XML 16 R8.htm IDEA: XBRL DOCUMENT
v3.25.2

Risk management | 6 Months Ended
--- | ---
Jun. 30, 2025
Risk Management [Abstract] |
Risk management |
Basis of disclosures (*) This risk management section contains an update of information relating to the nature and the extent of the risks arising from financial instruments as disclosed in the 2024 ING Group consolidated financial statements as included in the 2024 Annual Report. These disclosures are an integral part of ING Group condensed consolidated interim financial statements and are indicated by the symbol (*). Chapters, paragraphs, graphs or tables within this risk management section that are indicated with this symbol in the respective headings or table header are considered to be an integral part of the condensed consolidated interim financial statements. This risk management section also includes additional disclosures beyond those required by IFRS standards, such as certain legal and regulatory disclosures. Not all information in this section can be reconciled back to the primary financial statements and corresponding notes, as it has been prepared using risk data that differs to the accounting basis of measurement.
Credit risk Loan loss provisioning (*) ING recognises loss allowances based on the expected credit loss (ECL) model of IFRS 9, which is designed to be forward-looking. The IFRS 9 impairment requirements are applicable to on-balance-sheet financial assets measured at amortised cost or fair value through other comprehensive income (FVOCI), such as loans, debt securities and lease receivables, as well as off-balance-sheet items such as undrawn loan commitments, financial- and non-financial guarantees issued. ING distinguishes between two types of calculation methods for credit loss allowances: •Collective 12-month ECL (Stage 1) and collective lifetime ECL (Stage 2) for portfolios of financial instruments, as well as collective lifetime ECL for credit-impaired exposures (Stage 3) below €1 million; •Individual lifetime ECL for credit-impaired (Stage 3) financial instruments with exposures above €1 million. Climate and environmental risks in IFRS 9 models (*) Climate risk drivers (physical and transition risks) can reduce the ability of businesses and households to fulfil their obligations due on existing lending contracts. These may also lead to the depreciation/erosion of collateral values, which would translate into higher credit losses and loan-to-value ratios in the lending portfolio of ING. ING has devised a strategy for incorporation of climate risk factors into IFRS 9 models, which considers short, medium, and long-term plans. As part of that strategy, ING has introduced a management adjustment to ECL models for business clients in 2024, to specifically cover for the medium- to long-term transition risk on high greenhouse gas-emitting sectors in loan loss provisioning. This management adjustment is continued as at 30 June 2025. Additionally, where climate and environmental factors have impacted the economy in the recent past or present, these impacts are implicitly embedded in ING’s IFRS 9 ECL models through the projected macroeconomic indicators (e.g. indirectly via GDP growth and unemployment rates). We note, however, that our ECL models are primarily sensitive to the short-term economic outlook as we use a three-year time horizon for macroeconomic outlook, for the long term a mean reversion approach is applied. With regard to our evaluation of specific climate-related matters, particularly physical risk events that have already occurred (e.g. floods, stranded assets etc.), the impact of such events is individually assessed in the calculation of Stage 3 individual provisions, collective SICR or management adjustments to ECL models. For example, we consider whether affected assets have suffered from a significant increase in credit risk (or are credit impaired) and whether the ECL is appropriate. For more details, see ‘Management adjustments applied this reporting period’. Going forward, ING aims to continue to improve on climate risk data, which will enable us to further embed climate risks into the IFRS 9 ECL models. Portfolio quality and concentration (*) The table below describes the portfolio composition over the different IFRS 9 stages and rating classes. The Stage 1 portfolio represents 91.7 percent (2024: 91.1 percent) of the total gross carrying amounts, mainly composed of investment grade, while Stage 2 makes up 7.1 percent (2024: 7.6 percent) and Stage 3 makes up 1.2 percent (2024: 1.3 percent) of the total gross carrying amounts, respectively.
Gross carrying amount per IFRS 9 stage and rating class (*)1
in EUR million | 12-month ECL (Stage 1) | Lifetime ECL not credit impaired (Stage 2) | Lifetime ECL credit impaired (Stage 3) | Total
Rating class | Gross carrying amount | Provisions | Gross carrying amount | Provisions | Gross carrying amount | Provisions | Gross carrying amount | Provisions
|  | 30 June 2025 | 31 December 2024 | 30 June 2025 | 31 December 2024 | 30 June 2025 | 31 December 2024 | 30 June 2025 | 31 December 2024 | 30 June 2025 | 31 December 2024 | 30 June 2025 | 31 December 2024 | 30 June 2025 | 31 December 2024 | 30 June 2025 | 31 December 2024
Investment grade | 1 (AAA) | 89,188 |  | 79,076 |  | 1 |  | 1 |  | 191 |  | 281 |  |  |  |  |  |  |  |  |  |  |  |  |  | 89,379 |  | 79,357 |  | 1 |  | 1 |
2-4 (AA) | 145,150 |  | 140,671 |  | 12 |  | 10 |  | 1,894 |  | 1,579 |  | 1 |  | 1 |  |  |  |  |  |  |  |  |  | 147,043 |  | 142,250 |  | 13 |  | 11 |
5-7 (A) | 265,263 |  | 244,241 |  | 27 |  | 22 |  | 6,323 |  | 6,908 |  | 8 |  | 8 |  |  |  |  |  |  |  |  |  | 271,586 |  | 251,149 |  | 34 |  | 29 |
8-10 (BBB) | 317,743 |  | 310,324 |  | 66 |  | 55 |  | 20,122 |  | 24,683 |  | 47 |  | 55 |  |  |  |  |  |  |  |  |  | 337,865 |  | 335,008 |  | 113 |  | 110 |
Non-investment grade | 11-13 (BB) | 159,671 |  | 154,348 |  | 197 |  | 190 |  | 18,158 |  | 18,479 |  | 100 |  | 91 |  |  |  |  |  |  |  |  |  | 177,828 |  | 172,827 |  | 297 |  | 281 |
14-16 (B) | 25,725 |  | 25,377 |  | 128 |  | 124 |  | 19,569 |  | 17,433 |  | 399 |  | 366 |  |  |  |  |  |  |  |  |  | 45,294 |  | 42,811 |  | 527 |  | 490 |
17 (CCC) | 666 |  | 905 |  | 8 |  | 8 |  | 4,637 |  | 3,992 |  | 214 |  | 173 |  |  |  |  |  |  |  |  |  | 5,304 |  | 4,897 |  | 222 |  | 181 |
Performing Restructuring | 18 (CC) |  |  |  |  |  |  |  |  | 4,471 |  | 4,059 |  | 268 |  | 233 |  |  |  |  |  |  |  |  |  | 4,471 |  | 4,060 |  | 268 |  | 233 |
19 (C) |  |  |  |  |  |  |  |  | 2,232 |  | 2,474 |  | 210 |  | 203 |  |  |  |  |  |  |  |  |  | 2,232 |  | 2,474 |  | 210 |  | 203 |
Non-performing loans | 20-22 (D) |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 12,932 |  | 13,742 |  | 4,259 |  | 4,509 |  | 12,932 |  | 13,742 |  | 4,259 |  | 4,509 |
Total | 1,003,405 |  | 954,943 |  | 439 |  | 409 |  | 77,596 |  | 79,888 |  | 1,247 |  | 1,130 |  | 12,932 |  | 13,742 |  | 4,259 |  | 4,509 |  | 1,093,934 |  | 1,048,574 |  | 5,945 |  | 6,049 |
1 Stage 3 lifetime credit impaired provision includes €21 million (31 December 2024: €21 million) on purchased or originated credit impaired. Changes in gross carrying amounts and loan loss provisions (*) The table below provides a reconciliation by stage of the gross carrying amount and allowances for loans and advances to banks and customers, including loan commitments and financial guarantees. The transfers of financial instruments represent the impact of stage transfers upon the gross carrying/nominal amount and associated allowance for ECL. This includes the net-remeasurement of ECL arising from stage transfers, for example, moving from a 12-month (Stage 1) to a lifetime (Stage 2) ECL measurement basis. The net-remeasurement line represents the changes in provisions for facilities that remain in the same stage. Please note the following comments with respect to the movements observed in the table below: •Stage 3 gross carrying amount decreased by €0.8 billion from €13.7 billion as at 31 December 2024 to €12.9 billion as at 30 June 2025, mainly as a result of €1.5 billion derecognitions and repayments and €0.8 billion write-offs and disposals, which is offset by an increase of €1.5 billion net inflow into NPL (credit impaired) in the first six months of 2025. Following the decrease in carrying amount, Stage 3 provisions decreased by €0.3 billion. •Stage 2 gross carrying amounts decreased by €2.3 billion from €79.9 billion as at 31 December 2024 to €77.6 billion as at 30 June 2025, largely driven by a decrease of €10.5 billion exposure due to derecognised financial assets (including sales) and repayments, and €0.6 billion exposure moving to stage 3. This was offset by €7.7 billion net transfers moving from Stage 1 into Stage 2, including the impact of changes in risk drivers (driven by updated macro-economic forecasts and the impact of new early warning signals) and model redevelopments mainly for Wholesale Banking. Other includes an increase of €1.1 billion related to other commitments. Stage 2 provisions increased by €0.1 billion to €1.2 billion as of 30 June 2025.
Changes in gross carrying amounts and loan loss provisions (*)1, 2
in EUR million | 12-month ECL (Stage 1) | Lifetime ECL not credit impaired (Stage 2) | Lifetime ECL credit impaired (Stage 3) | Total |  | 12-month ECL (Stage 1) | Lifetime ECL not credit impaired (Stage 2) | Lifetime ECL credit impaired (Stage 3) | Total
| Gross carrying amount | Provisions | Gross carrying amount | Provisions | Gross carrying amount | Provisions | Gross carrying amount | Provisions |  | Gross carrying amount | Provisions | Gross carrying amount | Provisions | Gross carrying amount | Provisions | Gross carrying amount | Provisions
| 30 June 2025 |  | 31 December 2024
Opening balance as at 1 January | 954,943 | 409 | 79,888 | 1,130 | 13,742 | 4,509 | 1,048,574 | 6,049 |  | 937,633 | 517 | 75,454 | 1,435 | 11,956 | 3,887 | 1,025,043 | 5,839
Transfer into 12-month ECL (Stage 1) | 16,783 | 15 | -16,655 | -132 | -128 | -23 | 0 | -141 |  | 20,486 | 22 | -20,236 | -195 | -249 | -34 | 0 | -207
Transfer into lifetime ECL not credit impaired (Stage 2) | -24,349 | -36 | 25,053 | 358 | -703 | -72 | 0 | 250 |  | -43,155 | -49 | 43,900 | 429 | -745 | -96 | 0 | 285
Transfer into lifetime ECL credit impaired (Stage 3) | -980 | -7 | -1,305 | -107 | 2,286 | 562 | 0 | 448 |  | -2,980 | -18 | -2,856 | -235 | 5,836 | 1,802 | 0 | 1,548
Net remeasurement of loan loss provisions | 0 | -7 | 0 | 85 | 0 | 137 |  | 215 |  | 0 | -181 | 0 | -137 | 0 | 185 | 0 | -133
New financial assets originated or purchased | 134,966 | 119 | 0 | 0 | 0 | 1 | 134,966 | 120 |  | 212,516 | 192 | 0 | 0 | 0 | 0 | 212,516 | 192
Financial assets that have been derecognised | -65,485 | -40 | -6,435 | -84 | -554 | -121 | -72,474 | -245 |  | -126,858 | -76 | -11,840 | -153 | -1,450 | -257 | -140,148 | -485
Net drawdowns and repayments | -28,119 |  | -3,973 |  | -912 |  | -33,005 |  |  | -41,763 | 0 | -4,393 | 0 | -309 | 0 | -46,465 | 0
Changes in models/risk parameters | 0 | -6 | 0 | 17 | 0 | -47 | 0 | -35 |  | 0 | 8 | 0 | -6 | 0 | -22 | 0 | -20
Increase in loan loss provisions |  | 39 |  | 137 |  | 436 |  | 612 |  |  | -102 |  | -297 |  | 1,578 |  | 1,179
Write-offs | 0 | 0 | 0 | 0 | -556 | -556 | -556 | -556 |  | 0 | 0 | 0 | 0 | -1,017 | -1,017 | -1,017 | -1,017
Disposals | -510 | -2 | -68 | -2 | -282 | -125 | -860 | -129 |  | -935 | -1 | -141 | -8 | -279 | -215 | -1,355 | -225
Recoveries of amounts previously written off |  | 0 |  | 0 |  | 30 |  | 30 |  |  | 0 |  | 0 |  | 69 |  | 69
Foreign exchange and other movements | 16,157 | -7 | 1,092 | -18 | 40 | -35 | 17,288 | -60 |  | 0 | -5 | 0 | 0 | 0 | 208 | 0 | 203
Closing balance | 1,003,405 | 439 | 77,596 | 1,247 | 12,932 | 4,259 | 1,093,934 | 5,945 |  | 954,943 | 409 | 79,888 | 1,130 | 13,742 | 4,509 | 1,048,574 | 6,049
1 Stage 3 lifetime credit impaired provision includes €21 million (31 December 2024:€21 million) on purchased or originated credit impaired. 2 The addition to the loan provision (in the consolidated statement of profit or loss) amounts to €612 million (31 December 2024: €1,194 million) of which €638 million (31 December 2024: €1,170 million) related to IFRS 9 eligible financial assets, €-26 million (31 December 2024: €9 million) related to non-credit replacement guarantees and €0 million (31 December 2024: €15 million) to modification gains and losses on restructured financial assets. Macroeconomic scenarios and sensitivity analysis of key sources of estimation uncertainty (*) Methodology (*) Our methodology in relation to the adoption and generation of macroeconomic scenarios is described in this section. We continue to follow this methodology in generating our probability-weighted ECL, with consideration of alternative scenarios and management adjustments supplementing this ECL where, in management's opinion, the consensus forecast does not fully capture the extent of recent credit or economic events. The macroeconomic scenarios are applicable to the whole ING portfolio in the scope of IFRS 9 ECLs. The IFRS 9 standard, with its inherent complexities and potential impact on the carrying amounts of our assets and liabilities, represents a key source of estimation uncertainty. In particular, ING’s reportable ECL numbers are sensitive to the forward-looking macroeconomic forecasts used as model inputs, the probability-weights applied to each of the three scenarios, and the criteria for identifying a significant increase in credit risk. As such, these crucial components require consultation and management judgement, and are subject to extensive governance. Baseline scenario (*) As a baseline for IFRS 9, ING has adopted a market-neutral view combining consensus forecasts for economic variables (GDP, unemployment) with market forwards (for interest rates, exchange rates and oil prices). Input from a leading third-party service provider is used to complement the consensus with consistent projections for variables for which there are no consensus estimates available (most notably house prices and – for some countries – unemployment), to generate alternative scenarios, to convert annual consensus information to a quarterly frequency and to ensure general consistency of the scenarios. As the baseline scenario is consistent with the consensus view, it can be considered as free from any bias. The relevance and selection of macroeconomic variables is defined by the ECL models under credit risk model governance. The scenarios applied are reviewed and challenged by ING experts. Alternative scenarios and probability weights (*) Two alternative scenarios are taken into account: an upside and a downside scenario. The alternative scenarios have statistical characteristics as they are based on the forecast deviations of the leading third-party service provider. To understand the baseline level of uncertainty around any forecast, the leading third-party service provider keeps track of all its deviations (so-called forecast errors) of the past 20 years. The distribution of forecast errors for GDP, unemployment, house prices and share prices is applied to the baseline forecast creating a broad range of alternative outcomes. In addition, to understand the balance of risks facing the economy in an unbiased way, the leading third-party service provider runs a survey with respondents from around the world and across a broad range of industries. In this survey, respondents put forward their views of key risks. Following the survey results, the distribution of forecast errors (that is being used for determining the scenarios) may be skewed. For the downside scenario, ING has chosen the 90th percentile of that distribution because this corresponds with the way risk management earnings-at-risk is defined within the Group. The upside scenario is represented by the 10th percentile of the distribution. The applicable percentiles of the distribution imply a 20 percent probability for each alternative scenario. Consequently, the baseline scenario has a 60 percent probability weighting. Please note that, given their technical nature, the downside and upside scenarios are not based on an explicit specific narrative. Macroeconomic scenarios applied (*) The macroeconomic scenarios applied in the calculation of loan loss provisions are based on the consensus forecasts. Baseline assumptions (*) The general picture that the consensus conveys is that global economic growth is expected to slow sharply in 2025 on the back of global economic uncertainty. This is expected to outweigh fiscal expansion in many advanced markets. Inflation is expected to remain near target for most advanced economies, although it is expected to remain above target for the United States on the back of new economic policies. With interest rates moderating, although some uncertainty about this path for the US exists at this point, monetary conditions should turn more favourable for growth. For the housing market, continued price growth is expected for almost all main markets. The June 2025 consensus expects global output (as measured by the weighted average GDP growth rate of ING’s 25 main markets) to marginally increase from 2.0 percent in 2025 to 2.1 percent in 2026. For 2027 economic growth is expected to come in at 2.4 percent. In the US, the uncertainty and negative effects from the economic policy agenda will likely outweigh the impact of continued fiscal stimulus. This causes economic growth expectations to slow. Inflation has come down to more benign levels but the potential inflationary impact of higher tariffs has made the Federal Reserve hold its rate-cutting cycle. Still, inflation remains above the 2% target and the outlook for inflation has become more uncertain. The consensus expects the growth rate of the US economy to grow at 1.4 percent in 2025 to 1.5 percent and 2.0 percent in 2026 and 2027 respectively. The eurozone economy saw some growth return in 2024 after a long period of stagnation that started during the energy crisis but expectations for 2025 remain modest. The export environment continues to be plagued by weak global demand amidst trade tensions and investments are stymied by global uncertainty. Expectations of a pickup in growth likely hangs on stronger public investment – think of defense spending or German infrastructure investment – but that will only gradually start to positively impact economic growth. Consensus expects the eurozone to have grown by only 0.9 percent in 2025, before recovering slightly to 1.1 percent and 1.4 percent in 2026 and 2027 respectively. Elsewhere in Europe, the outlook is more upbeat. In Poland, domestic demand appears to remain the key growth driver over the near-term forecast. Consumption growth is projected to be solid this year and next, supported by real earning gains on the back of a tight labour market. Poland can also expect stronger defense investment, but also there it will be a story for 2026. The economy is expected to grow by 3.2 percent in 2025, picking up to 3.4 percent in 2026 and slowing to 2.8 percent in 2027. The consensus expectation for Türkiye is to see growth pick up, from 2.9 percent in 2025 to 3.3 percent and 3.6 percent in 2026 and 2027 respectively as momentum remains strong despite domestic political events and global trade uncertainty. The Russian economy is expected to slow down to 1.3 percent in 2026 from 1.6 percent in 2025 and settle at 1.4 percent in 2027. For China, achieving the 5% growth target can be considered a significant challenge as external demand worries intensify due to American tariffs. Still, domestic stimulus plans do have an effect and a possible bottoming out of the real estate market still keep growth expectations decent for the short-run, although consensus expects Chinese GDP growth to remain on a downward trend for the medium-term. For 2025, consensus expects 4.5 percent growth, down to 4.1 percent in 2026 and 2027. While weaker demand from major trading partners poses a headwind, Australia’s limited direct exposure to US trade barriers will help cushion the impact. Growth will be supported by a strong labour market, solid disposable incomes, and resilient household consumption, despite subdued business investment amid heightened tariff uncertainty. Growth is expected to have come in at 1.8 percent in 2025, with a pick-up expected for 2026 to 2.2 percent and 2.5 percent for 2027. When compared to the December 2024 consensus forecast, the June 2025 forecast has deteriorated slightly on the back of geo-political tensions and economic uncertainty. Global GDP is expected to increase by 2.0 percent in 2025 (compared to 2.4 percent assumed before) and is expected to grow by 2.1 percent in 2026 (2.4 percent assumed before). With the energy crisis and pandemic now further behind us, the consensus for economic activity in major markets is showing smaller deviations over time despite economic and geopolitical uncertainty still being very prevalent. Alternative scenarios and risks (*) The baseline scenario assumes continued steady economic growth. However, a longer period of weakness, due to even more concerning geopolitical tensions, persistent elevated inflation and trade tensions could lead to a more protracted and deeper economic slowdown. As such, the balance of risks to the baseline outlook is negative, and the alternative scenarios have a downward skew in line with the outcomes of the Global Risk Survey of the before mentioned leading third-party service provider. The downside scenario sees a recession in 2025 and 2026 for most countries. Unemployment increases strongly in this scenario and house prices in most countries show outright falls. The downside scenario captures the possible impact from escalating geopolitical tensions, increased trade tensions and persistent elevated inflation. The upside scenario reflects the possibility of a better economic out-turn because of a substantial loosening of monetary policy, and policy stimulus in China. Management adjustments applied this reporting period (*) In times of volatility and uncertainty where portfolio quality and the economic environment are changing rapidly, models alone may not be able to accurately predict losses. In these cases, management adjustments can be applied to appropriately reflect ECL. Management adjustments can also be applied where the impact of the updated macroeconomic scenarios is over- or under-estimated by the IFRS 9 models, as well as to reflect the impact of model redevelopment or recalibration and periodic model assessment procedures that have not been incorporated in the IFRS 9 models yet. ING has an internal governance framework and controls in place to assess the appropriateness of all management adjustments.
Management adjustments to ECL models (*)
in EUR million | 30 June 2025 | 31 December 2024
Commercial Real Estate/ Inflation and interest rate increases | 32 |  | 50 |
Economic sector / portfolio based adjustments | 20 |  | 38 |
Mortgage portfolio adjustments | 112 |  | 112 |
Climate transition risk | 44 |  | 29 |
Other Post Model Adjustments | 29 | -27
Total management adjustments | 236 | 203
As the ING credit risk models generally assume that inflation and interest rate increases materialize with a delay, via other risk drivers such as GDP and unemployment rates, an overlay approach was determined in previous financial years to timely estimate the expected credit losses (ECL) related to reduced repayment capacity and affordability for private individuals and business clients. As inflationary stress has decreased since origination of the overlay and limited impact has been observed in both the Retail and the Wholesale Banking segment, no management adjustment is reported since 31 December 2024, with the exception of a management adjustment for the Commercial Real Estate portfolio. The €32 million management adjustment related to the Commercial Real Estate portfolio (31 December 2024: €50 million in total) is reported in Wholesale Banking (€18 million) and in Business Banking (€14 million) because the prevailing risks from increased levels of interest rates and inflation still exist for this sector in these portfolios. This management adjustment is reflected in Stage 1 and Stage 2. I n the Retail Banking segment, specific portfolio-based adjustments have been recognized. As of 30 June 2025, the economic sector / portfolio based adjustment in Stage 2 of €20 million (31 December 2024: €38 million) relates to the Business Banking portfolio in Germany (€9 million), to cover for the increased uncertainty in the German economy, and to the Mortgage portfolio in Australia (€11 million), to cover for emerging risks in that portfolio. The overall Mortgage portfolio adjustment of €112 million as of 30 June 2025 remained at the same level compared to 31 December 2024 (€112 million) and fully relates to the management adjustment in Stage 2 for the risk segmentation model that captures affordability, repayment and refinancing risk on performing mortgage customers with a bullet loan in the Netherlands. As of 30 June 2025, the adjustment of €44 million (31 December 2024: €29 million) accounts for the impact of climate transition risk in both Wholesale Banking (€25 million) and Business Banking (€19 million). Climate transition risk is expected to lead to a structural change in credit risk, which means specific business activities will become structurally riskier due to environmental policies, technological progress or changes in market sentiment and preferences. The current IFRS 9 models do not directly capture this novel risk. The management adjustment to ECL models for business clients was made to specifically cover for the medium- to long-term transition risk on high greenhouse gas-emitting sectors and is reported in Stage 2. Other management adjustments mainly relate to the impact of model redevelopment or recalibration and periodic model assessment procedures that have not been incorporated in the ECL models yet. The impact on total ECL can be positive or negative. These adjustments will be removed once updates to the specific models have been implemented. The change in balance compared to the previous reporting date is due to i) released adjustments because of model updates that have been implemented and ii) new model update related adjustments recognized. Analysis on sensitivity (*) The table below presents the analysis on the sensitivity of key forward-looking macroeconomic inputs used in the ECL collective-assessment modelling process and the probability weights applied to each of the three scenarios. The countries included in the analysis are the most significant geographic regions in ING, and for Wholesale Banking the US is the most significant in terms of both gross contribution to reportable ECL and sensitivity of ECL to forward-looking macroeconomics. Accordingly, ING considers these portfolios to present the most significant risk of resulting in a material adjustment to the carrying amount of financial assets within the next financial year. ING also observes that, in general, the WB business is more sensitive to the impact of forward-looking macroeconomic scenarios. The purpose of the sensitivity analysis is to enable the reader to understand the extent of the impact from the upside and downside scenario on model-based reportable ECL. In the table below, the real GDP is presented in percentage year-on-year change, the unemployment in percentage of total labour force and the house price index (HPI) in percentage year-on-year change.
Sensitivity analysis as at 30 June 2025 (*)
|  | 2025 | 2026 | 2027 | Unweighted ECL (€ mln) | Probability-weighting | Reportable ECL (€ mln)1
Netherlands Upside scenario | Real GDP | 1.6 |  | 2.7 |  | 2.9 |  | 275 |  | 20 | % | 382 |
Unemployment | 3.8 |  | 3.5 |  | 3.3 |
HPI | 9.8 |  | 16.7 |  | 5.1 |
Baseline scenario | Real GDP | 1.2 |  | 1.1 |  | 1.5 |  | 352 |  | 60 | %
Unemployment | 4.0 |  | 4.2 |  | 4.2 |
HPI | 7.2 |  | 3.8 |  | 3.0 |
Downside scenario | Real GDP | 0.6 |  | -1.6 |  | -0.9 |  | 581 |  | 20 | %
Unemployment | 5.0 |  | 6.6 |  | 7.8 |
HPI | 3.5 |  | -12.8 |  | 0.0 |
Germany Upside scenario | Real GDP | 0.5 |  | 3.1 |  | 2.6 |  | 577 |  | 20 | % | 621 |
Unemployment | 3.3 |  | 2.7 |  | 2.2 |
HPI | 4.1 |  | 8.0 |  | 9.6 |
Baseline scenario | Real GDP | 0.0 |  | 1.2 |  | 1.5 |  | 612 |  | 60 | %
Unemployment | 3.6 |  | 3.4 |  | 3.2 |
HPI | 2.9 |  | 4.4 |  | 6.4 |
Downside scenario | Real GDP | -0.7 |  | -2.1 |  | -0.4 |  | 695 |  | 20 | %
Unemployment | 4.2 |  | 5.3 |  | 5.7 |
HPI | 1.5 |  | -0.4 |  | 2.2 |
Belgium Upside scenario | Real GDP | 1.2 |  | 2.4 |  | 2.3 |  | 540 |  | 20 | % | 583 |
Unemployment | 5.4 |  | 5.2 |  | 5.1 |
HPI | 4.1 |  | 4.8 |  | 4.4 |
Baseline scenario | Real GDP | 0.9 |  | 1.1 |  | 1.5 |  | 572 |  | 60 | %
Unemployment | 5.9 |  | 5.8 |  | 5.7 |
HPI | 3.4 |  | 3.8 |  | 3.9 |
Downside scenario | Real GDP | 0.3 |  | -1.2 |  | 0.5 |  | 658 |  | 20 | %
Unemployment | 6.7 |  | 7.7 |  | 8.1 |
HPI | 2.5 |  | 2.1 |  | 2.6 |
United States Upside scenario | Real GDP | 1.7 |  | 2.9 |  | 3.2 |  | 82 |  | 20 | % | 126 |
Unemployment | 4.2 |  | 3.0 |  | 2.5 |
HPI | 4.7 |  | 6.3 |  | 9.7 |
Baseline scenario | Real GDP | 1.4 |  | 1.5 |  | 2.0 |  | 111 |  | 60 | %
Unemployment | 4.5 |  | 4.3 |  | 4.3 |
HPI | 4.3 |  | 3.6 |  | 4.4 |
Downside scenario | Real GDP | 0.7 |  | -1.7 |  | -0.9 |  | 213 |  | 20 | %
Unemployment | 5.3 |  | 6.9 |  | 7.9 |
HPI | 3.3 |  | -2.6 |  | -2.7 |
1 Excluding management adjustments.
Sensitivity analysis as at 31 December 2024 (*)
|  | 2025 | 2026 | 2027 | Unweighted ECL (€ mln) | Probability-weighting | Reportable ECL (€ mln)1
Netherlands Upside scenario | Real GDP | 2.6 |  | 3.0 |  | 2.5 |  | 193 |  | 20 | % | 270 |
Unemployment | 3.5 |  | 3.3 |  | 3.3 |
HPI | 18.9 |  | 11.7 |  | 2.5 |
Baseline scenario | Real GDP | 1.5 |  | 1.4 |  | 1.5 |  | 249 |  | 60 | %
Unemployment | 4.0 |  | 4.1 |  | 4.3 |
HPI | 9.1 |  | 3.5 |  | 2.4 |
Downside scenario | Real GDP | -0.4 |  | -1.4 |  | -0.2 |  | 411 |  | 20 | %
Unemployment | 5.7 |  | 7.2 |  | 8.1 |
HPI | -3.7 |  | -7.2 |  | 2.2 |
Germany Upside scenario | Real GDP | 2.0 |  | 2.8 |  | 1.6 |  | 510 |  | 20 | % | 548 |
Unemployment | 2.9 |  | 2.4 |  | 2.0 |
HPI | 5.4 |  | 8.9 |  | 9.9 |
Baseline scenario | Real GDP | 0.5 |  | 1.1 |  | 1.2 |  | 540 |  | 60 | %
Unemployment | 3.4 |  | 3.3 |  | 3.2 |
HPI | 2.6 |  | 5.6 |  | 6.3 |
Downside scenario | Real GDP | -1.7 |  | -1.7 |  | 0.3 |  | 609 |  | 20 | %
Unemployment | 4.7 |  | 5.6 |  | 5.9 |
HPI | -1.7 |  | 1.3 |  | 2.2 |
Belgium Upside scenario | Real GDP | 2.2 |  | 2.6 |  | 2.1 |  | 534 |  | 20 | % | 579 |
Unemployment | 5.1 |  | 5.0 |  | 4.9 |
HPI | 4.8 |  | 4.5 |  | 4.4 |
Baseline scenario | Real GDP | 1.1 |  | 1.5 |  | 1.6 |  | 569 |  | 60 | %
Unemployment | 5.7 |  | 5.7 |  | 5.6 |
HPI | 3.2 |  | 4.1 |  | 3.8 |
Downside scenario | Real GDP | -0.6 |  | -0.2 |  | 1.1 |  | 654 |  | 20 | %
Unemployment | 7.0 |  | 8.0 |  | 8.0 |
HPI | 1.2 |  | 2.9 |  | 2.5 |
United States Upside scenario | Real GDP | 3.1 |  | 3.5 |  | 3.2 |  | 74 |  | 20 | % | 113 |
Unemployment | 3.4 |  | 2.4 |  | 2.3 |
HPI | 4.3 |  | 8.4 |  | 9.4 |
Baseline scenario | Real GDP | 2.0 |  | 2.0 |  | 2.0 |  | 101 |  | 60 | %
Unemployment | 4.2 |  | 4.1 |  | 4.0 |
HPI | 3.3 |  | 3.7 |  | 3.9 |
Downside scenario | Real GDP | -0.1 |  | -1.1 |  | -0.4 |  | 187 |  | 20 | %
Unemployment | 5.9 |  | 7.3 |  | 8.0 |
HPI | -0.7 |  | -3.0 |  | -2.5 |
1 Excluding management adjustments.
When compared to the sensitivity analysis of year-end 2024, the macroeconomic inputs are overall less favourable. This is driven by a worsened macroeconomic outlook, mainly because of global economic uncertainty. On a total ING level, the unweighted ECL for all collective provisioned clients in the upside scenario was €2,911 million, in the baseline scenario €3,179 million and in the downside scenario €3,887 million compared to €3,267 million reportable collective provisions as at 30 June 2025 (excluding management adjustments and other adjustments in the reporting process). To perform the sensitivity analysis, a point in time reportable ECL excluding reporting adjustments is used as input, which slightly deviates from the total Model ECL as reported below:
Reconciliation of reportable collective ECL to total ECL (*)
in EUR million | 30 June 2025 | 31 December 2024
Total reportable collective provisions | 3,162 |  | 2,975 |
ECL from individually assessed impairments | 2,547 |  | 2,871 |
ECL from management adjustments | 236 |  | 203 |
Total ECL | 5,945 |  | 6,049 |
Criteria for identifying a significant increase in credit risk (SICR) (*) All assets and off-balance-sheet items that are in scope of IFRS 9 impairment and which are subject to collective ECL assessment are allocated a 12-month ECL if deemed to belong in Stage 1, or a lifetime ECL if deemed to belong in Stages 2 or 3. An asset belongs in Stage 2 if it is considered to have experienced a significant increase in credit risk (SICR) since initial origination or purchase. The main determinant of SICR is a quantitative test, whereby the lifetime probability of default (PD) of an asset at each reporting date is compared against its lifetime PD determined at the date of initial recognition. If either a threshold for absolute change in lifetime PD or a threshold for relative change in lifetime PD is reached, the item is considered to have experienced a SICR (for more details on absolute and relative thresholds, see the following sections). Furthermore, any facility which shows an increase of 200 percent between the PD at the date of initial recognition and the lifetime PD at the reporting date (i.e. threefold increase in PD) must be classified as Stage 2. This is considered a backstop within the quantitative assessment of SICR. In Wholesale Banking, significant increase in lifetime PD is not considered plausible for assets of obligors with a credit rating at the reporting date in the top range of investment grade. As of 2024, the assets of these Wholesale Banking obligors are excluded from the assessment of significant increase in credit risk triggers. For these obligors the qualitative significant increases in credit risk triggers remain applicable (see the section below on Qualitative SICR triggers). These are for example the Watchlist and/ or forbearance triggers. Finally, the 30 days past due backstop also remains applicable for the top range of investment grade exposures to ensure significant increase in credit risk recognition. Absolute lifetime PD threshold The absolute threshold is a fixed value calibrated per portfolio/segment and provides a fixed threshold that, if exceeded by the difference between lifetime PD at reporting date and lifetime PD at origination, triggers Stage 2 classification. The absolute threshold is calibrated during model development. Relative lifetime PD threshold The relative threshold defines a relative increase of the lifetime PD beyond which a given facility is classified in Stage 2 because of a significant increase in credit risk. The relative threshold is dependent on the individual PD assigned to each facility at the moment of origination, and a scaling factor calibrated in the model development phase. Ultimately, the relative threshold provides a criterion to assess whether the ratio (i.e. increase) between lifetime PD at reporting date and lifetime PD at origination date is deemed a significant increase in credit risk. If the threshold is breached, SICR is identified and Stage 2 is assigned to the given facility. The threshold for the relative change in lifetime PD is inversely correlated with the PD at origination; the higher the PD at origination, the lower the threshold. The logic behind this is to allow facilities originated in very favourable ratings to downgrade for longer without the need of a Stage 2 classification. In fact, it is likely that such facilities will still be in favourable ratings even after a downgrade of a few notches. On the contrary, facilities originated in already unfavourable ratings grades are riskier and even a single-notch downgrade might represent a significant increase in credit risk and thus a tighter threshold will be in place. Still, the relative threshold is relatively sensitive for investment-grade assets while the absolute threshold primarily affects non-investment grade assets. Average threshold ratio In the table below the average increase in PD at origination needed to be classified in Stage 2 is reported, taking into account the PD at origination of the facilities included in each combination of asset class and rating quality. In terms of rating quality, assets are divided into 'investment grade' and 'non-investment grade' facilities. Rating 18 and 19 are not included in the table, since facilities are not originated in these ratings and they constitute a staging trigger of their own (i.e. if a facility is ever to reach rating 18 or 19 at reporting date, it is classified in Stage 2). In the table, values are weighted by IFRS 9 exposure and shown for both year-end 2024 and June 2025. To represent the thresholds as a ratio (i.e. how much should the PD at origination increase in relative terms to trigger Stage 2 classification) the absolute threshold is recalculated as a relative threshold for disclosure purposes. Since breaching only relative or absolute threshold triggers Stage 2 classification, the minimum between the relative and recalculated absolute threshold is taken as value of reference for each facility.
Quantitative SICR thresholds (*)
| 30 June 2025 | 31 December 2024
Average threshold ratio | Investment grade (rating grade 1-10) | Non-investment grade (rating grade 11-17) | Investment grade (rating grade 1-10) | Non-investment grade (rating grade 11-17)
Asset class category |  |  |  |
Mortgages | 2.9 |  | 2.4 |  | 2.9 |  | 2.4 |
Consumer lending | 2.9 |  | 2.2 |  | 2.8 |  | 2.1 |
Business lending | 2.7 |  | 2.0 |  | 2.7 |  | 2.1 |
Governments and financial institutions | 2.9 |  | 1.9 |  | 2.9 |  | 1.9 |
Other Wholesale Banking | 2.7 |  | 1.9 |  | 2.7 |  | 1.9 |
As it is apparent from the disclosures above, as per ING’s methodology, the threshold is tighter the higher the riskiness at origination of the assets, illustrated by the difference between the average threshold applied to investment grade facilities and non-investment grade facilities. Sensitivity of ECL to PD lifetime PD thresholds The setting of PD threshold bands requires management judgement and is a key source of estimation uncertainty. On Group level, the total model ECL on performing assets, which is the ECL collective-assessment without taking management adjustments into account, was €1,474 million as at 30 June 2025 (31 December 2024: €1,328 million). To demonstrate the sensitivity of the ECL to these PD threshold bands, hypothetically solely applying the upside scenario would result in total model ECL on performing assets of €1,156 million and a decrease in the Stage 2 ratio by 0.5%-point, while solely applying the downside scenario would result in total model ECL on performing assets of €2,170 million and an increase in the Stage 2 ratio by 1.7%-point. Qualitative SICR thresholds It should be noted that the lifetime PD thresholds are not the only drivers of stage allocation as ING Group also relies on a number of qualitative indicators to identify and assess SICR. An asset can also change stages as a result of other triggers, such as having over 30 days arrears (used as a backstop), the occurrence of an early warning indicator, collective SICR assessment, being on a watch list, being under intensive care management, having a substandard internal rating or being forborne.

X
- Definition Entire disclosure of financial instruments and financial risk management. + References No definition available. + Details
Name: | ing_DisclosureOfFinancialInstrumentsAndFinancialRiskManagementTextBlock
Namespace Prefix: | ing_
Data Type: | dtr-types1:textBlockItemType
Balance Type: | na
Period Type: | duration

X
- Definition Risk Management [abstract] + References No definition available. + Details
Name: | ing_RiskManagementAbstract
Namespace Prefix: | ing_
Data Type: | xbrli:stringItemType
Balance Type: | na
Period Type: | duration