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Capital Management, Corporate Governance Transparency Policy and Risk Management (Tables) | 12 Months Ended
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Dec. 31, 2020
Statement [LineItems] |
Summary of Banks's Shareholders | As of December 31, 2020, the Bank’s shareholders are:
FULL NAME/ CORPORATE NAME |  | Participating Interest |  |  | Voting Interest |
Trust “Trust JHB” (1) |  |  | 17.28 |  |  |  | 19.65 |
Carballo Delfín Jorge Ezequiel |  |  | 17.47 |  |  |  | 19.19 |
ANSES FGS Law No. 26425 |  |  | 28.80 |  |  |  | 26.90 |
Grouped shareholders (Local Stock Exchanges) |  |  | 9.72 |  |  |  | 9.28 |
Grouped shareholders (Foreign stock exchanges) |  |  | 26.73 |  |  |  | 24.98 |
Summary of Minimum Capital Requirements Measured on Consolidated Basis | The table below shows the minimum capital requirements measured on a consolidated basis, effective for the month of December 2020, together with the integration thereof (computable equity) as of the end of such month:
Description |  | 12/31/2020 |
Minimum capital requirements |  |  | 41,357,542 |
Computable equity |  |  | 173,448,698 |
Capital surplus |  |  | 132,091,156 |
Summary of Allowance for Credit Losses | The following chart shows the distribution of loan loss allowances according to the type of financial instrument as of December 31, 2020, and 2019:
|  | 12/31/2020 |  |  | 12/31/2019 |
Loans and other financing |  |  | 9,928,122 |  |  |  | 6,901,953 |
Loans commitment |  |  | 23,200 |  |  |  | 23,514 |
Other financial assets |  |  | 18,929 |  |  |  | 14,032 |
Other debt securities at amortized cost |  |  | 5,472 |  |  |  | 63,701 |
Other debt securities at fair value through OCI |  |  | 5,964 |  |  |  | 286 |
|  |  | 9,981,687 |  |  |  | 7,003,486 |
Summary of Key Economic Variables or Assumptions | The following table shows the estimated values for macroeconomic variables used in the models for each scenario (base case, intermediate, downside), with the assigned probability of occurrence to each scenario:
Key Drivers |  | ECL Scenario |  | Assigned Probabilities |  |  | 2020 |  |  | 2021 |  |  | 2022 |
|  |  |  |  |  |  | % |  |  | % |  |  | % |
GDP growth % |  | Base case |  |  | 65 | % |  |  | 5.96 | % |  |  | 2.16 | % |  |  | 3.04 | %
|  | Intermediate |  |  | 30 | % |  |  | 2.66 | % |  |  | (1.52 | )% |  |  | 1.04 | %
|  | Downside |  |  | 5 | % |  |  | (1.80 | )% |  |  | (2.48 | )% |  |  | 1.00 | %
Central Bank base rates % |  | Base case |  |  | 65 | % |  |  | 37.00 | % |  |  | 28.05 | % |  |  | 23.44 | %
|  | Intermediate |  |  | 30 | % |  |  | 45.00 | % |  |  | 35.00 | % |  |  | 30.00 | %
|  | Downside |  |  | 5 | % |  |  | 80.00 | % |  |  | 100.00 | % |  |  | 120.00 | %
CPI % |  | Base case |  |  | 65 | % |  |  | 56.98 | % |  |  | 39.96 | % |  |  | 35.01 | %
|  | Intermediate |  |  | 30 | % |  |  | 68.00 | % |  |  | 65.00 | % |  |  | 49.99 | %
|  | Downside |  |  | 5 | % |  |  | 100.03 | % |  |  | 130.01 | % |  |  | 150.03 | %
Summary of Aging Analysis of Performing Loans in Arrears |
| 51.1.1.2 | The Bank’s internal rating and PD estimation process
The PD represents the probability that a debtor may fail to fulfill its financial obligation, either during the next 12 months (Stage 1) or during the remainder life of the financial asset (Stages 2 and 3). PD is assessed per customer in alignment with the Bank’s risk management model. For the individual analysis portfolio, the rating model developed by the Bank to identify PD-related risks and concentrations according to the Bank’s commercial strategies is based on a behavior module that considers the behavior scores of the commercial portfolio segments and contemplates internal behavior variables and external supplier variables. For the collective analysis portfolio per risk level, the Bank developed a 12-month PD based on a dual matrix that combine internal behavior market scores and generic Bureau Scores, increasing segregation when considering the internal behavior and the financial entities. Lifetime PDs were also developed for each group of assets defined as homogeneous risk to calculate the financial asset amount classified in Stage 2. The proposals to implement PD models are submitted for approval to the Risk Management Committee. The methods, variables, development population, observation windows and results that support the preparation of these models are tested and adjusted at least once a year. The following table discloses the risk levels score and rating arising from the Bank’s models:​​​​​​​​​​​​​​
|  | 12/31/2020 |  |  | 12/31/2019 |
Category |  | Weighted PD |  |  | % Gross Carrying Amount |  |  | Weighted PD |  |  | % Gross Carrying Amount |
Performing |  |  | 2.32 | % |  |  | 96.17 | % |  |  | 2.60 | % |  |  | 95.45 | %
High grade |  |  | 1.13 | % |  |  | 76.20 | % |  |  | 1.25 | % |  |  | 76.40 | %
Standard grade |  |  | 4.79 | % |  |  | 12.64 | % |  |  | 4.83 | % |  |  | 8.23 | %
Sub-standard grade |  |  | 12.48 | % |  |  | 7.33 | % |  |  | 11.64 | % |  |  | 10.82 | %
Past due but not impaired |  |  | 33.24 | % |  |  | 2.70 | % |  |  | 32.13 | % |  |  | 2.84 | %
Impaired |  |  | 100.00 | % |  |  | 1.13 | % |  |  | 100.00 | % |  |  | 1.71 | %
Total |  |  |  |  |  |  | 100.00 | % |  |  |  |  |  |  | 100.00 | %
| 51.1.1.3 | Exposure at default (EAD)
EAD is based on the amounts that the Bank expects to be owed at default during the next 12 month (Stage 1) or during the instruments remaining lifetime (Stages 2 and 3). The EAD model uses the same information sources than PD model. Segmentation is also used in the PD structure. The Bank developed a calculation method for the products that have a defined flow schedule, and another method for the products that provide the customers with a credit line (revolving products). For revolving products, the Bank calculated a credit risk factor that contemplates the use that this credit line could represent in case of default. Upon building the credit risk factors, the aging of the product and level of use was considered, among other characteristics.
| 51.1.1.4 | Loss given default (LGD)
LGD is the estimated loss in the case of default. It is based on the difference between all contractual cash flows and the cash flows expected by the lender (i.e., all cash shortfalls), considering the proceeds from the realization of collateral. It is the supplement to the unit of the recovery rate; that is, the proportion not collected by the Bank with respect to the EAD. Consequently, the amount at default is compared with the present value of the amounts recovered after the date of default. LGD varies based on the type of counterparty, aging, type of claim and the existence of guarantees securing credits. It is expressed as a percentage of the loss for EAD. To calculate LGD, the Bank differentiates per product. The Bank bases its estimates on the historical information observed regarding the recoveries over on default transactions discounted at the effective interest rate of such agreements and measured upon default. Once the recovery rates are obtained, this behavior is projected through the triangle method to estimate the periods with less maturity. Finally, the weighted average of the loss for each portfolio is determined. As PD, LGD are revised by the macroeconomic models used for the prospective view.
| 51.1.2 | Prospective information
The calculation of ECL for risk impairment includes and is revised prospectively with respect to the portfolio behavior. To such end, the Bank examines the macroeconomics variables which have an impact in PD and LGD and designed models that capture such impact for the commercial portfolio, comparable commercial portfolio and consumer portfolio. The main economic variables generating expected losses used to calculate ECL for each economic scenario are as follows:
| • |  | Changes in GDP
| • |  | Interest rates (BADLAR published by the BCRA)
| • |  | Index (CPI)
As established in IFRS 9, impact is calculated based on the different behavior scenarios of the variables; to such end, a 36-month estimate on the variables used for the models is requested from a well-known economic consulting firm. This estimate is prepared for three alternative macroeconomic scenarios, to which a likelihood of occurrence is assigned. Finally, the Bank calculates ECL by applying the alternative scenarios on a weighted basis, which are updated on a quarterly basis according to the financial statements filed each calendar quarter. The following table shows the estimated values for macroeconomic variables used in the models for each scenario (base case, intermediate, downside), with the assigned probability of occurrence to each scenario:​​​​​​​
Key Drivers |  | ECL Scenario |  | Assigned Probabilities |  |  | 2020 |  |  | 2021 |  |  | 2022 |
|  |  |  |  |  |  | % |  |  | % |  |  | % |
GDP growth % |  | Base case |  |  | 65 | % |  |  | 5.96 | % |  |  | 2.16 | % |  |  | 3.04 | %
|  | Intermediate |  |  | 30 | % |  |  | 2.66 | % |  |  | (1.52 | )% |  |  | 1.04 | %
|  | Downside |  |  | 5 | % |  |  | (1.80 | )% |  |  | (2.48 | )% |  |  | 1.00 | %
Central Bank base rates % |  | Base case |  |  | 65 | % |  |  | 37.00 | % |  |  | 28.05 | % |  |  | 23.44 | %
|  | Intermediate |  |  | 30 | % |  |  | 45.00 | % |  |  | 35.00 | % |  |  | 30.00 | %
|  | Downside |  |  | 5 | % |  |  | 80.00 | % |  |  | 100.00 | % |  |  | 120.00 | %
CPI % |  | Base case |  |  | 65 | % |  |  | 56.98 | % |  |  | 39.96 | % |  |  | 35.01 | %
|  | Intermediate |  |  | 30 | % |  |  | 68.00 | % |  |  | 65.00 | % |  |  | 49.99 | %
|  | Downside |  |  | 5 | % |  |  | 100.03 | % |  |  | 130.01 | % |  |  | 150.03 | %
The measures issued by the Argentine government and the BCRA on maturity deferrals or mandatory debt rescheduling gave rise to a considerable reduction in the nonperforming portfolio indicator, a variable dependent on the prospective probability of the default models used by the Bank. Therefore, as of December 31, 2020, to make an adequate estimate of the expected losses adjusted by the macroeconomic context, the Bank applied the probability of default models on the nonperforming portfolio projected as of such date by those models based on the information available prior to the abovementioned measures, instead of using indicators which do not show the actual loan portfolio situation.
| 51.1.3 | Overview of modified and forborne loans
From a risk management point of view, once an asset is forborne or modified, the Bank’s special department for distressed assets continues to monitor the exposure until it is completely and ultimately derecognized. The amortized cost of loans modified during 2020 and the associated net modification amounted to 944,374 and 82,267, respectively. The Bank does not consider loans using the mandatory extensions and payment facilities provide by BCRA as part of such modified loans. The amortized cost of loans modified during 2019 and the associated net modification amounted to 3,138,057 and 58,741, respectively. Moreover, certain debt securities were modified during 2019. The information related to this modification is disclosed in note 20.
| 51.1.4 | Adjustment for expected losses due to COVID-19 pandemic
The pandemic and its direct consequences, (firstly, the preventive lockdown, then the social distancing) had a high impact on the Argentine economy and, therefore, on the behavior of financial system debtors. The Argentine government, the BCRA and other tax and regulatory agencies adopted a series of measures to reduce the impact of the generated economic stagnation which includes the extending tax and social security due dates, offering financial aid to the most vulnerable sectors, deferring payment of all bank debtor’s obligations, mandatory refinancing of past due payables, a more flexible treatment for recognizing the impairment of the banking customer portfolio, and banning dismissals and suspensions, among others. Even though, all of them contributed to having the 2020 with low impact on bank portfolio delinquency, the negative results of the impairment in the debtors’ financial capacity are undeniable, thus an increase in the impairment of assets subject to credit risk is expected. Since statistical models do not appropriately reflect the effects arising from the pandemic on expected credit losses, the Bank decided to make a special adjustment prospectively based on an estimate of the impairment of certain financial assets showing greater vulnerability levels or signs of difficulties related to the payment of obligations. The ECL adjustment for Covid-19 is recalculated on a monthly basis with the objective to capture new information about subject customers and reset the estimated amounts at the reporting date, or adjust the calculation criteria in order to make more accurate estimations. With the same frequency is submitted for approval to the Bank’s highest authorities, and is presented to the Internal Risk Management Committee for its ratification and treatment. As to commercial loans, as of December 31, 2020, the Bank estimated an additional credit risk impairment loss for 445,386, over beneficiaries of credit facilities at reduced rates for payroll payments during the social lockdown and who are part of the economy sectors which are expected to experience the pandemic’s most significant adverse effects, both in terms of a drop in revenues and the subsequent recovery term. The same criterion was used in connection with the companies which are part of the sectors that chose to reschedule the due dates of their payables using the general and extraordinary flexible conditions established by the BCRA for paying financial obligations. The estimated charge amounted to 150,654. As regards loans granted to individuals, the adjustment affected the financing to employees on payroll private company, self-employed workers and microentrepreneurs. These sectors were considered to be the most affected by dismissals, suspensions and loss in salary purchasing power, fall in sales and a reduction in activity levels resulting from compulsory lockdown. In these segments, an impairment in customer risk was estimated in the cases in which they opted to defer the settlement of their payables to the Bank (amounts owed in connection with credit cards and personal loans) by making use of the mandatory extensions and payment facilities provided by the BCRA in connection with outstanding financial payables during the pandemic. The adjustment made in connection with consumer loans amounted to 3,083,342 as of December 31, 2020. This adjustment plus the recorded amount for commercial loans amounted to 3,679,382. Portfolio quality The table below shows the analysis by aging of performing loans in arrears (in days):
12/31/2020 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
Portfolio Type |  | Delinquent, performing (in days) |
| 0 to 31 |  |  | From 32 to 90 |  |  | From 91 to 180 |  |  | From 181 to 360 |  |  | Over 360 |
Commercial loans |  |  | 99.5 | % |  |  | 0.5 | % |  |  | 0.0 | % |  |  | 0.0 | % |  |  | 0.0 | %
Comparable loans |  |  | 99.8 | % |  |  | 0.2 | % |  |  | 0.0 | % |  |  | 0.0 | % |  |  | 0.0 | %
Consumer loans |  |  | 99.5 | % |  |  | 0.5 | % |  |  | 0.0 | % |  |  | 0.0 | % |  |  | 0.0 | %
Total |  |  | 99.6 | % |  |  | 0.4 | % |  |  | 0.0 | % |  |  | 0.0 | % |  |  | 0.0 | %
12/31/2019 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
Portfolio Type |  | Delinquent, performing (in days) |
| 0 to 31 |  |  | From 32 to 90 |  |  | From 91 to 180 |  |  | From 181 to 360 |  |  | Over 360 |
Commercial loans |  |  | 99.2 | % |  |  | 0.8 | % |  |  | 0.0 | % |  |  | 0.0 | % |  |  | 0.0 | %
Comparable loans |  |  | 99.9 | % |  |  | 0.1 | % |  |  | 0.0 | % |  |  | 0.0 | % |  |  | 0.0 | %
Consumer loans |  |  | 100.0 | % |  |  | 0.0 | % |  |  | 0.0 | % |  |  | 0.0 | % |  |  | 0.0 | %
Total |  |  | 99.6 | % |  |  | 0.4 | % |  |  | 0.0 | % |  |  | 0.0 | % |  |  | 0.0 | %
Summary of Risk Concentration by Industry for the Components of the Statement of Financial Position | The following table shows the loans and other financing portfolio under credit risk by industry sector, classified by risk stage and identifying the expected loss calculated under individual or collective basis:
|  | 1 |  |  | 2 |  |  | 3 |  |  | 12/31/2020 |
|  | Collective |  |  | Individual |  |  | Collective |  |  | Individual |
Loans and other financing |  |  | 180,456,655 |  |  |  | 68,333,255 |  |  |  | 11,133,013 |  |  |  | 4,396,524 |  |  |  | 3,029,870 |  |  |  | 267,349,317 |
Non-financial public sector |  |  | 13,230 |  |  |  | 3,601,297 |  |  |  | 175 |  |  |  |  |  |  |  | 103 |  |  |  | 3,614,805 |
Other financial entities |  |  | 23 |  |  |  | 1,839,235 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1,839,258 |
Non-financial private sector |  |  | 180,443,402 |  |  |  | 62,892,723 |  |  |  | 11,132,838 |  |  |  | 4,396,524 |  |  |  | 3,029,767 |  |  |  | 261,895,254 |
Individuals |  |  | 114,240,780 |  |  |  | 881,453 |  |  |  | 6,217,494 |  |  |  |  |  |  |  | 685,859 |  |  |  | 122,025,586 |
Manufacturing Industry |  |  | 10,262,036 |  |  |  | 14,025,285 |  |  |  | 679,770 |  |  |  | 1,526,516 |  |  |  | 498,780 |  |  |  | 26,992,387 |
Agricultural and cattle industry |  |  | 14,415,093 |  |  |  | 6,741,231 |  |  |  | 966,605 |  |  |  | 2,759,232 |  |  |  | 435,379 |  |  |  | 25,317,540 |
Services |  |  | 22,280,971 |  |  |  | 11,185,975 |  |  |  | 1,815,627 |  |  |  | 110,206 |  |  |  | 107,590 |  |  |  | 35,500,369 |
Commercial activities |  |  | 13,244,682 |  |  |  | 9,222,944 |  |  |  | 1,001,929 |  |  |  | 570 |  |  |  | 301,854 |  |  |  | 23,771,979 |
Exploration of mines and quarries |  |  | 653,112 |  |  |  | 14,544,611 |  |  |  | 35,095 |  |  |  |  |  |  |  | 873,558 |  |  |  | 16,106,376 |
Financial intermediation |  |  | 1,038,512 |  |  |  | 3,731,946 |  |  |  | 32,755 |  |  |  |  |  |  |  | 5,648 |  |  |  | 4,808,861 |
Construction activities |  |  | 3,055,656 |  |  |  | 1,444,030 |  |  |  | 291,532 |  |  |  |  |  |  |  | 114,440 |  |  |  | 4,905,658 |
Electricity supply and gas |  |  | 155,514 |  |  |  | 1,115,248 |  |  |  | 8,092 |  |  |  |  |  |  |  | 179 |  |  |  | 1,279,033 |
Public administration |  |  | 1,037,333 |  |  |  |  |  |  |  | 82,856 |  |  |  |  |  |  |  | 6,207 |  |  |  | 1,126,396 |
Water supply and public sanitation |  |  | 59,713 |  |  |  |  |  |  |  | 1083 |  |  |  |  |  |  |  | 273 |  |  |  | 61,069 |
|  | 1 |  |  | 2 |  |  | 3 |  |  | 12/31/2019 |
|  | Collective |  |  | Individual |  |  | Collective |  |  | Individual |
Loans and other financing |  |  | 152,543,931 |  |  |  | 128,020,746 |  |  |  | 17,511,125 |  |  |  | 4,284,909 |  |  |  | 5,272,831 |  |  |  | 307,633,542 |
Non-financial public sector |  |  | 8,573 |  |  |  | 8,773,060 |  |  |  | 221 |  |  |  |  |  |  |  | 94 |  |  |  | 8,781,948 |
Other financial entities |  |  | 246 |  |  |  | 5,417,881 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5,418,127 |
Non-financial private sector |  |  | 152,535,112 |  |  |  | 113,829,805 |  |  |  | 17,510,904 |  |  |  | 4,284,909 |  |  |  | 5,272,737 |  |  |  | 293,433,467 |
Individuals |  |  | 117,874,202 |  |  |  | 511,834 |  |  |  | 9,172,222 |  |  |  |  |  |  |  | 1,980,256 |  |  |  | 129,538,514 |
Manufacturing Industry |  |  | 4,722,054 |  |  |  | 46,359,585 |  |  |  | 1,244,104 |  |  |  | 843,873 |  |  |  | 1,624,661 |  |  |  | 54,794,277 |
Agricultural and cattle industry |  |  | 7,696,443 |  |  |  | 11,045,886 |  |  |  | 2,857,436 |  |  |  | 3,165,627 |  |  |  | 554,555 |  |  |  | 25,319,947 |
Services |  |  | 13,205,385 |  |  |  | 13,175,749 |  |  |  | 2,069,526 |  |  |  | 72,040 |  |  |  | 346,332 |  |  |  | 28,869,032 |
Commercial activities |  |  | 5,248,612 |  |  |  | 13,123,381 |  |  |  | 1,420,453 |  |  |  | 199,317 |  |  |  | 567,853 |  |  |  | 20,559,616 |
Exploration of mines and quarries |  |  | 229,146 |  |  |  | 20,069,007 |  |  |  | 66,215 |  |  |  |  |  |  |  | 11,854 |  |  |  | 20,376,222 |
Financial intermediation |  |  | 930,240 |  |  |  | 3,840,710 |  |  |  | 83,338 |  |  |  |  |  |  |  | 18,248 |  |  |  | 4,872,536 |
Construction activities |  |  | 1,385,661 |  |  |  | 2,241,773 |  |  |  | 456,169 |  |  |  | 4,052 |  |  |  | 152,667 |  |  |  | 4,240,322 |
Electricity supply and gas |  |  | 100,044 |  |  |  | 3,435,177 |  |  |  | 9,827 |  |  |  |  |  |  |  | 1,483 |  |  |  | 3,546,531 |
Public administration |  |  | 1,103,771 |  |  |  | 26,703 |  |  |  | 128,161 |  |  |  |  |  |  |  | 14,720 |  |  |  | 1,273,355 |
Water supply and public sanitation |  |  | 39,554 |  |  |  |  |  |  |  | 3,453 |  |  |  |  |  |  |  | 108 |  |  |  | 43,115 |
Summary of Collateral and Other Credit Improvements | The following tables show the amounts of guarantees received for the entire portfolio and for the portfolio in Stage 3 as of December 31, 2020.
Class of financial instrument |  | Maximum exposure to credit risk |  |  | Fair value of collateral |  |  | Total collateral |  |  | Net exposure |  |  | Associated ECL |
| Pledges on time deposits |  |  | Deferred payment checks |  |  | Mortgage on real property |  |  | Pledges on vehicles and machinery |  |  | Pledges on personal property |  |  | Other |
Loans and other financing |  |  | 267,349,317 |  |  |  | 797,460 |  |  |  | 6,546,693 |  |  |  | 23,996,519 |  |  |  | 4,124,485 |  |  |  | 1,667,100 |  |  |  | 47,062,080 |  |  |  | 84,194,337 |  |  |  | 183,154,980 |  |  |  | 9,928,122 |
Loans commitment |  |  | 97,910,338 |  |  |  | 1,305 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 279,240 |  |  |  | 280,545 |  |  |  | 97,629,793 |  |  |  | 23,200 |
Other financial assets |  |  | 18,905,219 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 18,905,219 |  |  |  | 18,929 |
Other debt Securities at amortized cost |  |  | 31,119,261 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 31,119,261 |  |  |  | 5,472 |
Other debt securities at fair value through OCI |  |  | 178,005,144 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 178,005,144 |  |  |  | 5,964 |
Total |  |  | 593,289,279 |  |  |  | 798,765 |  |  |  | 6,546,693 |  |  |  | 23,996,519 |  |  |  | 4,124,485 |  |  |  | 1,667,100 |  |  |  | 47,341,320 |  |  |  | 84,474,882 |  |  |  | 508,814,397 |  |  |  | 9,981,687 |
Class of financial instrument |  | Maximum exposure to credit risk |  |  | Fair value collateral |  |  | Total collateral |  |  | Net exposure |  |  | Associated ECL |
| Deferred payment checks |  |  | Mortgage on real property |  |  | Pledges on vehicles and machinery |  |  | Pledges on personal property |  |  | Other |
Loans and other financing |  |  | 3,029,870 |  |  |  | 1,064 |  |  |  | 709,038 |  |  |  | 935,558 |  |  |  | 65,485 |  |  |  | 270,083 |  |  |  | 1,981,228 |  |  |  | 1,048,642 |  |  |  | 1,658,115 |
Total |  |  | 3,029,870 |  |  |  | 1,064 |  |  |  | 709,038 |  |  |  | 935,558 |  |  |  | 65,485 |  |  |  | 270,083 |  |  |  | 1,981,228 |  |  |  | 1,048,642 |  |  |  | 1,658,115 |
The following tables show the amounts of guarantees received for the entire portfolio and for the portfolio in Stage 3 as of December 31, 2019.
|  |  |  |  | Fair value of collateral |  |  |  |  |  |  |  |  |  |
Class of financial instrument |  | Maximum exposure to credit risk |  |  | Pledges on time deposits |  |  | Deferred payment checks |  |  | Mortgage on real property |  |  | Pledges on vehicles and machinery |  |  | Pledges on personal property |  |  | Other |  |  | Total collateral |  |  | Net exposure |  |  | Associated ECL |
Loans and other financing |  |  | 307,633,542 |  |  |  | 513,103 |  |  |  | 3,665,050 |  |  |  | 29,919,411 |  |  |  | 5,490,143 |  |  |  | 1,465,710 |  |  |  | 33,654,626 |  |  |  | 74,708,043 |  |  |  | 232,925,499 |  |  |  | 6,901,953 |
Loans commitment |  |  | 128,745,139 |  |  |  | 2,787 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 902,420 |  |  |  | 905,207 |  |  |  | 127,839,932 |  |  |  | 23,514 |
Other financial assets |  |  | 8,405,598 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 8,405,598 |  |  |  | 14,032 |
Other debt Securities at amortized cost |  |  | 24,067,911 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 24,067,911 |  |  |  | 63,701 |
Other debt securities at fair value through OCI |  |  | 63,824,735 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 63,824,735 |  |  |  | 286 |
Total |  |  | 532,676,925 |  |  |  | 515,890 |  |  |  | 3,665,050 |  |  |  | 29,919,411 |  |  |  | 5,490,143 |  |  |  | 1,465,710 |  |  |  | 34,557,046 |  |  |  | 75,613,250 |  |  |  | 457,063,675 |  |  |  | 7,003,486 |
Class of financial instrument |  | Maximum exposure to credit risk |  |  | Fair value collateral |  |  | Total collateral |  |  | Net exposure |  |  | Associated ECL |
| Deferred payment checks |  |  | Mortgage on real property |  |  | Pledges on vehicles and machinery |  |  | Pledges on personal property |  |  | Other |
Loans and other financing |  |  | 5,272,831 |  |  |  | 3,086 |  |  |  | 735,440 |  |  |  | 167,028 |  |  |  | 11,805 |  |  |  | 955,458 |  |  |  | 1,872,817 |  |  |  | 3,400,014 |  |  |  | 2,967,457 |
TOTAL |  |  | 5,272,831 |  |  |  | 3,086 |  |  |  | 735,440 |  |  |  | 167,028 |  |  |  | 11,805 |  |  |  | 955,458 |  |  |  | 1,872,817 |  |  |  | 3,400,014 |  |  |  | 2,967,457 |
Summary of Liquidity Ratios Arising from Dividing Net Liquid Assets, Cash and Cash Equivalents by Total Deposits | The following table shows the liquidity ratios during the fiscal years 2020 and 2019, which arise from dividing net liquid assets, made up of cash and cash equivalents, by total deposits.​​​​​​​
|  | 2020 |  |  | 2019 |
December, 31 |  |  | 86.39 | % |  |  | 57.75 | %
average |  |  | 81.57 | % |  |  | 61.24 | %
Max |  |  | 87.13 | % |  |  | 70.13 | %
Min |  |  | 71.49 | % |  |  | 51.73 | %
Summary of Contractual Cash Flows and Other Financing | The tables below summarize the maturity of the contractual cash flows of loans and other financing, before ECL, including interest and charges to be accrued until maturity of the contract as of December 31, 2020 and 2019:
|  |  |  |  | Remaining terms to maturity as of December 31, 2020 |  |  |  |
Item |  | Matured |  |  | Up to 1 month |  |  | Over 1 month and up to 3 months |  |  | Over 3 months and up to 6 months |  |  | Over 6 months and up to 12 months |  |  | Over 12 months and up to 24 months |  |  | Over 24 months |  |  | Total |
Non-financial government sector |  |  |  |  |  |  | 240,063 |  |  |  | 709,789 |  |  |  | 722,124 |  |  |  | 1,302,701 |  |  |  | 2,240,210 |  |  |  | 475,185 |  |  |  | 5,690,072 |
Financial sector |  |  |  |  |  |  | 73,164 |  |  |  | 366,107 |  |  |  | 542,488 |  |  |  | 336,233 |  |  |  | 1,005,712 |  |  |  |  |  |  |  | 2,323,704 |
Non-financial private sector and foreign residents |  |  | 1,309,651 |  |  |  | 94,565,908 |  |  |  | 30,753,008 |  |  |  | 41,943,648 |  |  |  | 49,509,992 |  |  |  | 47,067,374 |  |  |  | 76,591,919 |  |  |  | 341,741,500 |
Total |  |  | 1,309,651 |  |  |  | 94,879,135 |  |  |  | 31,828,904 |  |  |  | 43,208,260 |  |  |  | 51,148,926 |  |  |  | 50,313,296 |  |  |  | 77,067,104 |  |  |  | 349,755,276 |
|  |  |  |  | Remaining terms to maturity as of December 31, 2019 |  |  |  |
Item |  | Matured |  |  | Up to 1 month |  |  | Over 1 month and up to 3 months |  |  | Over 3 months and up to 6 months |  |  | Over 6 months and up to 12 months |  |  | Over 12 months and up to 24 months |  |  | Over 24 months |  |  | Total |
Non-financial government sector |  |  |  |  |  |  | 3,722,842 |  |  |  | 880,926 |  |  |  | 1,040,537 |  |  |  | 2,501,141 |  |  |  | 4,121,934 |  |  |  | 2,751,211 |  |  |  | 15,018,591 |
Financial sector |  |  |  |  |  |  | 2,498,632 |  |  |  | 3,004,100 |  |  |  | 642,334 |  |  |  | 859,600 |  |  |  | 1,215,730 |  |  |  | 7,443 |  |  |  | 8,227,839 |
Non-financial private sector and foreign residents |  |  | 4,936,146 |  |  |  | 123,475,851 |  |  |  | 36,775,492 |  |  |  | 33,009,946 |  |  |  | 41,228,086 |  |  |  | 59,457,916 |  |  |  | 91,735,995 |  |  |  | 390,619,432 |
Total |  |  | 4,936,146 |  |  |  | 129,697,325 |  |  |  | 40,660,518 |  |  |  | 34,692,817 |  |  |  | 44,588,827 |  |  |  | 64,795,580 |  |  |  | 94,494,649 |  |  |  | 413,865,862 |
Summary of Contractual Future Cash Flows of Financial Liabilities, Including Interest and Charges to be Accured | Additionally, the tables below disclose the maturity of the contractual future cash flows of financial liabilities, including interest and charges to be accrued until maturity of the contracts, as of December 31, 2020 and 2019:
|  | Remaining terms to maturity as of December 31, 2020 |  |  |  |
Item |  | Up to 1 month |  |  | Over 1 month and up to 3 months |  |  | Over 3 months and up to 6 months |  |  | Over 6 months and up to 12 months |  |  | Over 12 months and up to 24 months |  |  | Over 24 months |  |  | Total |
Deposits |  |  | 439,899,936 |  |  |  | 45,047,684 |  |  |  | 5,581,716 |  |  |  | 3,025,417 |  |  |  | 34,807 |  |  |  | 2,187 |  |  |  | 493,591,747 |
From the non-financial government sector |  |  | 67,873,301 |  |  |  | 5,558,974 |  |  |  | 901,974 |  |  |  | 2,128 |  |  |  |  |  |  |  |  |  |  |  | 74,336,377 |
From the financial sector |  |  | 696,415 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 696,415 |
From the non-financial private sector and foreign residents |  |  | 371,330,220 |  |  |  | 39,488,710 |  |  |  | 4,679,742 |  |  |  | 3,023,289 |  |  |  | 34,807 |  |  |  | 2,187 |  |  |  | 418,558,955 |
Derivative instruments |  |  | 42 |  |  |  | 188 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 230 |
Repo transactions |  |  | 620,389 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 620,389 |
Other financial institutions |  |  | 620,389 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 620,389 |
Other Financial Liabilities |  |  | 47,876,408 |  |  |  | 133,674 |  |  |  | 125,844 |  |  |  | 317,199 |  |  |  | 264,590 |  |  |  | 514,354 |  |  |  | 49,232,069 |
Financing received from the Central Bank of Argentina and other financial institutions |  |  | 419,441 |  |  |  | 199,471 |  |  |  | 204,074 |  |  |  | 80,703 |  |  |  | 40,093 |  |  |  | 5,724 |  |  |  | 949,506 |
Issued corporate bonds |  |  | 209,346 |  |  |  |  |  |  |  | 2,762,098 |  |  |  | 208,048 |  |  |  | 2,585,744 |  |  |  |  |  |  |  | 5,765,236 |
Subordinated corporate bonds |  |  |  |  |  |  |  |  |  |  | 1,135,957 |  |  |  | 1,135,958 |  |  |  | 2,498,433 |  |  |  | 43,651,732 |  |  |  | 48,422,080 |
Total |  |  | 489,025,562 |  |  |  | 45,381,017 |  |  |  | 9,809,689 |  |  |  | 4,767,325 |  |  |  | 5,423,667 |  |  |  | 44,173,997 |  |  |  | 598,581,257 |
|  | Remaining terms to maturity as of December 31, 2019 |  |  |  |
Item |  | Up to 1 month |  |  | Over 1 month and up to 3 months |  |  | Over 3 months and up to 6 months |  |  | Over 6 months and up to 12 months |  |  | Over 12 months and up to 24 months |  |  | Over 24 months |  |  | Total |
Deposits |  |  | 319,128,393 |  |  |  | 35,554,356 |  |  |  | 4,728,311 |  |  |  | 1,398,959 |  |  |  | 72,883 |  |  |  | 30,866 |  |  |  | 360,913,768 |
From the non-financial government sector |  |  | 22,974,090 |  |  |  | 1,059,457 |  |  |  | 58,210 |  |  |  | 2,832 |  |  |  |  |  |  |  |  |  |  |  | 24,094,589 |
From the financial sector |  |  | 427,702 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 427,702 |
From the non-financial private sector and foreign residents |  |  | 295,726,601 |  |  |  | 34,494,899 |  |  |  | 4,670,101 |  |  |  | 1,396,127 |  |  |  | 72,883 |  |  |  | 30,866 |  |  |  | 336,391,477 |
Derivative instruments |  |  | 399,076 |  |  |  | 464,440 |  |  |  | 183,040 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1,046,556 |
Repo transactions |  |  | 1,364,962 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1,364,962 |
Other financial institutions |  |  | 1,364,962 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1,364,962 |
Other Financial Liabilities |  |  | 28,687,673 |  |  |  | 133,406 |  |  |  | 141,649 |  |  |  | 227,982 |  |  |  | 442,189 |  |  |  | 585,057 |  |  |  | 30,217,956 |
Financing received from the Central Bank of Argentina and other financial institutions |  |  | 1,403,744 |  |  |  | 1,130,058 |  |  |  | 205,002 |  |  |  | 133,670 |  |  |  | 230,972 |  |  |  | 62,376 |  |  |  | 3,165,822 |
Issued corporate bonds |  |  | 436,031 |  |  |  |  |  |  |  | 701,097 |  |  |  | 1,006,731 |  |  |  | 4,579,987 |  |  |  | 4,206,065 |  |  |  | 10,929,911 |
Subordinated corporate bonds |  |  |  |  |  |  |  |  |  |  | 1,100,808 |  |  |  | 1,100,810 |  |  |  | 2,201,618 |  |  |  | 44,722,198 |  |  |  | 49,125,434 |
Total |  |  | 351,419,879 |  |  |  | 37,282,260 |  |  |  | 7,059,907 |  |  |  | 3,868,152 |  |  |  | 7,527,649 |  |  |  | 49,606,562 |  |  |  | 456,764,409 |
Summary of Bank's VaR by type of Risks | As of December 31, 2020 and 2019, the Bank’s economic capital by type of risk is as follows:
Economic capital (EC – in millions) |  | 12/31/2020 |  |  | 12/31/2019 |
Interest rate risk |  |  | 6,621 |  |  |  | 8,723 |
Currency Exchange rate risk |  |  | 1,727 |  |  |  | 2,486 |
Price risk |  |  | 5,198 |  |  |  | 192 |
Consumer [member] |
Statement [LineItems] |
Disclosure of internal credit grades | The following table discloses the risk levels score and rating arising from the Bank’s models:​​​​​​​
|  | 12/31/2020 |  |  | 12/31/2019 |
Category |  | Weighted PD |  |  | % Gross Carrying Amount |  |  | Weighted PD |  |  | % Gross Carrying Amount |
Performing |  |  | 2.32 | % |  |  | 96.17 | % |  |  | 2.60 | % |  |  | 95.45 | %
High grade |  |  | 1.13 | % |  |  | 76.20 | % |  |  | 1.25 | % |  |  | 76.40 | %
Standard grade |  |  | 4.79 | % |  |  | 12.64 | % |  |  | 4.83 | % |  |  | 8.23 | %
Sub-standard grade |  |  | 12.48 | % |  |  | 7.33 | % |  |  | 11.64 | % |  |  | 10.82 | %
Past due but not impaired |  |  | 33.24 | % |  |  | 2.70 | % |  |  | 32.13 | % |  |  | 2.84 | %
Impaired |  |  | 100.00 | % |  |  | 1.13 | % |  |  | 100.00 | % |  |  | 1.71 | %
Total |  |  |  |  |  |  | 100.00 | % |  |  |  |  |  |  | 100.00 | %

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