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Measurement of Expected Credit Losses (ECL) | 12 Months Ended
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Dec. 31, 2022
Measurement of Expected Credit Loss [Abstract] |
Measurement of Expected Credit Losses (ECL) | 7. Measurement of Expected Credit Losses (ECL) The ECL of a financial instrument must reflect an unbiased estimate, the time value of money and a forward looking perspective (including the economic forecast). 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 ECL. Risk Parameters Adjusted by Macroeconomic Scenarios ECL must include forward-looking macroeconomic information. The Group uses the credit risk parameters PD, LGD and EAD in order to calculate the ECL for the credit portfolios. The Group’s 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 out of sample forecasting performance.
How economic scenarios are reflected in calculation of ECL Based on economic theory and analysis, the macroeconomic variables most directly relevant for explaining and forecasting the selected risk parameters are:
| • |  | The net income of families, corporates or public administrations.
| • |  | The payment amounts on the principal and interest on the outstanding loans.
The Group approximates these variables by using a proxy indicator from the set included of the macroeconomic scenarios provided by the economic research department. Only a single specific indicator can be used for each of the two variables and only key macroeconomic indicators should be chosen as the first option: a) the use of Real GDP Growth can be perceived as the only sufficient “factor” necessary to capture the influence of the entire macroeconomic scenario possibly relevant to internal PD; or b) the use of the most representative short-term interest rate or the exchange rate expressed in real terms. Real GDP growth is preferred 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 macroeconomic scenario generation. Multiple scenario approach under IFRS 9 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 team produces 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, the internal capital adequacy assessment process (ICAAP) and risk appetite framework, stress testing, etc. Additionally, the BBVA Research team produces 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 (GDP or interest rate or exchange rate), BBVA Research produces three scenarios. 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 approach of the Group consists of using the scenario that is the most likely scenario, which is the baseline scenario, consistent with the rest of internal processes (ICAAP, Budgeting) and then applying upside and downside scenarios by taking into account the weighted average of the ECL determined by each of the scenarios. It is important to note that in general, the effect of the adjustment for the application of multiple scenarios is expected to increase the ECL. It is possible to obtain an adjustment that does not have that effect whenever the correlation between macroeconomic scenarios and losses is linear; however, it is not expected that it will reduce the ECL. COVID-19 Impact During the pandemic-related lockdown, the BCRA and the government issued several communications and decrees, pursuant to which customers within the portfolio of non-card customers were allowed to defer their unpaid installments until April 2020, maturing at the end of the loan. The measure ceased in March 2021, so no further deferrals are applied. The table below summarizes the UVA (“Unidad de Valor Adquisitivo”, in Spanish ) indexed loan portfolio affected by the afore m entioned measure and the related impact on contractual cash flows:
|  | Balance as December 31, 2022 |  |  | Loss from changes in contractual cash flows recognized in Net Interest Income |
|  |  |  |  | December 31, 2021 |  |  | Variation |  |  | Inflation adjustment |  |  | December 31, 2022 |
UVA-indexed mortgage loans |  |  | 48,715,323 |  |  |  | 644,640 |  |  |  | 973,932 |  |  |  | (142,094 | ) |  |  | 1,476,478 |
UVA-indexed pledge loans |  |  | 996,002 |  |  |  | 11,670 |  |  |  | 18,067 |  |  |  | (3,698 | ) |  |  | 26,039 |
Balance |  |  |  |  |  |  | 656,310 |  |  |  | 991,999 |  |  |  | (145,792 | ) |  |  | 1,502,517 |
The ECL measurement model parameters were not affected. Credit quality ratios did not show deterioration as a result of the aid measures promoted by the national authorities. Given the pandemic and quarantine situation, no relevant impacts were recorded on ECL directly related to COVID 19.

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