Methodology for measuring expected credit losses (ECL) according to IFRS 9
For a detailed description of the bank’s loss model, please see note 9 in the annual report for 2024.
Sparebanken Møre has developed an ECL model based on the Group’s IRB parameters and applies a three-stage approach when assessing ECL on loans to customers and financial guarantees in accordance with IFRS 9.
Stage 1: At initial recognition and if there’s no significant increase in credit risk, the commitment is classified in stage 1 with 12-months ECL.
Stage 2: If a significant increase in credit risk since initial recognition is identified, but without evidence of loss, the commitment is transferred to stage 2 with lifetime ECL measurement.
Stage 3: If the credit risk increases further, including evidence of loss, the commitment is transferred to stage 3 with lifetime ECL measurement. The commitment is considered to be credit-impaired. As opposed to stage 1 and 2, the effective interest rate in stage 3 is calculated on net impaired commitment (total commitment less expected credit loss) instead of gross commitment.
Staging is performed at account level and implies that two or more accounts held by the same customer can be placed in different stages. If a customer has one account in stage 3 (risk classes K, M or N), all of the customer’s accounts will migrate to stage 3.
Customers in risk class N have been subject to individual loss assessment with impairment. In connection with individual loss assessment, 3 scenarios based on calculation of the weighted present value of future cash flow after realisation of collateral are prepared. If the weighted present value of cash flow after realisation of collateral is positive, model-based loss provisions according to the ECL model is used.
An increase in credit risk reflects both customer-specific circumstances and development in relevant macro factors for the particular customer segment. The assessment of what is considered to be a significant increase in credit risk is based on a combination of quantitative and qualitative indicators.
Significant increase in credit risk
The assessment of whtether a significant increase in credit risk has occured is based on a combination of quantitative and qualitative indicators. A significant increase in credit risk has occured when one or more of the critearia below are present:
Quantitative criteria
A significant increase in credit risk is determined by comparing the PD at the reporting date with PD at initial recognition. If the actual PD is higher than initial PD, an assessment is made of whether the increase is significant.
Significant increase in credit risk since initial recognition is considered to have occurred when either
- PD has increased by 100 per cent or more and the increase in PD is more than 0.5 percentage points, or
- PD has increased by more than 2,0 percentage points
- The customer’s agreed payments are overdue by more than 30 days
The weighted, macro adjusted PD in year 1 is used for comparison with PD on initial recognition to determine whether the credit risk has increased significantly.
Qualitative criteria
In addition to the quantitative assessment of changes in the PD, a qualitative assessment is made to determine whether there has been a significant increase in credit risk, for example, if the commitment is subject to special monitoring.
Credit risk is always considered to have increased significantly if the customer has been granted forbearance measures, though it is not severe enough to be individually assessed in stage 3.
Positive migration in credit risk
A customer migrates from stage 2 to stage 1 if:
- The criteria for migration from stage 1 to stage 2 is no longer present, and
- this is satisfied for at least one subsequent month (total 2 months)
A customer migrates from stage 3 to stage 1 or stage 2 if the customer no longer meets the conditions for migration to stage 3.
Accounts that are not subject to the migration rules above are not expected to have significant change in credit risk and retain the stage from the previous month.
Scenarios
Three scenarios are developed: Best, Basis and Worst. For each of the scenarios, expected values of different parameters are given, for each of the next five years. The possibility for each of the scenarios to occur is also estimated. After five years, the scenarios are expected to converge to a long-term stable level.
Changes to PD as a result of scenarios, may also affect the staging.
Definition of default, credit-impaired and forbearance
The definition of default is similar to that used in the capital adequacy regulation.
A commitment is defined to be subject to forbearance (payment relief due to payment difficulties) if the bank agrees to changes in the terms and conditions as a result of the debtor having problems meeting payment obligations. Performing forbearance (not in default) is placed in stage 2 whereas non-performing (defaulted) forbearance is placed in stage 3.
Management override
Quarterly review meetings evaluate the basis for the accounting of ECL losses. If there are significant events that will affect an estimated loss which the model has not taken into account, relevant factors in the ECL model will be overridden. An assessment is made of the level of long-term PD and LGD in stage 2 and stage 3 under different scenarios, as well as an assessment of macro factors and weighting of scenarios.
Consequences of increased macroeconomic uncertainty and measurement of expected credit loss (ECL) for loans and guarantees
The bank’s loss provisions reflect expected credit loss (ECL) pursuant to IFRS 9. When assessing ECL, the relevant conditions at the time of reporting and expected economic developments are taken into account.
Uncertainty related to the US trade policy and its impact on the international economy persists. With ongoing negotiations, including between the US and China, there are prospects that the US tariffs may be lower than those presented by the President on 2 April. However, it is reasonable to assume that both the US and other countries will emerge from this with a more protectionist trade policy than before Donald Trump began his second term.
The effect of these developments is still unclear. The International Monetary Fund (IMF) has revised down its growth projections for the US, Europe, China and the world as a result of the ongoing events. The US economy is expected to be most negatively affected, and increased import tariffs are predicted to contribute to higher inflation. The conflict in the Middle East also constitutes a source of international uncertainty, which may affect the Norwegian economy through changes in oil and gas prices, among other things.
The Norwegian economy appears to have a solid starting point going into this period of uncertainty. Both GDP growth and household consumption picked up through the first half of the year. The upswing appears to be broadly rooted both between industries and geographical areas. According to Norges Bank’s regional network survey, Norwegian enterprises expect growth to remain high.
In summary, we are in a period of considerable international uncertainty. The conditions for world trade are constantly changing, complicating economic forecasts. The direct effects of higher import tariffs in the US on the Norwegian economy are estimated to be limited. At the same time, the Norwegian economy appears to have a robust starting point.
To sum up, there is still considerable uncertainty about future economic developments, both internationally and in Norway, and the weighting from Q1-2025 will be maintained.
The ECL as at 30.06.2025 is based on a scenario weighting with 70 per cent weight on the baseline scenario (normal development), 20 per cent weight on the worst-case scenario and 10 per cent weight on the best-case scenario.
Climate-related risk and calculating ECL
The bank is in the process of enhancing the ECL model to simulate ECL resulting from climate-related risk in various scenarios.
The ECL model has been used to simulate the financial consequences of climate-related risk for commercial property. Stress testing has been carried out on commitments in excess of a certain size related to the rental of commercial property. In the stress tests, PD (capacity to service debt) and LGD (collateral) were stressed in different scenarios.
The bank has continued to identify and map climate-related risk in the loan portfolio and various industries. In 2025, transition plans will be established to ensure that the bank’s loan portfolios become emission-free by 2050. Climate-related risk has been integrated into the Sustainability Report/CSRD reporting.
The ECL model must be expectation-oriented, and the bank is of the opinion that qualitative climate-related risk analyses currently involve a high degree of uncertainty, and these are thus not taken account of when assessing ECL, although the model is used for stress testing climate-related risk. The bank will strive to find good methods for implementing climate-related risk in the ECL model for the corporate portfolio.