclusion of a loan refinancing and restructuring transaction does not mean the loan is reclassified from "impaired" or "significant increase in credit risk" to normal risk. The reclassification to "significant increase in credit risk" or normal risk categories must be based on the analysis mentioned earlier of the viability, upon completion of the probationary periods described below. The Group maintains the policy of including risks related to refinanced and restructured loans as either: –"Impaired assets", as although the customer is up to date with payments, they are classified as unlikely to pay when there are significant doubts that the terms of their refinancing may not be met; or –"Significant increase in credit risk" until the conditions established for their consideration as normal risk are met. The assets classified as "Impaired assets" should comply with the following conditions in order to be reclassified to "Significant increase in credit risk": –The customer has to have paid a significant part of the pending exposure. –At least one year must have elapsed since its classification as "Impaired asset". –The customer does not have past due payments and objective criteria, demonstrating the borrower´s ability to pay, have been verified. The conditions established for assets classified as “Significant increase in credit risk” to be reclassified out of this category are as follows: –The customer must have paid past-due amounts (principal and interest) since the date of the renegotiation or restructuring of the loan or other objective criteria, demonstrating the borrower´s ability to pay, have been verified; none of its exposures is more than 30 days past-due. –At least two years must have elapsed since completion of the renegotiation or restructuring of the loan and regular payments must have been made during at least half of this probation period; and –It is unlikely that the customer will have financial difficulties and, therefore, it is expected that the customer will be able to meet its loan payment obligations (principal and interest) in a timely manner. The economic impact caused by the COVID-19 pandemic has required the adaptation of the repayment schedule of a large volume of loans in all geographies and portfolios. In general, this support has been conducted through the granting of deferrals that comply with the principles established by the EBA, which has allowed for the application of a differential accounting and prudential treatment. Renewals and renegotiations will be classified as normal risk, provided that there is no significant increase in risk. This classification is applicable at the initial moment, and in the event of any deterioration, the criteria established in the existing governance are followed. In this sense, the aforementioned conditions are considered, including, among others, no facility with more than 30 days delinquency and not being identified as 'unlikely to pay'. The BBVA Group’s refinancing and restructuring policy provides for the possibility of two modifications in a 24 month period for loans that are not in compliance with the payment schedule. The internal models used to determine allowances for loan losses consider the restructuring and renegotiation of a loan, as well as re-defaults on such a loan, by assigning a lower internal rating to restructured and renegotiated loans than the average internal rating assigned to non-restructured/renegotiated loans. This downgrade results in an increase in the probability of default (PD) assigned to restructured/renegotiated loans (with the resulting PD being higher than the average PD of the non- renegotiated loans in the same portfolios). In any case, a restructuring will be considered impaired when the reduction in the present net value of the financial obligation is greater than 1% in line with the new management criteria introduced during 2021. For quantitative information on refinancing and restructuring transactions see Appendix VIII. Risk concentration Policies for preventing excessive risk concentration In order to prevent the build-up of excessive risk concentrations at the individual, sector, portfolio and geography levels, BBVA Group maintains updated maximum permitted risk concentration indices which are tied to the various observable variables related to concentration risk. Together with the limits for individual concentration, the Group uses the Herfindahl index to measure the concentration of the Group's portfolio and the banking group's subsidiaries. At the BBVA Group level, the index reached implies a "very low" degree of concentration. The limit on the Group’s exposure or financial commitment to a specific customer therefore depends on the customer’s credit rating, the nature of the risks involved, and the Group’s presence in a given market, based on the following guidelines: –The aim is, as much as possible, to reconcile the customer's credit needs (commercial/financial, short-term/long-term, etc.) with the interests of the Group. –Any legal limits that may exist concerning risk concentration are taken into account (relationship between risks with a customer and the capital of the shareholder´s entity that assumes them), the markets, the macroeconomic situation, etc. –The aim is to seek inter and intra-sector diversification in coherence with the metrics defined in the RAF for the Group and for the banking group's subsidiaries. Risk concentrations by geography The breakdown of the main figures in the most significant foreign currencies in the accompanying consolidated balance sheets is set forth in Appendix IX. Sovereign risk concentration Sovereign risk management The identification, measurement, control and monitoring of risk associated with sovereign risk transactions is carried out by a centralized unit within the BBVA Group's Risk Area. Its basic functions are preparing reports (called financial programs) on the countries with which it maintains cross-border risks (i.e. risks taken in a foreign currency from outside the country with borrowers in the country, whether public or private) and sovereign risks (i.e. risks with the local Sovereign of the country where the risk-taking unit is located), monitoring those risks, establishing risk limits, assigning ratings to the countries analyzed and, in general, supporting the Group in any information request regarding this type of transaction. The risk policies established in the financial programs are approved by the relevant risk committees. The country risk unit tracks the evolution of the risks associated with the various countries to which the Group are exposed (including sovereign risk) on an ongoing basis in order to adapt its risk and mitigation policies to any macroeconomic and political changes that may occur. Moreover, it regularly updates its internal ratings and forecasts for these countries. The methodology is based on the assessment of quantitative and qualitative parameters which are in line with those used by certain multilateral organizations (the International Monetary Fund (IMF), the World Bank, etc.) rating agencies and export credit organizations. For additional information on sovereign risk in Europe see Appendix IX. Risk related to the developer and Real-Estate sector in Spain The sale of impaired assets concluded in 2018. Currently, there is no risk concentration in the developer and real estate sector, taking into account that its weight in total wholesale risks in Spain is approxi mately 10%, while compared with the total risks in the portfolio (wholesale and retail), the Real Estate risk assumed would be around 3%. Policies and strategies established by the Group to deal with risks related to the developer and real-estate sector BBVA Group has teams specializing in the management of the Real Estate Sector risk, given its economic importance and specific technical component. This specialization is not only in risk teams, but throughout the handling, commercial, problem risks and legal, etc. It also includes the research department of the BBVA Group (BBVA Research), which helps determine the medium/long-term vision needed to manage this portfolio. The policies established to address the risks related to the developer and real-estate sector, aim to accomplish, among others, the following objectives: to avoid concentration in terms of customers, products and regions; to estimate the risk profile for the portfolio; and to anticipate possible worsening of the portfolio within a sector is highly cyclical. Specific policies for analysis and granting of new developer risk transactions In the analysis of new transactions, the assessment of the commercial operation in terms of the economic and financial viability of the project has been one of the constant. The monitoring of the work, sales prospects and the legal situation of the project are essential aspects for the admission and follow-up of new real estate transactions. With regard the participation of the Risk Acceptance teams, they have a direct link and participate in the committees of areas such as Valuation, Legal, Research and Recoveries. This guarantees coordination and exchange of information in all the processes. In this context, and within the current Real Estate cycle, the strategy with clients is subject to an Asset Allocation limit and to an action framework that allows defining a target portfolio, both in volume and in credit quality. Risk monitoring policies The base information for analyzing the real estate portfolios is updated monthly. There is a systematic monitoring of developments under close monitoring with the evolution of works and sales. Policies applied in the management of real estate assets in Spain The internal Rules on Real Estate Financing, which establish recommendations for financing a new housing development business, are reviewed and updated annually. The recommendations represent guidelines about how to manage the credit admission activity of BBVA Group entities based on best practices of markets in which this activity is performed. It is expected that a high percentage of the current transactions will be in compliance with the latter. For quantitative information about the risk related to the developer and Real-Estate sector in Spain see Appendix IX. Structural risk The structural risks are defined, in general terms, as the possibility of suffering losses due to adverse movements in market risk factors as a result of mismatches in the financial structure of an entity´s balance sheet. In the Group, the following types of structural risks are defined, according to the nature and the following market factors: interest rate risk, credit spread risk, exchange rate risk and equity risk. The scope of structural risks in the Group is limited to the banking book, excluding market risks in the trading book that are clearly delimited and separated and make up the Market Risks. The Assets and Liabilities Committee (ALCO) is the main responsible body for the management of structural risks regarding liquidity/ funding, interest rate, credit spread, currency, equity and solvency. Every month, with the participation of the CEO and representatives from the areas of Finance, Risks and Business Areas; this committee monitors the structural risks and is presented with proposals with regard to action plans related with its management for its approval. These management proposals are made by the Finance area with a forward-looking focus, maintaining the alignment with the risk appetite framework, trying to guarantee the recurrence of results and financial stability, as well as to preserve the solvency of the entity. All balance sheet management units have a local ALCO, which is permanently attended by members of the corporate center, and there is a corporate ALCO where management strategies are monitored and presented in the Group's subsidiaries. The GRM area acts as an independent unit, ensuring adequate separation between the management and risk control functions, and is responsible for ensuring that the structural risks in the Group are managed according to the strategy approved by the Board of Directors. Consequently, GRM deals with the identification, measurement, monitoring and control of those risks and their reporting to the corresponding corporate bodies. Through the Global Risk Management Committee (GRMC), it performs the function of control and risk assessment and is responsible for developing the strategies, policies, procedures and infrastructure necessary to identify, evaluate, measure and manage the significant risks that the BBVA Group faces. To this end, GRM, through the corporate unit of Structural Risks, proposes a scheme of limits that defines the risk appetite set for each of the relevant structural risk types, both at Group level and by management units, which will be reviewed annually, reporting the situation periodically to the Group's corporate bodies as well as to the GRMC. Additionally, both the management system and the control and measurement system for structural risks are necessarily adjusted to the Group's internal control model, complying with the evaluation and certification processes that comprise it. In this sense, the tasks and controls necessary for its scope of action have been identified and documented, supporting a regulatory framework which includes specific processes and measures for structural risks, from a broad geographical perspective. Within the three lines of defense scheme in which BBVA's internal control model is based according to the most advanced standards in terms of internal control, the first line of defense is maintained by the Finance area, which is responsible for managing the structural risk. As a second line of defense, GRM is in charge of identifying risks, and establishing policies and control models, periodically evaluating their effectiveness. In the second line of defense, there are also the Internal Risk Control units, which independently review the Structural Risk control, and Internal Financial Control, which carries out a review of the design and effectiveness of the operational controls over structural risk management. The third line of defense is represented by the Internal Audit area, an independent unit within BBVA Group, which is responsible for reviewing specific controls and processes. Structural interest rate risk and credit spread The structural interest-rate risk (IRRBB) is related to the potential impact that variations in market interest rates have on an entity's net interest income and equity. In order to properly measure IRRBB, BBVA Group takes into account all the main sources of this risk: repricing risk, yield curve risk, option risk and basis risk. The assessment of structural interest rate risk is carried out with an integral vision, combining two complementary points of view: the effects of interest rate shifts in net interest income (short term) and their impact on the economic value of equity (long term). In addition, the impact on the market value of the financial instruments of the banking book, as a result of changes in the market interest rates (IRRBB) or the credit spreads (CSRBB), will be assessed as it may have an impact on the income statement and/or equity due to their accounting treatment. The exposure of a financial entity to adverse interest rates movements is a risk inherent to the development of the banking business, which is also, in turn, an opportunity to create economic value. Therefore, interest rate risk must be effectively managed so that it is limited in accordance with the entity’s equity and in line with the expected economic result. In BBVA, the purpose of structural interest rate risk management is to maintain the stability of the net interest income in the event of interest rate fluctuations. It contributes to a recurrent generation of earnings, limit the capital consumption due to structural interest rate risk and monitor potential mark-to-market impacts on “held to collect and sell” (HtC&S) portfolios. Likewise, the spread risk management in banking book portfolios is aimed at limiting the impact on the valuation of fixed income instruments, which are used for balance sheet liquidity and interest rate risk management purposes in order to increase diversification, and at reducing the concentration of each issuer, maintaining the spread risk at levels aligned with the total volume of the investment portfolio and the equity of the Group. These functions falls to the Global ALM (Asset & Liability Management) unit, within the Finance area, who, through ALCO, aims to enable the recurrence of results and preserve the solvency of the entity, always adhering to the risk profile defined by the management bodies of the BBVA Group. Structural interest rate risk management is decentralized, and is carried out independently in each entity included in the structural balance sheet (banking book) of the BBVA Group, keeping the exposure to interest rates and credit spreads movements aligned with the strategy and the target risk profile of the Group, and in compliance with the regulatory requirements according to the EBA guidelines. Nature of interest rate risk and credit spread risk Repricing risk arises due to the difference between the repricing or maturity terms of the assets and liabilities, and represents the most frequent interest rate risk faced by financial entities. However, other sources of risk such as changes in the slope and shape of the yield curve, the reference to different indexes and the optionality risk embedded in certain banking transactions, are also taken into account by the risk control system. Furthermore, the credit spread risk (CSRBB) of fixed-income portfolios in the banking book arises from the potential impact on the value of fixed-income portfolios and credit derivatives classified as HtC&S produced by a variation in the level of credit spreads associated with those instruments/issuers and that are not explained by default risk or by movements in market interest rates. BBVA's structural interest-rate risk management and control process includes a set of metrics and tools that enable the capture of additional sources to properly monitor the risk profile of the Group, backed-up by assumptions that aim to characterize the behavior of the balance sheet items with the maximum accuracy. The IRRBB and CSRBB measurement is carried out on a monthly basis, and includes probabilistic measures based on simulation methods of interest rate curves and credit spread shocks. The corporate methodology enables to capture additional sources of risk to the interest rate parallel shifts, such as the changes in slope shape and the basis of yield curves. Additionally, sensitivity analysis to multiple parallel shocks of different magnitude are also assessed on a regular basis. The process is run separately for each currency to which the Group is exposed, considering, at a later stage, the diversification effect among currencies and business units. The risk measurement model is complemented by the assessment of ad-hoc scenarios, stress tests and reverse stress. As stress testing has become more relevant during the recent years, the evaluation of market rates and behavioral assumptions extreme scenarios has continued to be enhanced, while assessing, also, BBVA Research market scenarios, and the set of scenarios defined according to EBA guidelines. During 2021, the continuous improvement of internal systems and IRRBB management and control models has continued according to the EBA guidelines. Among others, the developments to improve the data provisioning and the risk management tools are highlighted, as well as the enhancement of the stress testing and models backtesting procedures. Key assumptions of the model In order to measure structural interest rate risk, the setting of assumptions on the evolution and behavior of certain balance sheet items is particularly relevant, especially those related to products without an explicit or contractual maturity which characteristics are not established in their contractual terms and must be therefore estimated. The assumptions that characterize these balance sheet items must be understandable for the areas and bodies involved in risk management and control and remain duly updated, justified and documented. The modeling of these assumptions must be conceptually reasonable and consistent with the evidence based on historical experience, reviewed at least once a year and, if any, the behavior of the customers induced by the business areas. These assumptions are regularly subject to a sensitivity analysis to assess and understand the impact of the modelling on the risk metrics. The approval and update of the IRRBB behavioral models is subject to the corporate governance under the scope of GRM analytics. Thus, all the models must be duly inventoried and catalogued and comply with the requirements for their development, updating and changes management set out in the internal procedures. They are also subject to the corresponding internal validations and follow-up requirements established based on their relevance, as well as to backtesting procedures against experience to ratify the validity of the assumptions applied. In view of the heterogeneity of the financial markets, customers and products in the multiple jurisdictions, each one of the entities of the Group is responsible for determining the behavior assumptions to be applied to the balance sheet items, always under the guidelines and the applicability of the corporate models existing in the Group. The balance sheet behavioral assumptions stand out those established for the treatment of items without contractual maturity, mainly for demand customer deposits, and those related to the expectations on the exercise of interest rate options, especially relating to loans and deposits subject to prepayment risk. For the modelling of demand deposits, a segmentation of the accounts in several categories is previously carried out depending on the characteristics of the customer (retail / wholesale) and the product (type of account / transactionality / remuneration), in order to outline the specific behavior of each segment. In order to establish the remuneration of each segment, the relationship between the evolution of market interest rates and the interest rates of managed accounts is analyzed, with the aim of determining the translation dynamic (percentages and lags) of interest rates variations to the remuneration of the accounts. In this regard, consideration is given to the potential limitations in the repricing of these accounts in scenarios of low or negative rates, with special attention to retail customers, through the establishment of floors in the remuneration. The behavior assigned to each category of accounts is determined by an analysis of the historical evolution of the balances and the probability of cancellation of the accounts. For this, the volatile part of the balance assigned to a short-term maturity is isolated, thus avoiding fluctuations in the level of risk caused by specific variations in the balances and promoting stability in the management of the balance. Once the stable part is identified, a medium / long term maturity model is applied through a decay distribution based on the average term of the accounts and the conditional cancellation probabilities throughout the life of the product. The relationship of the evolution of the balance of deposits with the levels of market interest rates is incorporated, where appropriate, in the behavioral modelling, especially in low interest rates environments, including its effect on the stability of the deposits as well as the potential migration between the different types of deposits (on demand / time deposits) in the different interest rate scenarios. Equally relevant is the treatment of early cancellation options embedded in credit loans, mortgage portfolios and customer deposits. The evolution of market interest rates may condition, along with other variables, the incentive that customers have to prepay loans or deposits, modifying the future behavior of the balance amounts with respect to the forecasted contractual maturity schedule. The detailed analysis of the historical information related to prepayment data, both partial and total prepayment, combined with other variables such as interest rates, allows estimating future amortizations and, where appropriate, their behavior linked to the evolution of such variables through the relationship between the incentive of the customer to prepay and the early cancellation speed. The table below shows the profile of average structural interest rate risk and credit spread risk of fixed income portfolio in the banking book classified as HtC&S in terms of sensitivities of the main currencies for the BBVA Group in 2021:
Sensitivity to interest-rate and credit spread analysis. Year 2021 |
| interest rate risk and | credit spread
| Impact on net interest income (*) | Impact on economic value (**) | Impact on economic value (**)
| 100 basis-point increase | 100 basis-point decrease (***) | 100 basis-point increase | 100 basis-point decrease (***) | 100 basis-point increase
EUR | [3.5% , 5.5%] | [-3.5% , -1.5%] | [3.5% , 5.5%] | [-3.5% , -1.5%] | [-3.5% , -1.5%]
MXN | [0.5% , 1.5%] | [-1.5% , -0.5%] | [-1.5% , -0.5%] | [0.5% , 1.5%] | [-0.5% , 0.5%]
USD | [0.5% , 1.5%] | [-1.5% , -0.5%] | [0.5% , 1.5%] | [-1.5% , -0.5%] | [-0.5% , 0.5%]
TRY | [-0.5% , 0.5%] | [-0.5% , 0.5%] | [-0.5% , 0.5%] | [-0.5% , 0.5%] | [-0.5% , 0.5%]
Other | [-0.5% , 0.5%] | [-0.5% , 0.5%] | [-0.5% , 0.5%] | [-0.5% , 0.5%] | [-0.5% , 0.5%]
BBVA Group | [7.5% , 10.0%] | [-5.5% , -3.5%] | [3.5% , 5.5%] | [-3.5% , -1.5%] | [-3.5% , -1.5%]
(*) Percentage of "12 months" net interest income for the BBVA Group. (**) Percentage of CET1 (Fully Loaded) for BBVA Group (***) In EUR and USD (and GBP included in "Other"), negative interest rates scenarios are allowed up to plausible levels lower than current rates. During 2021, central banks began withdrawing the expansionary policies implemented during the year 2020, to mitigate the economic impact caused by the COVID-19 pandemic, with the aim of reducing the inflationary pressures that are occurring in most countries of the world. In Europe, the end of the PEPP (Pandemic Emergency Purchase Programme) was announced for the month of March 2022. In Turkey, although it initially showed an upward trend in interest rates, there have been significant drops since September, ending the year 300 basis points below the level of December 2020. Regarding Mexico, the Central Bank implemented the last rate cut in February, placing it at a level of 4%. Starting in June, there was a change in trend, initiating an upward cycle in rates, reaching a level of 5.50% in December. The objective of the Central Bank is to moderate the rise in inflation and bring it back within its target range. In South America, the monetary policy was restrictive, with increases in the policy rates in Colombia and Peru, affected by higher levels of inflation, reaching above the central banks targets. Regarding Argentina it has had a stable monetary policy without changes during the year. The BBVA Group, at an aggregate level, continues to maintain a moderate risk profile, in accordance with the established objective, showing a favorable position to a rise in interest rates on net interest income. Effective management of the balance sheet structural risk has mitigated the negative impact of the low interest rates derived from the expansive monetary policies implemented by the different central banks to offset the negative economic effects derived from the COVID-19 pandemic, and is reflected in the strength and recurrence of the net interest income: –In Europe, the downward trend in interest rates remains limited by current levels, preventing extremely adverse scenarios from occurring. The balance sheet is characterized by a high proportion of variable-rate loans (basically mortgages and corporate lending) and liabilities are composed mainly of customer on demand deposits. The ALCO portfolio acts as a management lever and hedging for the balance sheet, mitigating its sensitivity to interest rate fluctuations. The balance sheet´s interest rate profile has remained stable during the year, showing an interest net income sensitivity to 100 basis points increases by the interest rates slightly above 20%. On the other hand, the ECB held the marginal deposit facility rate unchanged at -0.50% in 2021 and maintained the extraordinary support programs created after the outbreak of the COVID-19 crisis. This has created stability in European benchmark interest rates (EURIBOR). –In Mexico, a balance has been maintained between balances referenced to fixed and variable interest rates. Among the assets most sensitive to interest rate movements, the wholesale portfolio stands out, while consumer and mortgages are mostly at a fixed rate. The ALCO portfolio is mainly invested in fixed-rate sovereign bonds with limited durations. The sensitivity of the net interest income continues to be limited, stable, and slightly biased towards higher interest rates, which have increased during 2021 by 125 basis points. –In Turkey, the sensitivity of loans, mostly fixed-rate but with relatively short maturities, and the ALCO portfolio balance the sensitivity of deposits on the liability side. In this way, the interest rate risk is limited, both in Turkish lira and in foreign currency. –In South America, the risk profile on interest rates continues to be low, as most of the countries in the area have a composition of fixed / variable and very similar maturities between assets and liabilities, showing a sensitivity of the margin interest rate limited and with slight variations throughout 2021. Likewise, in countries with balances in several currencies, interest rate risk is also managed for each of the currencies, showing a very low level of risk. The more restrictive measures promoted by the central banks during 2021 are expected to have a slightly positive impact, given the sensitivity maintained by the different banks in the region. Structural exchange-rate risk Structural exchange rate risk, is defined as the possibility of impacts on solvency, equity value and results driven by fluctuations in the exchange rates due to exposures in foreign currencies. Structural exchange rate risk is inherent to the business of international banking groups, such as BBVA, that develop their activities in different geographies and currencies. At a consolidated level, structural exchange-rate risk arises from the consolidation of holdings in subsidiaries with functional currencies other than the euro. Its management is centralized in order to optimize the joint management of permanent foreign currency exposures, taking diversification into account. The purpose of structural exchange rate risk management is protecting solvency by limiting volatility of the consolidated CET1 ratio and income to consolidate denominated in a currency other the euro in the Group, as well as to limit the capital requirements under exchange rate fluctuations to which the Group is exposed due to its international diversification. The ALM Global corporate unit, through the ALCO, is responsible for the management of this risk all through an active hedging policy, deliberately taken for each objective, and fully aligned with the management strategy. At the corporate level, the risk monitoring metrics included in the limits framework are aligned with the Risk Appetite Framework, and are targeted to control the effects on the solvency through the economic capital metric and the fluctuations in the Common Equity Tier I fully loaded (CET1 fully loaded) consolidated ratio, as well as the maximum deviation in the Group's attributable profit. The probabilistic metrics make it possible to estimate the joint impact of exposure to different currencies taking into account the different variability in exchange rates and their correlations. These metrics are supplemented with additional assessment indicators. The suitability of these risk assessment metrics is reviewed on a regular basis through backtesting exercises. The final element of structural exchange-rate risk control is the stress and scenario analysis aimed to assess the vulnerabilities of foreign currency structural exposure not contemplated by the risk metrics and to serve as an additional tool when making management decisions. The scenarios are based both on historical situations simulated by the risk model and on the risk scenarios provided by BBVA Research. The purpose of the exchange rate risk management of BBVA's long term investments, which arises mainly from its foreign franchises, is to preserve the capital ratios of the Group and to maintain the stability of the profits. The U.S. dollar accumulated an appreciation of 8.3% against the euro in 2021, thus reversing much of the movement in favor of the euro in 2020 after the outbreak of the pandemic. Among the emerging currencies, the sharp depreciation of the Turkish lira in 2021 (-40.2%) stood out, severely penalized by rate cuts in the recent months. The positive side came from the good performance of the Mexican peso, which has appreciated by 5.5% against the euro since the end of 2020. With regard to the South American currencies, the Peruvian Sol finally closed the year with a slight depreciation against Euro (-1.3%) while the Chilean peso (-8.8%) and the Colombian peso (-6.6%) showed a greater depreciation. The Argentine peso depreciated (-11.3%) but in a more contained manner than in previous years. BBVA maintains its active management policies of the main investments in emerging countries, which are set, on average, between 30% and 50% of the annual profits and around 70% of the excess of the CET1 capital ratio. The sale of BBVA USA in June modified the sensitivity against movements in the exchange rates of the ratio CET1 fully-loaded of the Group. USD sensitivity has been the most affected by this change, reaching +18 basis points in case of a depreciation of -10% in the currency. At the end of December 2021, the sensitivity is estimated as -7 bps for the Mexican Peso and -1 bps for the Turkish lira, both against a depreciation of -10%. Regarding the hedging of the expected profits for 2022, it stands at around 65% in the case of Mexico, 20% for Turkey and 100% for Peru and Colombia. For the years 2021, 2020 and 2019, the estimated sensitivities of the result attributable to the parent company are shown below, taking into account the coverage, against depreciations and appreciations of 1% of the average rate in the main currencies. To the extent that hedging positions are periodically modulated, the sensitivity estimate attempts to reflect an average (or effective) sensitivity in the year:
Sensitivity to 1% change (Millions of Euros)
Currency | 2021 | 2020 | 2019
Mexican peso | 14.0 | 4.9 | 12.7
Turkish lira | 4.7 | 4.5 | 3.1
Peruvian sol | 0.3 | 0.4 | 1.9
Chilean peso | 0.6 | 0.3 | 0.5
Colombian peso | 1.1 | 1.4 | 2.6
Argentine peso | 0.6 | 0.9 | 1.3
Structural equity risk Structural equity risk refers to the possibility of suffering losses in the value of positions in shares and other equity instruments held in the banking book with long or medium term investment horizons due to fluctuations in the value of equity indexes or shares. BBVA Group's exposure to structural equity risk arises largely from minority shareholdings held on industrial and financial companies, and in new business (innovation). This exposure is modulated in some portfolios with positions held on derivative instruments on the same underlying assets, in order to adjust the portfolio sensitivity to potential changes in equity prices. The structural equity risk management is aimed at increasing the income-generating capacity of those shares held by the Group, limiting the capital requirements for equity risk and narrowing the impact on the solvency level through a proactive management of the portfolio using hedges. The function of managing the structural equity portfolios is a responsibility of the corporate units of Global ALM and other Group's units specialized in this area. Their activity is subject to the risk management corporate policy on structural equity risk management, complying with the defined management principles and Risk Appetite Framework. The structural equity risk metrics, designed by GRM according to the corporate model, contribute to the effective monitoring of the risk by estimating the sensitivity and the capital necessary to cover the possible unexpected losses due to changes in the value of the shareholdings in the Group's investment portfolio, with a level of confidence that corresponds to the objective rating of the entity, taking into account the liquidity of the positions and the statistical behavior of the assets to be considered In order to analyze the risk profile in depth, stress tests and scenario analysis of sensitivity to different simulated scenarios are carried out. They are based on both past crisis situations and forecasts made by BBVA Research. These analyses are carried out regularly to assess the vulnerabilities of structural equity exposure not contemplated by the risk metrics and to serve as an additional tool when making management decisions. Backtesting is carried out on a regular basis on the risk measurement model used. Equity markets in Europe and the US have rallied significantly in 2021. The excellent performance of listed companies' corporate earnings and the continuity of central banks' accommodative policies have been behind these revaluations. However, the Spanish stock market has once again lagged behind the rest of the European stock markets. Structural equity risk, measured in terms of economic capital, has raised during the last year due to the higher exposure taken. The aggregate sensitivity of the BBVA Group’s consolidated equity to a 1% fall in the price of shares of the companies making up the equity portfolio increased to -€27 million as of December 31, 2021, compared to -€20 million as of December 31, 2020. This estimation takes into account the exposure in shares valued at market prices, or if not applicable, at fair value (excluding the positions in the Treasury Area portfolios) and the net delta-equivalent positions in derivatives on the same underlyings. Market riskMarket risk originates from the possibility of experiencing losses in the value of positions held as a result of movements in market variables that affect the valuation of financial assets and liabilities. Market risk in the Group's trading portfolios stems mainly from the portfolios originated by Global Markets valued at fair value and held for the purpose of trading and generating short-term results. Market risk in the field of banking book is clearly and distinctly addressed and can be broken down into structural risks relating to interest rate, exchange rate and equity (see Note 7.3).Market risk in trading portfolios The main risks in the trading portfolios can be classified as follows: –Interest-rate risk: This arises as a result of exposure to movements in the different interest-rate curves involved in trading. Although the typical products that generate sensitivity to the movements in interest rates are money-market products (deposits, interest-rate futures, call money swaps, etc.) and traditional interest-rate derivatives (swaps and interest-rate options such as caps, floors, swaptions, etc.), practically all the financial products are exposed to interest-rate movements due to the effect that such movements have on the valuation of the financial discount. –Equity risk: This arises as a result of movements in share prices. This risk is generated in spot positions in shares or any derivative products whose underlying asset is a share or an equity index. Dividend risk is a sub-risk of equity risk, arising as an input for any equity option. Its variation may affect the valuation of positions and it is therefore a factor that generates risk on the books. –Exchange-rate risk: This is caused by movements in the exchange rates of the different currencies in which a position is held. As in the case of equity risk, this risk is generated in spot currency positions, and in any derivative product whose underlying asset is an exchange rate. In addition, the quanto effect (operations where the underlying asset and the instrument itself are denominated in different currencies) means that in certain transactions in which the underlying asset is not a currency, an exchange-rate risk is generated that has to be measured and monitored. –Credit-spread risk: Credit spread is an indicator of an issuer's credit quality. Spread risk occurs due to variations in the levels of spread of both corporate and government issues, and affects positions in bonds and credit derivatives. –Volatility risk: This occurs as a result of changes in the levels of implied price volatility of the different market instruments on which derivatives are traded. This risk, unlike the others, is exclusively a component of trading in derivatives and is defined as a first-order convexity risk that is generated in all possible underlying assets in which there are products with options that require a volatility input for their valuation. The metrics developed to assess market risk in the BBVA Group are aligned with market practices and are implemented consistently across all the local market risk units. Measurement procedures are established in terms of the possible impact of negative market conditions on the trading portfolio of the Group's Global Markets units, both under ordinary circumstances and in situations of heightened risk factors. The standard metric used to measure market risk is Value at Risk (“VaR”), which indicates the maximum loss that may occur in the portfolios at a given confidence level (99%) and time horizon (one day). This statistic value is widely used in the market and has the advantage of summing up in a single metric the risks inherent to trading activity, taking into account how they are related and providing a prediction of the loss that the trading book could sustain as a result of fluctuations in equity prices, interest rates, foreign exchange rates and credit spreads. The market risk analysis considers various risks, such as credit spread risk, basis risk, as well as volatility and correlation risk. With respect to the risk measurement models used by the BBVA Group, the Bank of Spain has authorized the use of the internal market risk model to determine bank capital requirements deriving from risk positions on the BBVA S.A. and BBVA Mexico trading book, which jointly accounted for around 77%, 72% and 72% of the Group’s trading-book market risk as of December 31, 2021, 2020 and 2019. For the rest of the geographical areas where the Group operates (applicable mainly to the Group´s South America subsidiaries and Garanti BBVA), bank capital for the risk positions in the trading book is calculated using the Standardized Approach defined by the Basel Committee on Banking Supervision (which is referred to herein as the "standard model”). The current management structure includes the monitoring of market-risk limits, consisting of a scheme of limits based on VaR, economic capital (based on VaR measurements) and VaR sub-limits, as well as stop-loss limits for each of the Group’s business units. The model used estimates VaR in accordance with the historical simulation methodology, which involves estimating losses and gains that would have taken place in the current portfolio if the changes in market conditions that took place over a specific period of time in the past were repeated. Based on this information, it predicts the maximum expected loss of the current portfolio within a given confidence level. This model has the advantage of reflecting precisely the historical distribution of the market variables and not assuming any specific distribution of probability. The historical period used in this model is two years. VaR figures are estimated with the following methodologies: –VaR without smoothing, which awards equal weight to the daily information for the previous two years. This is currently the official methodology for measuring market risks for the purpose of monitoring compliance with risk limits. –VaR with smoothing, which gives a greater weight to more recent market information. This metric supplements the previous one. The use of VaR by historical simulation methodology as a risk metric has many advantages, but also certain limitations, among which it is worth highlighting: –The estimate of the maximum daily loss of the Global Markets portfolio positions (with a confidence level of 99%) depends on the market movements of the last two years, not picking up the impact of large market events if they have not occurred within that historical window –The use of the 99% confidence level does not consider potential losses that can occur beyond this level. To mitigate this limitation, different stress exercises are also performed, as described later. At the same time, and following the guidelines established by the Spanish and European authorities, BBVA incorporates metrics in addition to VaR with the aim of meeting the Bank of Spain's regulatory requirements with respect to the calculation of bank capital for the trading book. Specifically, the measures incorporated in the Group since December 2011 (stipulated by Basel 2.5) are: –VaR: In regulatory terms, the VaR charge incorporates the stressed VaR charge, and the sum of the two (VaR and stressed VaR) is calculated. This quantifies the losses associated with the movements of the risk factors inherent to market operations (including interest-rate risk, exchange-rate risk, equity risk and credit risk, among others). Both VaR and stressed VaR are rescaled by a regulatory multiplier (between three and four) and by the square root of ten to calculate the capital charge. –Specific Risk - Incremental Risk Capital (“IRC”). Quantification of the risks of default and changes of the credit ratings of the bond and derivative positions and debt funds with daily look-through or significant benchmark (correlation > 90%) in the trading portfolio. The IRC charge is exclusively applied in entities in respect of which the internal market risk model is used (i.e. BBVA, S.A. and BBVA Mexico). The IRC charge is determined based on the associated losses (calculated at 99.9% confidence level over a one year horizon under the hypothesis of constant risk) due to a rating change and/or default of the issuer with respect to an asset. In addition, the price risk is included in sovereign positions for the specified items. –Specific Risk: Securitization, correlation portfolios and Investment funds without look-through. Capital charges for securitizations and correlation portfolios are assessed based on the potential losses associated with the occurrence of a credit event in the underlying exposures. They are calculated by the standard model. The scope of the correlations portfolios refers to the First To Default (FTD)-type market operation and/or tranches of market CDOs and only for positions with an active market and hedging capacity. Capital charge for Funds include losses associated with volatility and credit risk of the underling positions of the fund. All charges are calculated by the standard model. Validity tests are performed regularly on the risk measurement models used by the Group. They estimate the maximum loss that could have been incurred in the assessed positions with a certain level of probability (backtesting), as well as measurements of the impact of extreme market events on risk positions (stress testing). As an additional control measure, backtesting is conducted at a trading desk level in order to enable more specific monitoring of the validity of the measurement models. Market risk in 2021 The Group’s market risk related to its trading portfolio remained in 2021 at low levels compared to other risks managed by BBVA, particularly credit risk. This is due to the nature of the business. In 2021 the average VaR was €29 million, above the figure of 2020, with a maximum level in the year reached on the day April 7, 2021 of €36 million. The evolution in the BBVA Group’s market risk during 2021, measured as VaR without smoothing (see Glossary) with a 99% confidence level and a 1-day horizon (shown in Millions of Euros) is as follows: By type of market risk assumed by the Group's trading portfolio, the main risk factor for the Group continued to be that linked to interest rates, with a weight of 57% of the total at December 31, 2021 (this figure includes the spread risk). The relative weight of this risk has slightly increased compared with the close of 2020 (56%). Exchange-rate risk accounted for 16% of the total risk, decreasing its weight with respect to December 2020 (22%), while equity, volatility and correlation risk has increased, with a weight of 28% at the close of 2021 (vs. 22% at the close of 2020). As of December 31, 2021, 2020 and 2019 the VaR was €31 million, €28 million and €20 million, respectively. The total VaR figures for 2021, 2020 and 2019 can be broken down as follows:
VaR by Risk Factor (Millions of Euros)
| Interest/Spread risk | Currency risk | Stock-market risk | Vega/Correlation risk | Diversification effect(*) | Total
2021 |  |  |  |  |  |
VaR average in the year | 33 | 10 | 2 | 11 | (28) | 29
VaR max in the year | 32 | 13 | 4 | 1 | (14) | 36
VaR min in the year | 27 | 9 | 1 | 10 | (25) | 22
End of period VaR | 34 | 9 | 5 | 11 | (29) | 31
2020 |  |  |  |  |  |
VaR average in the year | 29 | 12 | 4 | 11 | (28) | 27
VaR max in the year | 39 | 20 | 10 | 20 | (14) | 39
VaR min in the year | 20 | 3 | 1 | 6 | (39) | 18
End of period VaR | 32 | 12 | 2 | 11 | (29) | 28
2019 |  |  |  |  |  |
VaR average in the year | 21 | 6 | 4 | 9 | (20) | 19
VaR max in the year | 28 | 6 | 3 | 9 | (21) | 25
VaR min in the year | 13 | 5 | 5 | 9 | (18) | 14
End of period VaR | 24 | 5 | 5 | 8 | (22) | 20
(*) The diversification effect is the difference between the sum of the average individual risk factors and the total VaR figure that includes the implied correlation between all the variables and scenarios used in the measurement. Validation of the internal market risk model The internal market risk model is validated on a regular basis by backtesting in both, BBVA, S.A. and Global Markets Mexico (in BBVA Mexico). The aim of backtesting is to validate the quality and precision of the internal market risk model used by BBVA Group to estimate the maximum daily loss of a portfolio, at a 99% level of confidence and a 250-day time horizon, by comparing the Group's results and the risk measurements generated by the internal market risk model. These tests showed that the internal market risk model of both, BBVA, S.A. and Global Markets Mexico is adequate and precise. Two types of backtesting have been carried out in 2021, 2020 and 2019: –"Hypothetical" backtesting: the daily VaR is compared with the results obtained, not taking into account the intraday results or the changes in the portfolio positions. This validates the appropriateness of the market risk metrics for the end-of-day position. –"Real" backtesting: the daily VaR is compared with the total results, including intraday transactions, but discounting the possible minimum charges or fees involved. This type of backtesting includes the intraday risk in portfolios. In addition, each of these two types of backtesting was carried out at a risk factor or business type level, thus making a deeper comparison of the results with respect to risk measurements. For the period between the year ended December 31, 2020 and the year ended December 31, 2021, the backtesting of the internal VaR calculation model was carried out, comparing the daily results obtained to the risk level estimated by the internal VaR calculation model. In that period, there was one negative exception in BBVA S.A. In BBVA Mexico, there was also a negative exception. At the end of the year the comparison showed the internal VaR calculation model was working correctly, within the "green" zone (0-4 exceptions), thus validating the internal VaR calculation model, as has been the case each year since the internal market risk model was approved for the Group. Stress testing A number of stress tests are carried out on the BBVA Group's trading portfolios. First, global and local historical scenarios are used that replicate the behavior of an extreme past event, such as for example the collapse of Lehman Brothers or the "Tequilazo" crisis. These stress tests are complemented with simulated scenarios, where the aim is to generate scenarios that have a significant impact on the different portfolios, but without being anchored to any specific historical scenario. Finally, for some portfolios or positions, fixed stress tests are also carried out that have a significant impact on the market variables affecting these positions. Historical scenarios The historical benchmark stress scenario for the BBVA Group is Lehman Brothers, whose sudden collapse in September 2008 led to a significant impact on the behavior of financial markets at a global level. The following are the most relevant effects of this historical scenario: –Credit shock: reflected mainly in the increase of credit spreads and downgrades in credit ratings. –Increased volatility in most of the financial markets (giving rise to a great deal of variation in the prices of different assets (currency, equity, debt). –Liquidity shock in the financial systems, reflected by a major movement in interbank curves, particularly in the shortest sections of the euro and dollar curves. Simulated scenarios Unlike the historical scenarios, which are fixed and therefore not suited to the composition of the risk portfolio at all times, the scenario used for the exercises of economic stress is based on resampling methodology. This methodology is based on the use of dynamic scenarios that are recalculated periodically depending on the main risks affecting the trading portfolios. On a data window wide enough to collect different periods of stress (data are taken from January 1, 2008 until the date of the assessment), a simulation is performed by resampling of historic observations, generating a distribution of losses and gains that serve to analyze the most extreme of births in the selected historical window. The advantage of this methodology is that the period of stress is not predetermined, but depends on the portfolio maintained at each time, and making a large number of simulations (10,000 simulations) allows a greater richness of information for the analysis of expected shortfall than what is available in the scenarios included in the calculation of VaR. The main features of this approach are: a) the generated simulations respect the correlation structure of the data, b) there is flexibility in the inclusion of new risk factors and c) it allows the introduction of a lot of variability in the simulations (desirable for considering extreme events). The impact of the stress test under multivariable simulation of the risk factors of the portfolio based on the expected shortfall (expected shortfall calculated at a 97.5% confidence level, 20 days) as of December 31, 2021 is as follows:
Impact of the stress test (Millions of Euros)
0 | Europe | Mexico | Peru | Venezuela | Argentina | Colombia | Turkey
Expected shortfall | (76) | (75) | (11) | — | (5) | (5) | (8)
Financial instruments offset Financial assets and liabilities may be netted in certain cases. In particular, they are presented for a net amount on the consolidated balance sheet only when the Group's entities satisfy the provisions of IAS 32-Paragraph 42, so they have both the legal right to net recognized amounts, and the intention of settling the net amount or of realizing the asset and simultaneously paying the liability. In addition, the Group has presented as gross amounts assets and liabilities on the consolidated balance sheet for which there are master netting arrangements in place, but for which there is no intention of settling the net amount. The most common types of events that trigger the netting of reciprocal obligations are bankruptcy of the entity, surpassing certain level of indebtedness threshold, failure to pay, restructuring and dissolution of the entity. In the current market context, derivatives are contracted under different framework contracts being the most widespread the ones developed by the International Swaps and Derivatives Association (“ISDA”) and, for the Spanish market, the Framework Agreement on Financial Transactions (“CMOF”). Almost all portfolio derivative transactions have been concluded under these framework contracts, including in them the netting clauses mentioned in the preceding paragraph as "Master Netting Agreement", greatly reducing the credit exposure on these instruments. Additionally, in contracts signed with counterparties, the collateral agreement annexes called Credit Support Annex (“CSA”) are included, thereby minimizing exposure to a potential default of the counterparty. Moreover, many of the transactions involving assets purchased or sold under a repurchase agreement are transacted through clearing houses that articulate mechanisms to reduce counterparty risk, as well as through the signing of various master agreements for bilateral transactions, the most widely used being the Global Master Repurchase Agreement (GMRA), published by the International Capital Market Association (“ICMA”), to which the clauses related to the collateral exchange are usually added within the text of the master agreement itself. A summary of the effect of offsetting (via netting and collateral) for derivatives and securities operations is presented below as of December 31, 2021, 2020 and 2019:
Effect of offsetting for derivatives and securities operation (Millions of Euros)
|  |  |  |  | Gross amounts not offset in the consolidated balance sheets (D) |
| Notes | Gross amounts recognized (A) | Gross amounts offset in the consolidated balance sheets (B) | Net amount presented in the consolidated balance sheets (C=A-B) | Financial instruments | Cash collateral received/ pledged | Net amount (E=C-D)
December 2021 |  |  |  |  |  |  |
Trading and hedging derivatives | 10, 15 | 36,349 | 3,611 | 32,737 | 22,524 | 8,758 | 1,456
Reverse repurchase, securities borrowing and similar agreements |  | 54,296 | — | 54,296 | 55,010 | 2,213 | (2,927)
Total assets |  | 90,645 | 3,611 | 87,034 | 77,534 | 10,971 | (1,471)
Trading and hedging derivatives | 10, 15 | 37,916 | 3,584 | 34,331 | 22,524 | 10,119 | 1,688
Repurchase, securities lending and similar agreements |  | 54,159 | — | 54,159 | 58,174 | 679 | (4,694)
Total liabilities |  | 92,074 | 3,584 | 88,490 | 80,698 | 10,798 | (3,006)
December 2020 |  |  |  |  |  |  |
Trading and hedging derivatives | 10, 15 | 47,862 | 5,688 | 42,173 | 33,842 | 9,018 | (686)
Reverse repurchase, securities borrowing and similar agreements |  | 32,121 | — | 32,121 | 32,762 | 161 | (802)
Total assets |  | 79,983 | 5,688 | 74,294 | 66,604 | 9,178 | (1,488)
Trading and hedging derivatives | 10, 15 | 49,720 | 5,722 | 43,998 | 33,842 | 9,435 | 721
Repurchase, securities lending and similar agreements |  | 41,571 | — | 41,571 | 42,298 | 1,619 | (2,346)
Total liabilities |  | 91,291 | 5,722 | 85,569 | 76,140 | 11,054 | (1,624)
December 2019 |  |  |  |  |  |  |
Trading and hedging derivatives | 10, 15 | 36,349 | 2,388 | 33,961 | 25,020 | 8,210 | 731
Reverse repurchase, securities borrowing and similar agreements |  | 33,539 | 21 | 33,518 | 33,352 | 204 | (39)
Total assets |  | 69,888 | 2,409 | 67,479 | 58,372 | 8,415 | 692
Trading and hedging derivatives | 10, 15 | 38,693 | 2,394 | 36,299 | 25,020 | 10,613 | 667
Repurchase, securities lending and similar agreements |  | 43,712 | 21 | 43,691 | 42,974 | 420 | 297
Total liabilities |  | 82,404 | 2,414 | 79,990 | 67,993 | 11,033 | 964
The amount of recognized financial instruments within derivatives includes the effect in case of compensation with counterparties with which the Group holds netting agreements, while, for repos, it reflects the market value of the collateral associated with the transaction. Liquidity and Funding riskLiquidity and funding risk is defined as the incapacity of a bank in meeting its payment commitments due to lack of funds or that, to face those commitments, should have to make use of funding under burdensome terms.Liquidity and Funding Strategy and PlanningThe BBVA Group is a multinational financial institution whose business is focused mainly on retail and commercial banking activities. In addition to the retail business model, which forms its core business, the Group engages in corporate and investment banking, through the global CIB (Corporate & Investment Banking) division. Liquidity and Funding Risk Management aims to maintain a balance sheet structure which allows a sustainable business model. The Group’s liquidity and funding strategy is based on the following pillars: –The principle of the funding self-sufficiency of its subsidiaries, meaning that each of the Liquidity Management Units (LMU) must cover its funding needs independently on the markets where it operates. This avoids possible contagion due to a crisis affecting one or more of the Group’s LMU. –Stable customer deposits as the main source of funding in all the LMU, in accordance with the Group’s business model. –Diversification of the sources of wholesale funding, in terms of maturity, market, instruments, counterparties and currencies, with recurring access to the markets. –Compliance with regulatory requirements, ensuring the availability of ample liquidity buffers, of high quality, as well as sufficient instruments as required by regulations with the capacity to absorb losses. –Compliance with the internal Liquidity Risk and Funding metrics, while adhering to the Risk Appetite level established for each LMU at any time. Liquidity and Funding Risk Management aims, in the short term, to prevent an entity from having difficulties in meeting its payment commitments in due time and form or that, to meet them, it has to resort to obtaining funds in burdensome conditions that deteriorate the image or reputation of the entity. In the medium term, its objective is to support the suitability of the Group's financial structure and its evolution, within the framework of the economic situation, the markets and regulatory changes. This management of structural and liquidity funding is based on the principle of financial self-sufficiency of the entities that comprise it. This approach helps prevent and limit liquidity risk by reducing the Group’s vulnerability during periods of high risk. This decentralized management prevents possible contagion from a crisis affecting only one or a few Group entities, which must act independently to meet their liquidity requirements in the markets where they operate. Within this strategy, the BBVA Group is organized into eight LMUs composed of the parent company and the bank subsidiaries in each geography, plus the branches that depend on them. In addition, the policy for managing liquidity and funding risk is also based on the model’s effectiveness and on the planning and integration of risk management into the budgeting process of each LMU, according to the financing risk appetite that it decides to assume in its business. Liquidity and funding planning is part of the strategic processes for the Group’s budgetary and business planning. This objective is to allow a recurrent growth of the banking business with suitable maturities and costs within the established risk tolerance levels by using a wide range of instruments which allow the diversification of the funding sources and the maintenance of a high volume of available liquid assets. Governance and monitoring The responsibility for liquidity and funding management in the development of normal business activity lies with the Finance area as a first line of defense in managing the risks inherent to this activity, in accordance with the principles established by the European Banking Authority (EBA) and in line with the most demanding standards, policies, procedures and controls in the framework established by the governing bodies. Finance, through the Balance-Sheet Management area, plans and executes the funding of the structural long-term gap of each LMU and proposes to the Assets and Liabilities Committee (ALCO) the actions to be taken on this matter, in accordance with the policies established by the Risk Committee in line with the metrics of the Risk Appetite Framework approved by the Board of Directors. Finance is also responsible for preparing the regulatory reporting of liquidity, coordinating with the responsible areas in each LGU the necessary processes to cover the requirements at corporate and regulatory level, ensuring the integrity of the information provided. GRM is responsible for ensuring that the liquidity and financing risk in the Group is managed in accordance with the framework established by governing bodies. It also deals with the identification, measurement, monitoring and control of such risks and their communication to the relevant corporate bodies. In order to carry out this task properly, the risk function in the Group has been configured as a single, global function, independent of the management areas. Additionally, the Group has, in its second line of defense, an Internal Risk Control unit, which performs an independent review of the control of Liquidity and Funding Risk, and a Financial Internal Control Unit that reviews the design and effectiveness of the controls operations on liquidity management and reporting. As the third line of defense of the Group's internal control model, Internal Audit is in charge of reviewing specific controls and processes in accordance with a work plan that is drawn up annually. The Group’s fundamental objectives regarding the liquidity and funding risk are determined through the Liquidity Coverage Ratio (LCR) and through the Loan-to-Stable Customer Deposits (LtSCD) ratio. The LCR ratio is a regulatory metric that aims to enable the resilience of entities in a scenario of liquidity tension within a time horizon of 30 days. Within its risk appetite framework and system of limits and alerts, BBVA has established a required LCR compliance level for the entire Group and for each individual LMU. The internal levels required are aimed at efficiently meeting the regulatory requirement, at a loose level above 100%. The LtSCD ratio measures the relationship between net lending and stable customer funds. The aim is to preserve a stable funding structure in the medium term for each of the LMU which make up the BBVA Group, taking into account that maintaining an adequate volume of stable customer funds is key to achieving an appropriate liquidity profile. In geographical areas with dual-currency balances, the indicator is also controlled by currency to manage the mismatches that might occur. Stable customer funds are considered to be the financing obtained and managed from the LMU among their target customers. Those funds are characterized by their low sensitivity to market changes and by their less volatile behavior at aggregated level per operation due to the loyalty of the customer to the entity. The stable resources are calculated by applying to each identified customer segment a haircut determined by the analysis of the stability if the balances by which different aspects are evaluated (concentration, stability, level of loyalty). The main source of stable resources arises from wholesale funding and retail customer funds. In order to establish the target (maximum) levels of LtSCD in each LMU and provide an optimal funding structure reference in terms of risk appetite, the corporate Structural Risks unit of GRM identifies and assesses the economic and financial variables that condition the funding structures in the different geographical areas. Additionally, liquidity and funding risk management aims to achieve a proper diversification of the funding structure, avoiding excessive dependence on short-term funding by establishing a maximum level for the short-term funds raised, including both wholesale financing and the least stable proportion of customer funds In relation to long-term financing, the maturity profile does not present significant concentrations, which makes it possible to adapt the schedule of the planned issuance plan to the best financial conditions in the markets. Lastly, concentration risk is monitored at LMU level, with the aim of ensuring a correct diversification of both the counterparty and type of instrument. One of the fundamental metrics within the general management framework of the liquidity and funding risk is the maintenance of a liquidity buffer consisting of high quality assets free of charges which can be sold or offered as collateral to obtain funding, either under normal market conditions or in stress situations. The Finance area is responsible for the collateral management and determining the liquidity buffer within the BBVA Group. According to the principle of auto-sufficiency of the Group's subsidiaries, each LMU is responsible for maintaining a buffer of liquid assets which complies with the regulatory requirements applicable under each jurisdiction. In addition, the liquidity buffer of each LMU must be aligned with the liquidity and funding risk tolerance as well as the management limits set and approved for each case. In this context, the short-term resistance of the liquidity risk profile is promoted, ensuring that each LMU has sufficient collateral to deal with the risk of the closing of wholesale markets. Basic capacity is the internal metric for the management and control of short-term liquidity risk, which is defined as the relationship between the explicit assets available and the maturities of wholesale liabilities and volatile resources, at different time periods up to one year, with special relevance at 30 and 90 days, with the objective of preserving the survival period above 3 months with the available buffer, without considering the balance inflows. As a fundamental element of the liquidity and financing risk monitoring scheme, stress tests are carried out. They enable to anticipate deviations from the liquidity targets and the limits set in the appetite, and to establish tolerance ranges in the different management areas. They also play a major role in the design of the Liquidity Contingency Plan and the definition of specific measures to be adopted to rectify the risk profile if necessary. For each scenario, it is checked whether BBVA has a sufficient stock of liquid assets to meet the liquidity commitments/outflows in the different periods analyzed. The analysis considers four scenarios: one central and three crisis-related (systemic crisis; unexpected internal crisis with a considerable rating downgrade and/or affecting the ability to issue in wholesale markets and the perception of business risk by the banking intermediaries and the entity’s clients; and a mixed scenario, as a combination of the two aforementioned scenarios). Each scenario considers the following factors: existing market liquidity, customer behavior and sources of funding, the impact of rating downgrades, market values of liquid assets and collateral, and the interaction between liquidity requirements and the development of BBVA's credit quality. The stress tests conducted on a regular basis by GRM reveal that BBVA maintains a sufficient buffer of liquid assets to deal with the estimated liquidity outflows in a scenario resulting from the combination of a systemic crisis and an unexpected internal crisis, during a period of longer than 3 months in general for the different LMU (including Turkey closing the year above 6 months), including in the scenario of a significant downgrade of the Bank’s rating by up to three notches. Together with the results of the stress tests and the risk metrics, the early warning indicators play an important role within the corporate model and the Liquidity Contingency Plan. They are mainly indicators of the funding structure, in relation to asset encumbrance, counterparty concentration, flights of customer deposits, unexpected use of credit facilities, and of the market, which help anticipate possible risks and capture market expectations. Finance is the area responsible for the elaboration, monitoring, execution and update of the liquidity and funding plan and of the market access strategy to assist in and improve the stability and diversification of the wholesale funding sources. In order to implement and establish management in an anticipated manner, limits are set on an annual basis for the main management metrics that form part of the budgeting process for the liquidity and funding plan. This framework of limits contributes to the planning of the joint future performance of: –The loan book, considering the types of assets and their degree of liquidity, as well as their validity as collateral in collateralized funding. –Stable customer funds, based on the application of a methodology for establishing which segments and customer balances are considered to be stable or volatile funds based on the principle of sustainability and recurrence of these funds. –Projection of the credit gap, in order to require a degree of self-funding that is defined in terms of the difference between the loan-book and stable customer funds. –Incorporating the planning of securities portfolios into the banking book, which include both fixed-interest and equity securities, and are classified as financial assets at fair value through other comprehensive income and at amortized cost, and additionally on trading portfolios. –The structural gap projection, as a result of assessing the funding needs generated both from the credit gap and by the securities portfolio in the banking book, together with the rest of on-balance-sheet wholesale funding needs, excluding trading portfolios. This gap therefore needs to be funded with customer funds that are not considered stable or on wholesale markets. As a result of these funding needs, the BBVA Group plans the target wholesale funding structure according to the tolerance set in each LMU target. Thus, once the structural gap has been identified and after resorting to wholesale markets, the amount and composition of wholesale structural funding is established in subsequent years, in order to maintain a diversified funding mix and guarantee that there is not a high reliance on short-term funding (short-term wholesale funding plus volatile customer funds). In practice, the execution of the principles of planning and self-funding at the different LMU results in the Group’s main source of funding being customer deposits, which consist mainly of demand deposits, savings deposits and time deposits. As sources of funding, customer deposits are complemented by access to the interbank market and the domestic and international capital markets in order to address additional liquidity requirements, implementing domestic and international programs for the issuance of commercial paper and medium and long-term debt. The process of analysis and assessment of the liquidity and funding situation and of the inherent risks is a process carried out on an ongoing basis in the BBVA Group, with the participation of all the Group areas involved in liquidity and funding risk management. This process is carried out at both local and corporate level. It is incorporated into the decision- making process for liquidity and funding management, with integration between the risk appetite strategy and establishment and the planning process, the funding plan and the limits scheme. Liquidity and funding performance The BBVA Group maintains an adequate and dynamic funding structure with a predominantly retail nature, where customer resources represent the main source of funding. During 2021, liquidity conditions have remained comfortable in all the countries where the BBVA Group operates. The global crisis caused by COVID-19 had a significant impact on financial markets. The effects of this crisis on the Group's balance sheets materialized fundamentally at first, through greater credit line withdrawals by wholesale clients in view of the worsening financing conditions in the markets, with no significant effect on the retail portfolio. These withdrawals were largely paid off over the following quarters. Dealing with this situation of initial uncertainty, the different central banks provided a joint response through specific measures and programs, whose extension, in some cases, has been prolonged during 2021, to facilitate the financing of the real economy and the provision of liquidity in financial markets, supporting the suitability of liquidity buffers in almost all areas with BBVA presence. The performance of the indicators show that the adequacy of the funding structure remained steady during 2021, 2020 and 2019, in the sense that all LMU held self-funding levels with stable customer resources above the requirements.
LtSCD by LMU
| 2021 | 2020 | 2019
Group (average) | 95% | 95% | 108%
BBVA S.A. | 98% | 97% | 108%
BBVA Mexico | 93% | 98% | 116%
Garanti BBVA | 81% | 95% | 99%
Other LMU | 93% | 86% | 103%
With respect to LCR, the Group has maintained a liquidity buffer at both a consolidated and individual level in 2021. As a result, the ratio has remained comfortably above 100%, with the consolidated ratio as of December 31, 2021 standing at 165%. Although this requirement is only established at a Group level, for banks in the Eurozone, the minimum level required is comfortably exceeded in all subsidiaries. It should be noted that the calculation of the Consolidated LCR does not allow the transfer of liquidity between subsidiaries, so no excess liquidity may be transferred from these entities for the purpose of calculating the consolidated ratio. If the impact of these highly liquid assets was considered, the LCR would be 213%, or +48 basis points above the required level.
LCR main LMU
0 | 2021 | 2020 | 2019
Group | 165% | 149% | 129%
BBVA S.A. | 190% | 173% | 147%
BBVA Mexico | 245% | 196% | 147%
Garanti BBVA | 211% | 183% | 206%
One of the key elements in BBVA's Group liquidity and funding management is the maintenance of large high quality liquidity buffers in all business areas where the group operates. Each entity maintains a consistent liquidity buffer at the individual level for BBVA, S.A. and for each of its subsidiaries, such as BBVA Mexico, Garanti BBVA and the Latin American subsidiaries. In general, this buffer has been strengthened during 2021 in the LMU. In this respect, the Group has maintained for the last 12 months an average volume of high quality liquid assets (HQLA) amounting to €138.2 billion, among which, 93% correspond to maximum quality assets (LCR Level 1). The table below shows the liquidity available by instrument as of December 31, 2021, 2020 and 2019 for the most significant entities based on prudential supervisor’s information (Commission Implementing Regulations (EU) 2017/2114 of November 9, 2017):
Liquidity available by instrument (Millions of Euros)
| BBVA S.A. | BBVA Mexico |  | Garanti BBVA | Other
| 2021 | 2020 | 2019 | 2021 | 2020 | 2019 |  |  |  | 2021 | 2020 | 2019 | 2021 | 2020 | 2019 (*)
Cash and withdrawable central bank reserves | 35,258 | 39,330 | 14,516 | 12,146 | 8,930 | 6,246 |  |  |  | 8,179 | 6,153 | 6,450 | 6,469 | 6,831 | 11,317
Level 1 tradable assets | 37,272 | 48,858 | 41,961 | 13,881 | 9,205 | 7,295 |  |  |  | 5,549 | 7,019 | 7,953 | 6,036 | 6,237 | 14,930
Level 2A tradable assets | 5,234 | 5,119 | 403 | 74 | 106 | 316 |  |  |  | — | — | — | — | — | 344
Level 2B tradable assets | 9,492 | 6,080 | 5,196 | 28 | 11 | 219 |  |  |  | — | — | — | 2 | — | 12
Other tradable assets | 27,870 | 20,174 | 22,213 | 343 | 421 | 1,269 |  |  |  | 722 | 701 | 669 | 934 | 745 | 1,538
Non tradable assets eligible for central banks | — | — | — | — | — | — |  |  |  | — | — | — | — | — | 2,935
Cumulated counterbalancing capacity | 115,127 | 119,560 | 84,288 | 26,472 | 18,672 | 15,344 |  |  |  | 14,449 | 13,873 | 15,072 | 13,440 | 13,814 | 31,075
(*) In 2019 it includes the balance of the companies in the United States (see Notes 1.3, 3 and 21). The Net Stable Funding Ratio (NSFR), defined as the result between the amount of stable funding available and the amount of stable funding required, requiring banks to maintain a stable financing profile in relation to the composition of their assets and off-balance sheet activities. This ratio should be at least 100% at all times. The NSFR ratio of the BBVA Group, calculated by applying the regulatory criteria established in Regulation (EU) 2019/876 of the European Parliament and of the Council, of May 20, 2019, entered into force in June 2021, and stood at 135% as of December 31, 2021. The NSFR of BBVA Group and its main LMU at December 31, 2021, 2020 and 2019, was the following:
NSFR main LMU
| 2021 | 2020(*) | 2019(*)
Group | 135 % | 127 % | 120 %
BBVA S.A. | 126% | 121% | 113%
BBVA Mexico | 149% | 138% | 130%
Garanti BBVA | 162% | 154% | 151%
(*) Ratio calculated based on the Basel requirements for 2019 and 2020. Below is a matrix of residual maturities by contractual periods based on supervisory prudential reporting as of December 31, 2021, 2020 and 2019:
December 2021. Contractual maturities (Millions of Euros)
| Demand | Up to 1 month | 1 to 3 months | 3 to 6 months | 6 to 9 months | 9 to 12 months | 1 to 2 years | 2 to 3 years | 3 to 5 years | Over 5 years | Total
ASSETS |  |  |  |  |  |  |  |  |  |  |
Cash, cash balances at central banks and other demand deposits | 39,761 | 24,598 | — | — | — | — | — | — | — | — | 64,359
Deposits in credit entities | — | 3,781 | 400 | 790 | 373 | 299 | 211 | 166 | 8 | 26 | 6,056
Deposits in other financial institutions | 2 | 901 | 801 | 584 | 727 | 432 | 694 | 470 | 261 | 469 | 5,343
Reverse repo, securities borrowing and margin lending | — | 33,856 | 11,611 | 2,945 | 1,063 | 1,692 | 2,188 | 2,239 | 1,118 | 739 | 57,451
Loans and advances | 174 | 18,531 | 23,185 | 22,141 | 11,769 | 13,782 | 39,656 | 30,049 | 44,508 | 94,780 | 298,574
Securities' portfolio settlement | 10 | 1,779 | 3,606 | 3,395 | 2,333 | 3,958 | 18,854 | 13,135 | 17,214 | 47,331 | 111,614
December 2021. Contractual maturities (Millions of Euros)
| Demand | Up to 1 month | 1 to 3 months | 3 to 6 months | 6 to 9 months | 9 to 12 months | 1 to 2 years | 2 to 3 years | 3 to 5 years | Over 5 years | Total
LIABILITIES |  |  |  |  |  |  |  |  |  |  |
Wholesale funding | — | 3,065 | 1,077 | 3,498 | 2,914 | 1,885 | 9,477 | 4,931 | 12,332 | 19,991 | 59,169
Deposits in financial institutions | 1,936 | 4,257 | 415 | 825 | 183 | 924 | 496 | 146 | 146 | 579 | 9,907
Deposits in other financial institutions and international agencies | 8,894 | 2,728 | 1,700 | 382 | 289 | 227 | 578 | 231 | 337 | 722 | 16,087
Customer deposits | 281,812 | 28,806 | 11,814 | 4,867 | 1,717 | 1,520 | 1,740 | 578 | 863 | 416 | 334,132
Security pledge funding | — | 52,437 | 6,858 | 2,485 | 1,513 | 8,252 | 29,954 | 5,527 | 4,755 | 1,490 | 113,269
Derivatives, net | (33) | (395) | (176) | (326) | (66) | (641) | 100 | (122) | (155) | (66) | (1,880)
December 2020. Contractual maturities (Millions of Euros) (*)
| Demand | Up to 1 month | 1 to 3 months | 3 to 6 months | 6 to 9 months | 9 to 12 months | 1 to 2 years | 2 to 3 years | 3 to 5 years | Over 5 years | Total
ASSETS |  |  |  |  |  |  |  |  |  |  |
Cash, cash balances at central banks and other demand deposits | 42,518 | 32,741 | — | — | — | — | — | — | — | — | 75,258
Deposits in credit entities | — | 3,616 | 677 | 921 | 356 | 461 | 117 | 120 | 2 | 39 | 6,309
Deposits in other financial institutions | — | 2,202 | 855 | 797 | 734 | 543 | 1,251 | 721 | 515 | 500 | 8,119
Reverse repo, securities borrowing and margin lending | — | 20,033 | 4,757 | 1,351 | 364 | 368 | 3,320 | 1,849 | 891 | 1,089 | 34,021
Loans and advances | 279 | 16,939 | 24,280 | 23,012 | 15,579 | 17,032 | 46,182 | 38,851 | 51,709 | 110,173 | 344,036
Securities' portfolio settlement | — | 3,896 | 6,680 | 6,557 | 5,084 | 13,014 | 9,858 | 15,494 | 17,231 | 50,045 | 127,859
(*) It includes the balance of the companies in the United States (see Notes 1.3, 3 and 21).
December 2020. Contractual maturities (Millions of Euros) (*)
| Demand | Up to 1 month | 1 to 3 months | 3 to 6 months | 6 to 9 months | 9 to 12 months | 1 to 2 years | 2 to 3 years | 3 to 5 years | Over 5 years | Total
LIABILITIES |  |  |  |  |  |  |  |  |  |  |
Wholesale funding | — | 4,750 | 2,618 | 3,963 | 1,283 | 1,543 | 10,573 | 7,505 | 12,793 | 23,839 | 68,868
Deposits in financial institutions | 8,838 | 7,859 | 254 | 741 | 152 | 726 | 825 | 189 | 166 | 371 | 20,120
Deposits in other financial institutions and international agencies | 12,735 | 4,324 | 2,694 | 588 | 353 | 272 | 957 | 337 | 459 | 870 | 23,589
Customer deposits | 308,360 | 39,978 | 13,416 | 6,808 | 4,526 | 4,366 | 3,361 | 1,213 | 869 | 799 | 383,694
Security pledge funding | — | 41,239 | 5,301 | 1,643 | 1,192 | 368 | 11,304 | 28,510 | 3,740 | 1,516 | 94,812
Derivatives, net | — | (722) | 15 | (961) | (85) | 134 | (400) | (157) | (264) | (159) | (2,599)
(*) It includes the balance of the companies in the United States (see Notes 1.3, 3 and 21).
December 2019. Contractual maturities (Millions of Euros) (*)
| Demand | Up to 1 month | 1 to 3 months | 3 to 6 months | 6 to 9 months | 9 to 12 months | 1 to 2 years | 2 to 3 years | 3 to 5 years | Over 5 years | Total
ASSETS |  |  |  |  |  |  |  |  |  |  |
Cash, cash balances at central banks and other demand deposits | 20,954 | 20,654 | — | — | — | — | — | — | — | — | 41,608
Deposits in credit entities | — | 3,591 | 283 | 488 | 585 | 503 | 189 | 24 | 120 | 432 | 6,216
Deposits in other financial institutions | — | 1,336 | 1,120 | 796 | 589 | 991 | 1,420 | 1,072 | 672 | 2,089 | 10,084
Reverse repo, securities borrowing and margin lending | — | 21,612 | 3,858 | 2,287 | 561 | 808 | 4,121 | 1,838 | 411 | 803 | 36,299
Loans and advances | 157 | 22,015 | 25,056 | 24,994 | 15,777 | 16,404 | 42,165 | 35,917 | 54,772 | 122,098 | 359,354
Securities' portfolio settlement | — | 1,622 | 3,873 | 6,620 | 2,017 | 7,292 | 21,334 | 6,115 | 13,240 | 46,022 | 108,136
(*) It includes the balance of the companies in the United States (see Notes 1.3, 3 and 21).
December 2019. Contractual maturities (Millions of Euros) (*)
| Demand | Up to 1 month | 1 to 3 months | 3 to 6 months | 6 to 9 months | 9 to 12 months | 1 to 2 years | 2 to 3 years | 3 to 5 years | Over 5 years | Total
LIABILITIES |  |  |  |  |  |  |  |  |  |  |
Wholesale funding | 1 | 1,393 | 1,714 | 4,208 | 1,645 | 4,386 | 8,328 | 10,608 | 10,803 | 27,840 | 70,927
Deposits in financial institutions | 7,377 | 7,608 | 493 | 1,122 | 172 | 1,514 | 386 | 614 | 206 | 510 | 20,004
Deposits in other financial institutions and international agencies | 10,177 | 3,859 | 867 | 381 | 367 | 257 | 982 | 503 | 499 | 952 | 18,843
Customer deposits | 271,638 | 43,577 | 18,550 | 10,013 | 7,266 | 6,605 | 3,717 | 2,062 | 854 | 1,039 | 365,321
Security pledge funding | — | 45,135 | 3,202 | 15,801 | 1,456 | 653 | 3,393 | 7,206 | 759 | 1,308 | 78,914
Derivatives, net | — | (66) | (25) | 29 | (11) | 1,097 | (830) | (278) | (333) | (420) | (838)
(*) I t includes the balance of the companies in the United States (see Notes 1.3, 3 and 21). With regard to the financing structure, the loan portfolio is mostly financed by retail deposits. The “demand” maturity bucket mainly contains the retail customer sight accounts whose behavior historically showed a high level of stability and little concentration. According to a behavior analysis which is done every year in every entity, this type of account is considered to be stable and for liquidity risk purposes receive a better treatment. The most relevant aspects related to the main geographical areas are the following: –In the Eurozone, BBVA has continued to maintain an adequate position with a large high-quality liquidity buffer. During 2021, commercial activity has drawdown liquidity amounting to approximately €9 billion due to the increase in lending activity, especially in the last quarter of the year, as well as the decrease in the volume of deposits, mainly wholesale. It should also be noted that in the second quarter of 2021, the payment of the BBVA USA sale transaction was collected. In addition, in March 2021, BBVA S.A. took part in the TLTRO III liquidity window program to take advantage of the improved conditions announced by the European Central Bank (ECB) in December 2020, with an amount drawn of €3.5 billion that, together with the €34.9 billion available at the end of December 2020, amount to €38.4 billion at the end of December 2021. –In BBVA Mexico, commercial activity has provided liquidity between January and December 2021 in the amount of approximately 73 billion Mexican pesos, derived from a higher growth in customer funds compared to the growth in lending activity. This increased liquidity is expected to be reduced due to the recovery in lending activity expected in 2022. This stable liquidity position has contributed to an efficient policy in the cost of funding, in an environment of higher interest rates. In terms of wholesale issuances, there was no need to refinance any maturities in 2021, having matured in 2021 a subordinated issue amounting to USD 750 million and a senior issue amounting to 4,500 million Mexican pesos. –In the fourth quarter, the Central Bank of the Republic of Turkey made a series of cuts in benchmark rates, despite the increases in the inflation rate, for a total of 400 basis points to 14%, triggering an adverse reaction from the markets and severe currency depreciation. In order to alleviate the depreciation of the currency, during the month of December, the Turkish government implemented a new mechanism to encourage local currency deposits. During 2021, the lending gap in local currency has widened, with a higher increase in loans than in deposits, while the lending gap in foreign currency has narrowed, due to a decline in loans and an increase in deposits. Garanti BBVA continues to maintain a stable liquidity position. –In South America, the liquidity situation remains adequate throughout the region, despite the fact that central banks in the region have started rate hike cycles and withdrawal of stimulus programs that mitigate the impact of the COVID-19 crisis. In Argentina, liquidity in the system and in BBVA continues to increase due to the higher growth in deposits than in loans in local currency. In BBVA Colombia, activity picks up accompanied by the growth in deposits. BBVA Peru maintains stable levels of liquidity, while reducing excess liquidity due to growth in lending activity, combined with a contraction of deposits, following a costs control strategy. The main wholesale financing transactions carried out by the companies of the BBVA Group are listed below: –In March 2021, BBVA S.A. issued a senior preferred debt for an amount of €1 billion, with a maturity of 6 years and an option for early redemption after five years. In September 2021, BBVA S.A. issued a floating rate senior preferred bond totaling €1 billion and maturing in 2 years, the fifth issue made by BBVA linked to environmental, social and governance (ESG) criteria. Additionally, in January 2022, BBVA S.A. issued a €1 billion senior non-preferred bond, with a maturity of 7 years and an option for early redemption in the sixth year, with a coupon of 0.875%. –In Turkey, there have been no issuances in 2021. The Bank renewed its syndicated loans in June and November, indexed to sustainability criteria. On June 2, BBVA Garanti renewed 100% of a syndicated loan, formed by two separate tranches, amounting to USD 279m and €294m, with a 1-year maturity and a cost of Libor +2.50% and Euribor +2.25%, respectively. In November, the Bank renewed 100% of the second tranche of the mentioned loan, for USD 365m and €247m, at a cost of Libor + 2.15% and Euribor + 1.75% respectively. –In South America, BBVA Uruguay issued in February 2021 the first sustainable bond on the Uruguayan financial market for USD 15m at an initial interest rate of 3.854%. The liquidity position of the rest of subsidiaries has continued to be stable in all the jurisdictions in which the Group operates. In this context, BBVA has maintained its objective of strengthening the funding structure of the different Group entities based on growing their self-funding from stable customer funds, while guaranteeing a sufficient buffer of fully available liquid assets, diversifying the various sources of funding available, and optimizing the generation of collateral available for dealing with stress situations in the markets. Asset encumbrance As of December 31, 2021, 2020 and 2019, the encumbered (those provided as collateral for certain liabilities) and unencumbered assets are broken down as follows:
Encumbered and unencumbered assets (Millions of Euros)
| Encumbered assets | Unencumbered assets
| Book value | Fair value | Book value | Fair value
| 2021 | 2020 | 2019 | 2021 | 2020 | 2019 | 2021 | 2020 | 2019 | 2021 | 2020 | 2019
Assets | 114,336 | 121,999 | 101,792 |  |  |  | 548,548 | 614,260 | 596,898 |  |  |
Equity instruments | 307 | 2,134 | 3,526 | 307 | 2,134 | 3,526 | 22,280 | 14,556 | 12,113 | 22,280 | 14,556 | 12,113
Debt securities | 31,557 | 29,379 | 29,630 | 29,527 | 26,112 | 29,567 | 89,307 | 100,108 | 95,611 | 89,307 | 100,108 | 95,611
Loans and advances and other assets | 82,472 | 90,486 | 68,636 |  |  |  | 436,962 | 499,595 | 489,174 |  |  |
The committed value of "Loans and Advances and other assets" corresponds mainly to loans linked to the issue of covered bonds, territorial bonds or long-term securitized bonds (see Note 22.4) as well as those used as a guarantee to access certain funding transactions with central banks. Debt securities and equity instruments correspond to underlying that are delivered in repos with different types of counterparties, mainly clearing houses or credit institutions, and to a lesser extent central banks. Collateral provided to enable derivative transactions is also included as committed assets. As of December 31, 2021, 2020 and 2019, collateral pledges received mainly due to repurchase agreements and securities lending, and those which could be committed in order to obtain funding are provided below:
Collateral received (Millions of Euros)
| Fair value of encumbered collateral received or own debt securities issued | Fair value of collateral received or own debt securities issued available for encumbrance | Fair value of collateral received or own debt securities issued not available for encumbrance
| 2021 | 2020 | 2019 | 2021 | 2020 | 2019 | 2021 | 2020 | 2019
Collateral received | 40,905 | 30,723 | 38,496 | 17,029 | 8,652 | 9,208 | 1,719 | 1,071 | 48
Equity instruments | 289 | 239 | 65 | 265 | 204 | 70 | — | — | —
Debt securities | 40,616 | 30,484 | 38,431 | 16,764 | 8,448 | 9,130 | 1,719 | 1,071 | 38
Loans and advances and other assets | — | — | — | — | — | 8 | — | — | 10
Own debt securities issued other than own covered bonds or ABSs | — | 3 | — | 50 | 94 | 82 | — | — | —
The guarantees received in the form of reverse repurchase agreements or security lending transactions are committed by their use in repurchase agreements, as is the case with debt securities. As of December 31, 2021, 2020 and 2019, financial liabilities issued related to encumbered assets in financial transactions as well as their book value were as follows:
Sources of encumbrance (Millions of Euros)
| Matching liabilities, contingent liabilities or securities lent | Assets, collateral received and own debt securities issued other than covered bonds and ABSs encumbered
| 2021 | 2020 | 2019 | 2021 | 2020 | 2019
Book value of financial liabilities | 137,242 | 131,352 | 124,252 | 151,275 | 147,523 | 135,500
Derivatives | 15,368 | 16,611 | 19,066 | 15,191 | 16,348 | 20,004
Deposits | 109,311 | 98,668 | 87,906 | 120,957 | 111,726 | 94,240
Outstanding subordinated debt | 12,563 | 16,073 | 17,280 | 15,127 | 19,449 | 21,256
Other sources | 620 | 653 | 449 | 3,966 | 5,202 | 4,788

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