24. Net allowances for expected credit losses

The allowance for expected credit losses is recognized in the financial statements in the following manner:

• Financial assets measured at amortized cost: the allowance reduces the gross carrying amount of the financial asset (adjusted for adjustments to the gross carrying amount for legal risk of mortgage loans in convertible currencies, statutory credit holidays and for potential reimbursements to customers for the expected early repayment of consumer and mortgage loans); changes in the allowances amount are recognised in the income statement;
• Off-balance sheet liabilities of a financial nature and financial guarantees: the allowance is presented as a provision under liabilities; changes in the provisions amount are recognized in the income statement;
• Financial instruments measured at fair value through other comprehensive income: the carrying amount of assets recognized at fair value is not additionally decreased by the allowances; however, each change in the measurement is divided into the impairment component, which is recognized in the income statement, and the component relating to other changes in the fair value measurement, which is recognized in other comprehensive income.

The Group reviews its loan portfolio for impairment at least quarterly. To determine whether an impairment should be recognised in the income statement, the Group assesses whether there is any data indicating a measurable reduction in the estimated future cash flows relating to the loan portfolio. The methodology and assumptions used to determine the estimated cash flow amounts and the periods over which they will occur are reviewed on a regular basis.

With regard to impairment, the Group applies the concept of expected losses.

The impairment model is applicable to financial assets that are not measured at fair value through profit or loss, comprising:

• debt financial instruments comprising credit exposures and securities;
• lease receivables;
• other financial assets;
• off-balance sheet financial and guarantee liabilities.

Impairment allowances for exposure reflect 12-month or lifetime expected credit losses on such exposures for a given financial asset.

The time horizon of an expected loss depends on whether a significant increase in credit risk occurred since the moment of initial recognition. Based on this criterion, financial assets are allocated to 3 stages:

• Stage 1 – exposures in which the credit risk is not significantly higher than upon initial recognition and no evidence of impairment is found;
• Stage 2 – exposures in which the credit risk is significantly higher than upon initial recognition, but no evidence of impairment is found;
• Stage 3 –assets in respect of which evidence of impairment is recognized, including assets granted or purchased with evidence of impairment recognized (upon being granted or purchased).

A significant increase in credit risk is verified according to the likeliness of default and its changes with respect to the date of originating the loan.

The Group uses a model based on a marginal PD calculation, i.e. the probability of default in a given month, to assess a significant increase in credit risk for mortgage exposures and other retail exposures. This probability depends on the time that has passed from originating the exposure. This enables reflecting the differences in credit quality that are typical of exposures to individuals over the lifetime of the exposure. The marginal PD curves were determined on the basis of historic data at the level of homogeneous portfolios, which are separated according to the type of product, the year of their origination, the loan currency and the credit quality at the time of origination. The marginal PD is attributed to individual exposures by scaling the curve at the level of the portfolio to the individual assessment of the exposure / customer using application models (using data from loan applications) and behavioural models. The Group identifies the premise of a significant increase in credit risk for a given exposure by comparing individual PD curves over the exposure horizon as at the date of initial recognition and as at the reporting date. Only the parts of the original and current PD curves which correspond to the period from the reporting date to the date of maturity of the exposure are compared as at each reporting date. The comparison is based on the average probability of default over the life of the loan in the period under review adjusted for current and forecast macroeconomic indicators.

The result of this comparison, referred to as α statistics, is referred to the threshold value above which an increase in credit risk is considered significant. The threshold value is determined on the basis of the historical relationship between the values of the α statistics and the default arising. In this process the following probabilities are minimized:

• classification into a set of credit exposures with a significant increase in the level of credit risk (based on the α statistic), for which no event of default took place during the audited period (type I error)
• non-classification into the set of credit exposures with a significant increase in the level of credit risk (based on the statistics) for which an event of default occurred during the audited period (type II error).

According to data as at the end of 2023, an increase in the PD parameter of at least 2.5 compared to the value at the time of its recognition in the Group’s accounting records in respect of mortgage exposures and an increase of at least 2.5 in respect of other retail exposures constitutes a premise of a significant deterioration in credit quality.

With respect to credit exposures for which the current risk of default does not exceed the level provided for in the price of the loan, the results of the comparison of the probability of default curves as at the date of initial recognition and as at the reporting date do not signify a significant increase in credit risk.

In order to assess the significant increase in credit risk for institutional customers the Group applies the model based on the Markov chains. Historical data is used to build matrices of probabilities of customers migrating between individual classes of risk that are determined on the basis of the Group’s rating and scoring models. These migrations are determined within homogeneous portfolios, classified using, among other things, customer and customer segment assessment methodologies.

An individual highest acceptable value of the probability of default is set for each category of risk and portfolio on the date of the initial recognition of the credit exposure, which, if exceeded, is identified as a significant increase in credit risk. This value is set on the basis of the average probability of default for categories of risk worse than that at initial recognition of the exposure, weighted by the probability of transition to those categories of risk in the given time horizon.

In accordance with the data as at the end of 2023, the minimum deterioration in the category of risk which constitutes a premise of a significant increase in credit risk compared to the current category of risk were as follows:

The Group uses all available qualitative and quantitative information to identify the remaining premises of a significant increase in credit risk, including:

• marking a credit exposure as POCI without any indication of impairment,
• restructuring measures introducing forbearance for a debtor in financial difficulties;
• delays in repayment of a material amount of principal or interest (understood as an amount exceeding PLN 400 for retail exposures or PLN 2,000 for other credit exposures and 1% of the debtor’s total cumulative loan exposure to the Bank and the other entities of the Bank’s Group) exceeding 30 days;
• identified early warning signals as part of the monitoring process, suggesting a material increase in credit risk (including changes in collateral, modifications of the terms of agreement with the customer, in particular relating to the schedule of loan utilization or repayment, reduction of the Bank’s exposure to the customer);
• significant increase in the LTV ratio;
• quarantine for Stage 2 exposures, which have not shown premises for impairment in the previous 3 months.
• filing for consumer bankruptcy by any of the joint borrowers;
• transfer of the credit exposure for management on a general basis by the Bank’s restructuring and debt collection units;
• use by the borrower of a mortgage loan from statutory support in loan repayment.

The premise for the impairment of a credit exposure is, in particular:

• delays in repayment of a material amount of principal or interest (understood as an amount exceeding PLN 400 for retail exposures or PLN 2,000 for other credit exposures and 1% of the debtor’s total cumulative loan exposure to the Bank and the other entities of the Bank’s Group) exceeding 90 days;
• a deterioration in the debtor’s economic and financial position during the lending period or a risk to the completion of the investment project financed, expressed by the classification into a rating class or risk category suggesting a material risk of default (rating H);
• the conclusion of a restructuring agreement or the application of relief in debt repayment, which is forced by economic or legal reasons arising from the customer’s financial difficulties (until the claim is recognized as remedied);
• filing a motion for the debtor’s bankruptcy, placing the debtor into liquidation or the opening of enforcement proceedings with respect to the debtor;
• declaration of consumer bankruptcy by any of the joint borrowers;
• information on death of all borrowers who are natural persons or entrepreneurs running individual business activity or a civil partnership (unless such business activity is continued by a successor);
• the occurrence of other events indicating the debtor’s inability to repay his total liability under the agreement.

In accordance with Regulation (EU) No 575/2013 of the European Parliament and of the Council on prudential requirements for credit institutions and investment firms (“CRR”), the

Group defines a state of default if it assesses that the debtor is unable to repay the loan liability without resorting to exercising the collateral or if the exposure is overdue more than 90 days. The premises of default are identical to the premises for impairment of the exposure.

Both the process of assessing a material increase in credit risk and the process of calculating the expected loss are conducted monthly at the level of individual exposures. They use a dedicated computing environment that allows for the distribution of the results to the Group’s internal units.

The Group has separated the portfolio of financial assets with low credit risk by classifying financial instruments for which the average long-term default rate does not exceed the probability of default specified by the rating agency for the worst class investment rating. This portfolio includes, in particular, exposures to banks, governments, local government entities and housing cooperatives and communities.

The model for the calculation of the expected credit loss is based on applying detailed segmentation to the credit portfolio, taking into account the following characteristics at product and customer level:

• type of credit product;
• currency of the product;
• year of granting;
• assessment of risk of the customer’s default;
• the customer’s business segment;
• method of assessing the customer risk.

The Group calculates expected credit losses on an individual and on a portfolio basis.

The individual basis is used in respect of individually significant exposures. The expected credit loss from the exposure is determined as the difference between its gross carrying amount (in the case of an off-balance sheet credit exposure – the value of its balance sheet equivalent) and the present value of the expected future cash flows, established by taking into account the possible scenarios regarding the performance of the contract and the management of credit exposure, weighted by the probability of their realization.

The portfolio method is applied to exposures that are not individually significant and in the event of a failure to identify premises of impairment.

In the portfolio method, the expected loss is calculated as the product of the credit risk parameters: the probability of default (PD), the loss given default (LGD) and the value of the exposure at default (EAD); each of these parameters assumes the form of a vector representing the number of months covering the horizon of estimation of the credit loss.

The Group sets this horizon for retail exposures without a repayment schedule on the basis of behavioural data from historical observations. The loss expected both in the entire duration of the exposure and in a period of 12 months is the sum of expected losses in the individual periods discounted using the effective interest rate. The Group adjusts the parameter specifying the level of exposure at the time of default by the future repayments arising from the schedule and potential overpayments and underpayments to specify the value of the asset at the time of default in a given period.

In the calculations of expected credit losses the estimates concerning future macroeconomic conditions are taken into account. In terms of portfolio analysis, the impact of macroeconomic scenarios is taken into account in the amount of the individual risk parameters. The methodology for calculating the risk parameters includes the study of the dependencies of these parameters on the macroeconomic conditions based on historical data. Three macroeconomic scenarios based on the Bank’s own projections are used for calculating the expected loss:

• a baseline scenario with a probability of 75%
• and two alternative scenarios, with a probability of 20% and 5%, respectively.

The scope of the projected indicators includes:

• GDP growth rate,
• unemployment rate,
• WIBOR 3M rate,
• SARON 3M rate,
• CHF/PLN exchange rate,
• property price index
• NBP reference rate.

The final expected loss is the weighted average probability of scenarios from expected losses corresponding to individual scenarios.

The Group ensures compliance of the macroeconomic scenarios used for the calculation of the risk parameters with macroeconomic scenarios used for the credit risk budgeting processes.

The baseline scenario uses the base macroeconomic projections. The projections are prepared on the basis of the quantitative models, taking into account adjustments for the presence of one-off events.

The extreme scenarios apply to cases of so-called internal shock, as a result of which the so-called external variables (foreign interest rates) do not change with respect to the baseline scenario. The extreme scenarios are developed on the basis of a statistical and econometric analysis, i.e. they do not reflect the events described, but the projected path. Two scenarios are identified, optimistic and pessimistic.

The share of the scenarios for the GDP path (GDP growth rate) that falls between the optimistic and the pessimistic scenario is referred to as the probability of the baseline scenario. Such an assumption is used to project GDP growth, using a potential rate of growth of the Polish economy that varies over time, calculated with the use of quarterly data provided by the Central Statistical Office. The values of other macroeconomic variables used in the scenarios (rate of unemployment, property price index) are estimated after the extreme paths of GDP growth are defined.

The rate of unemployment is calculated on the basis of the quantified dependence on the difference between GDP growth and the potential rate of economic growth. The result is adjusted for significant structural changes taking place in the Polish economy, which are not encompassed by the quantitative model, in particular:

• the ageing of the Polish population (and the appearance of unsatisfied demand for labour, which will limit the scale of increase in the rate of unemployment in a situation in an economic downturn);
• the Polish labour market is nearing full employment (restrictions of supply mean that there is increasingly less space for a further decline in the rate of unemployment);
• the inflow of immigrants (only partly included in the official statistics).

The level of the property price index is set on the basis of changes in GDP, taking into account the conditions of supply and demand on the market based on the data and trends presented by the NBP in the publication “Information on housing prices and the situation on the residential and commercial property market in Poland” and the Bank’s own analyses.

The projections for deposit rates are mainly prepared on the basis of assumptions regarding central bank interest rates.

The CHF/PLN exchange rate is a cross rate of the EUR/PLN and EUR/CHF exchange rates. Its projections are a combination of projections for these two rates. The EUR/PLN and EUR/CHF projections are prepared on the basis of a macroeconomic analysis (current and historical) based on econometric methods, as well as on a technical analysis of the financial markets.

In 2023, the macroeconomic model incorporates factors to reflect current domestic and global events: the impact of the current macroeconomic situation (high inflation) on customers’ ability to settle their obligations, as well as the impact of Russia’s invasion of Ukraine on fuel prices and, consequently, on the health of companies. Additional factors in the model include:

• taking into account the high level of interest rates on the quality of the credit portfolio and increases in energy prices on the situation of enterprises, using the historically observed portfolio quality dependency on the level of interest rates and energy prices,
• consideration of the effect of exchange rate volatility on the quality of the foreign currency housing loan portfolio, as a result of the escalation of hostilities in Ukraine.

In addition, due to the significant influx of refugees following Russia’s invasion of Ukraine and the uncertainty of its impact on the labour market, the model in all portfolios does not take into account a decrease in unemployment as a factor improving the quality of the loan portfolio.

The applied approach to the impact of macroeconomic forecasts on risk parameters describes the situation simultaneously in all branches of the economy and may not take into account the problems of individual industries caused by the pandemic, which is why the Group has conducted additional analyses of the loan portfolio, including leasing portfolio. These analyses, carried out by risk experts, mainly included an assessment of the impact of specific macroeconomic conditions not taken into account in the portfolio approach and helped identify clients and industries particularly affected by the current economic situation.

For the loan and advances portfolio, this is particularly the case in the construction, automotive, office and retail rental sectors, organic fertiliser production and energy-intensive industries. Exposures with highest PD values (D rating or worse) belonging to identified industries were marked with the indication of „significant increase in credit risk” and covered by increased write-downs. In 2023, as a result of the above measures, the Group increased the write-downs for expected credit losses by PLN 272 million, which represents approx. 16% of the value of write-downs on the entire portfolio of economic loans classified as Stage 2.

In the case of the portfolio of finance lease receivables, this relates to the following sectors: transport, construction, hotel, finishing, furniture, automotive, paper, agriculture, fertiliser and steel. For these sectors, the Group divided the portfolio into the portfolio of customers with a higher level of risk and the portfolio of standard customers, and for both these groups introduced adjustments to the model PD to increase the coverage of the write-down on this portfolio, with standard clients being lower than for customers with increased risk levels. The most numerous of the identified groups include the transport sector, which accounts for 24% of the healthy portfolio (of which 3% of the healthy portfolio is at a higher risk level), the remaining industries constitute 24% of a healthy portfolio. The introduced changes resulted in an increase in allowances by PLN 9 million for the steel and fertilizer industry in 2023, and by PLN 12 million for the agricultural sector. The industry add-ons applied in 2022 resulted in an increase in valuation allowances by PLN 11 million for the transport industry and PLN 27 million for other industries.

The tables below present projections of the key macroeconomic parameters and their assumed probabilities of materialization.

The table below presents the estimated sensitivity of the level of allowances for expected credit losses to macroeconomic conditions, calculated as the change in the level of allowances for expected credit losses in respect of not impaired exposures resulting from the materialization of particular macroeconomic scenarios as at 31 December 2023 and 31 December 2022.

The table below presents the estimated sensitivity of the level of allowances for expected losses as a result of scenarios of deterioration or improvement in risk parameters as at 31 December 2023 and 31 December 2022.