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Risk management

12 Months Ended

Dec. 31, 2023


Basis of disclosures () The risk management section contains information relating to the nature and extent of the risks of financial instruments as required by International Financial Reporting Standards (IFRS) 7 'Financial Instruments: Disclosures'. These disclosures are an integral part of ING Group Consolidated financial statements and are indicated by the symbol (). This is applicable for the chapters, paragraphs, graphs or tables within the risk management section that are indicated with this symbol in the respective headings or table header. This risk management section 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. Disclosures in accordance with Part Eight of the CRR2 and CRD V, and as required by the supervisory authority, are published in our ‘Additional Pillar III Report’, which can be found on our corporate website ing.com.

Governance (*)

ING’s credit risk strategy is to maintain an internationally diversified loan and bond portfolio, while avoiding

large risk concentrations. The emphasis is on managing business developments within the defined credit

and concentration risk appetite. The aim is to support relationship banking activities, while maintaining

internal risk/reward guidelines and controls.

The Credit Risk department is responsible for setting the credit risk strategy for ING and aims to ensure

credit risk and credit restructuring are managed from an overarching point of view rather than per business

line. Furthermore, the Credit Risk Control Unit is responsible for the oversight and control of rating systems.

While the Credit Risk department has oversight of the Group credit risk strategy and risk appetite across

Retail Banking risk and Wholesale Banking risk, the head of Retail/Rest of World (RoW) Risk and head of

Wholesale Banking Risk aim to ensure the management of the risk within these business lines. Also refer to

the Risk governance and organisational structure in the introductory section of 'Risk management'.

The Credit Risk function encompasses the following activities:

•Providing consistent credit risk policies, systems and tools to manage the credit lifecycle of all activities;

•Measuring, monitoring and managing credit risks in the bank’s portfolio, including evaluation of scenario

and stress test results;

•Challenging and approving new and modified transactions and borrower reviews, including involvement

in the process of assigning risk ratings to indicate a clients's creditworthiness;

•Managing the levels of provisioning and risk costs, and advising on impairments.

Credit risk categories (*)

In the following table the different types of credit risk categories are described and a reconciliation with the

notes in the financial statements is also included:


Reconciliation between credit risk categories and financial position (*)
Credit risk categories	Notes in the financial statements
Lending risk: is the risk that the client (counterparty, corporate or individual) does not pay the principal interest or fees on a loan when they are due, or on demand for letters of credit (LCs) and guarantees provided by ING.	Note	2	Cash and balances with central banks
	Note	3	Loans and advances to banks
	Note	4	Financial assets at fair value through profit or loss
	Note	5	Financial assets at fair value through other comprehensive income
	Note	7	Loans and advances to customers
	Note	41	Contingent liabilities and commitments
Investment risk: is the credit default and risk rating migration risk that is associated with ING’s investments in bonds, commercial paper, equities, securitisations and other similar publicly traded securities. This can be viewed as the potential loss that ING may incur from holding a position in underlying securities whose issuer's credit quality deteriorates or defaults.	Note	4	Financial assets at fair value through profit or loss
	Note	5	Financial assets at fair value through other comprehensive income
	Note	6	Debt securities
Money market risk: arises when ING places short-term deposits with a counterparty in order to manage excess liquidity. In the event of a counterparty default, ING may lose the deposit placed.	Note	2	Cash and balances with central banks
	Note	3	Loans and advances to banks
	Note	7	Loans and advances to customers
Pre-settlement risk: arises when a client defaults on a transaction before settlement and ING must replace the contract by a trade with another counterparty at the then prevailing (possibly unfavourable) market price. This credit risk category is associated with derivatives transactions (exchange-traded derivatives, over- the-counter (OTC) derivatives and securities financing transactions).	Note	4	Financial assets at fair value through profit or loss
	Note	14	Financial liabilities at fair value through profit or loss
	Note	40	Offsetting financial assets and liabilities
Settlement risk: arises when there is an exchange of value (funds or instruments) and receipt from its counterparty is not verified or expected until after ING has given irrevocable instructions to pay or has paid or delivered its side of the trade. The risk is that ING delivers but does not receive delivery from its counterparty.	Note	4	Financial assets at fair value through profit or loss
	Note	11	Other assets
	Note	14	Financial liabilities at fair value through profit or loss
	Note	16	Other liabilities

Credit risk appetite and concentration risk framework (*)

The credit risk appetite and concentration risk framework is designed to prevent undesired high levels of

credit risk and credit concentrations within various levels of the ING portfolio. It is derived from the concepts

of boundaries and instruments as described in the ING Risk Appetite Framework (RAF).

Credit risk appetite is the maximum level of credit risk ING is willing to accept for growth and value creation.

The credit risk appetite is linked to the overall bank-wide RAF. The credit risk appetite is expressed in

quantitative and qualitative measures. Having a credit risk appetite provides:

•Clarity about the credit risks that ING is prepared to assume, target setting and prudent risk

management. Credit risk appetite is used as an input for Lending guidances which are made by sector

and/or location;

•Consistent communication to different stakeholders;

•Guidelines on how to align reporting and monitoring tools with the organisational structure and strategy;

•Alignment of business strategies and key performance indicators of business units with ING’s credit risk

appetite through dynamic planning.

The credit risk appetite is set at different levels and dimensions within ING. The credit risk appetite

framework specifies the scope and focus of the credit risk which ING takes and the composition of the credit

portfolio, including its concentration and diversification objectives in relation to business lines, locations,

sectors and products. The credit risk appetite framework has also been extended to embed climate risk

elements. The first steps towards introducing climate risk elements in the credit risk appetite framework

were taken in 2022 and these have further evolved and matured in 2023. The climate risk elements within

the credit risk appetite framework allow for more efficient steering of sector concentrations from a climate

risk perspective.

The credit concentration risk framework is composed of:

•Country risk concentration: Country risk is the risk that arises due to events in a specific country (or group

of countries). To manage the maximum country loss ING is willing to accept, boundaries are approved by

the SB. The estimated level is correlated to the risk rating assigned to a given country. Actual country

limits are set by means of country instruments, which are monitored monthly and updated, when

needed. For countries with elevated levels of geopolitical or severe economic cycle risk, monitoring is

performed on a more frequent basis with strict pipeline and exposure management.

•Single name and secondary risk concentration: ING has an established credit concentration risk

framework to identify, measure and monitor single name concentration including secondary risk. The

same concept of boundaries and instruments is applicable.

•Sector and product concentration risk are managed via the credit risk appetite framework.

Credit risk models (*)

Within ING, internal CRR-compliant models are used to determine probability of default (PD), exposure at

default (EAD) and loss given default (LGD) for regulatory and economic capital purposes. These models also

form the basis of ING’s IFRS 9 loan loss provisioning (see ‘IFRS 9 models’ below). Bank-wide, ING has

implemented approximately 100 credit risk models, for regulatory capital, economic capital and loan loss

provisioning purposes.

There are two main types of PD, EAD and LGD models used throughout the bank:

•Statistical models are created where a large set of default or detailed loss data is available. They are

characterised by sufficient data points to facilitate meaningful statistical estimation of the model

parameters. The model parameters are estimated with statistical techniques based on the data set

available.

•Hybrid models are statistical models supplemented with knowledge and experience of experts from risk

management and front-office staff, literature from rating agencies, supervisors and academics. These

models are only used for ‘low default portfolios’, where limited historical defaults exist.

Credit risk rating process (*)

The majority of risk ratings are based on a risk rating (PD) model that complies with the minimum

requirements detailed in CRR/CRDIV, ECB Supervisory Rules and European Banking Authority (EBA)

guidelines. This concerns all borrower types and segments.

ING’s PD rating models are based on a 1-22 internal risk rating scale (1 = highest rating; 22 = lowest rating)

referred to as the ‘master scale’, which roughly corresponds to the rating grades that are assigned by

external rating agencies, such as Standard & Poor’s, Moody’s and Fitch. For example, an ING rating of 1

corresponds to an S&P/Fitch rating of AAA and a Moody’s rating of Aaa; an ING rating of 2 corresponds to an

S&P/Fitch rating of AA+ and a Moody’s rating of Aa1, and so on.

The 22 internal risk rating grades are composed of the following categories:

•Investment grade (risk rating 1-10);

•Non-investment grade (risk rating 11-17);

•Performing Restructuring (risk rating 18-19);

•Non-performing (risk rating 20-22).

The first three categories (1-19) are risk ratings for performing loans. Ratings are calculated in IT systems

with internally developed models, based on manually or automatically fed data, or for part of the non-

performing loans set by the global or regional credit restructuring department. Under certain conditions, the

outcome of a manually fed model can be challenged through a rating appeal process. For securitisation

portfolios, the external ratings of the tranche in which ING has invested are leading indicators.

Risk ratings assigned to clients are reviewed at least annually, with the performance of the underlying

models monitored regularly. Some of these models are global in nature, such as those for large corporates,

commercial banks, insurance companies, central governments, funds, fund managers, project finance and

leveraged companies. Other models are more regional or country-specific: there are PD models for small

and medium enterprises (SMEs) in the Netherlands, Belgium, Poland as well as residential mortgage and

consumer loan models in the various retail markets.

Rating models for Retail clients are predominantly statistically driven and automated, such that ratings can

be updated on a monthly basis. Rating models for large corporates, institutions and banks include both

statistical characteristics and manual input, with the ratings being manually updated at least annually.

More frequent reviews (e.g. quarterly) are performed where considered necessary, for example portfolios

and clients most at risk of being impacted by the Russian invasion of Ukraine and expected spillover effects.

In line with evolving regulatory expectations on models and emerging industry practices ING has embarked

a multi-year redevelopment process of its credit risk models. This is also in line with ING’s model governance

to ensure continuous improvement of models.

Credit risk portfolio (*)

ING’s credit exposure is mainly related to lending to individuals (also referred to as consumer lending, all

Retail) and businesses (referred to as business lending, both in Retail and Wholesale) followed by

investments in bonds and securitised assets, and money market (Wholesale). Loans to individuals are

mainly mortgage loans secured by residential property. Loans (including guarantees issued) to businesses

are often collateralised, but may be unsecured based on the internal analysis of the borrower’s

creditworthiness. Bonds in the investment portfolio are generally unsecured, but predominantly consist of

bonds issued by central governments and EU and/or OECD-based financial institutions. Secured bonds, such

as mortgage-backed securities and asset-backed securities are secured by the underlying diversified pool of

assets (commercial or residential mortgages, car loans and/or other assets) held by the securities issuer. For

money market, exposure is mainly deposits to central banks. The last major credit risk source involves pre-

settlement exposures which arise from trading activities, including derivatives, repurchase transactions and

securities lending/borrowing transactions. This is also commonly referred to as counterparty credit risk.

Portfolio analysis per business line (*)


Outstandings per line of business (*)1, 2, 3
in € million		Wholesale Banking		Retail Benelux		Retail Challengers & Growth Markets		Corporate Line		Total
Rating class		2023	2022	2023	2022	2023	2022	2023	2022	2023	2022
Investment grade	1 (AAA)	52,665	89,686	310	324	34,373	32,492	2,284	2,529	89,631	125,032
	2-4 (AA)	67,034	49,320	7,089	7,871	52,566	40,498	6	12	126,694	97,701
	5-7 (A)	95,320	79,292	44,026	45,471	88,051	61,422	147	320	227,543	186,504
	8-10 (BBB)	123,081	129,709	118,340	117,172	27,955	56,046	2,357	2,833	271,733	305,760
Non-Investment grade	11-13 (BB)	57,348	56,409	57,652	55,945	36,756	46,657		4	151,756	159,016
	14-16 (B)	12,234	13,693	16,872	14,224	12,459	11,662			41,565	39,579
	17 (CCC)	1,122	1,858	2,129	2,021	985	1,014	392	299	4,628	5,192
Performing Restructuring loans	18 (CC)	2,523	3,564	1,363	1,304	594	519			4,481	5,386
Performing Restructuring loans	19 (C)	535	731	876	962	437	490			1,848	2,183
Non-performing loans	20-22 (D)	4,051	4,354	4,586	4,762	3,036	2,592			11,673	11,708
Total		415,914	428,616	253,241	250,056	257,211	253,391	5,186	5,997	931,552	938,061

Industry
Private Individuals		2,330	32	165,447	163,243	193,610	191,556			361,387	354,831
Central Banks		70,139	80,006			21,740	23,541	2,269	1,495	94,147	105,043
Natural Resources		40,511	44,695	1,259	1,160	624	694			42,394	46,549
Real Estate		24,904	26,426	23,675	22,648	2,936	3,439			51,515	52,513
Commercial Banks		37,342	42,036	177	194	6,006	5,721	2,515	2,911	46,040	50,862
Non-Bank Financial Institutions		55,313	54,274	1,400	1,379	890	504	286	438	57,889	56,594
Central Governments		45,316	41,622	2,124	2,880	5,180	3,838	1	1,016	52,621	49,356
Transportation & Logistics		27,106	25,474	4,105	4,038	1,679	1,471			32,890	30,982
Utilities		23,324	22,683	2,024	1,865	160	150			25,509	24,698
Food, Beverages & Personal Care		13,503	13,681	7,307	7,356	2,576	2,585			23,386	23,623
Services		9,128	9,926	11,596	11,606	1,276	981	24	33	22,023	22,546
General Industries		12,039	11,731	5,680	5,753	3,406	3,381			21,126	20,865
Lower Public Administration		6,211	6,020	6,885	5,921	10,608	9,725			23,704	21,666
Other		48,748	50,009	21,563	22,014	6,519	5,805	92	104	76,922	77,932
Total		415,914	428,616	253,241	250,056	257,211	253,391	5,186	5,997	931,552	938,061


Outstandings per line of business (*) - continued1, 2, 3
in € million		Wholesale Banking		Retail Benelux		Retail Challengers & Growth Markets		Corporate Line		Total
Region		2023	2022	2023	2022	2023	2022	2023	2022	2023	2022
Europe	Netherlands	54,938	61,143	155,792	154,253	390	254	2,366	2,898	213,486	218,548
	Belgium	24,171	27,144	90,450	88,767	1,294	669	7		115,921	116,580
	Germany	26,152	24,441	478	463	128,407	127,764	31	63	155,067	152,730
	Poland	20,346	16,350	9	49	28,962	26,831			49,317	43,229
	Spain	11,047	10,491	109	71	27,049	25,649	35	25	38,240	36,237
	United Kingdom	28,587	27,735	150	152	125	185	112	107	28,974	28,179
	Luxembourg	23,805	26,113	4,880	4,953	677	639		15	29,363	31,720
	France	21,528	18,484	698	643	2,410	4,448	14	1	24,650	23,576
	Rest of Europe	65,157	77,814	367	400	20,001	18,750	32	24	85,558	96,989
America		78,851	80,444	201	190	1,841	1,795	222	358	81,114	82,786
Asia		49,851	46,291	69	73	90	121	2,365	2,504	52,374	48,989
Australia		9,409	9,817	14	16	45,963	46,281	2	2	55,389	56,116
Africa		2,071	2,348	24	28	2	5			2,098	2,381
Total		415,914	428,616	253,241	250,056	257,211	253,391	5,186	5,997	931,552	938,061
1 Based on credit risk measurement contained in lending, pre-settlement, money market and investment activities.
2 Based on the total amount of credit risk in the respective column using ING’s internal credit risk measurement methodologies. Economic sectors (industry) below 2% are not shown separately but grouped in Other.
3 Geographical areas are based on country of residence, except for private individuals for which the geographical areas are based on the primary country of risk.

Overall portfolio (*)

During 2023, ING’s portfolio size decreased by €6.5 billion (0.69%) to €931.6 billion outstanding. Foreign

exchange rate changes had a negative impact on the portfolio growth, mainly in WB, decreasing total

outstanding by €4.6 billion, driven by the depreciation of the US dollar (-3.8%) against the euro, Australian

dollar (-3.4%) and Turkish lira (-42.1%), partly compensated by the Polish zloty (+6.8%).

Rating distribution (*)

Overall, the rating class distribution remained stable in 2023. The share of investment grade rating classes

increased from 76.2% to 76.8%, while the share of non-investment grade decreased from 21.7% to 21.2%.

Performing restructuring outstandings decreased from 0.8% to 0.7% of the total portfolio, whereas non-

performing loans increased from 1.2% to 1.3%. The decrease in AAA and the increase in AA was mainly due

to lower Central banks/Central Governments exposure in AAA-rated countries, partly driven by the

downgrade of the USA to AA rating.

With respect to the rating distribution within the business lines, in WB, investment grade remained at 81.2%,

where non-investment grade exposures increased to 17.1% (from 16.8%) compared to 2022. Performing

Restructuring assets decreased from 1.0% to 0.7% of total Wholesale Banking assets. The share of non-

performing loans for WB remained stable at 1.0%.

The non-investment grade portfolio of Retail Benelux increased from 28.9% to 30.3% of the portfolio, which

is explained primarily by rating migration in mortgages in Belgium. Performing restructuring remained flat

at 0.9% whereas NPL improved to 1.8% (from 1.9%) in 2023.

In Retail Challengers & Growth Markets, the distribution across rating classes remained stable in 2023.

Overall share of investment grade increased from 75.2% to 78.9%. NPL increased to 1.2% (from 1.0%).

Industry (*)

The industry breakdown is presented in accordance with the NAICS definition. Total volume decreased in

2023 from €938.1 billion to €931.6 billion (-0.7%), mainly witnessed in Netherlands (-2.3%) and in

Luxembourg (-7.4%) due to a decrease in outstanding at Central Banks. The largest part of our book in terms

of outstandings is in private individuals with 38.8% (2022: 37.8%). Private individuals accounted for 67%

outstanding in Germany, 67% in Spain, 66% Australia and 55% in the Netherlands. The increase in WB

Private individuals is following the discontinuation of Retail Banking France which led to the transfer of the

Retail individuals portfolio from Retail Banking to Wholesale Banking.

Looking at sectors in the Business Lending portfolio, the most notable decrease in outstanding, next to

Central Banks, was in Natural Resources (-€4.2 billion).


Outstandings by economic sectors and geographical area (*) 1
in € million	Region													Total
Industry	Netherlands	Belgium	Germany	Poland	Spain	United Kingdom	Luxembourg	France	Rest of Europe	America	Asia	Australia	Africa	2023
Private Individuals	116,530	44,637	103,151	14,860	25,452	128	3,347	2,472	14,179	149	121	36,340	20	361,387
Central Banks	31,017	9,756	18,945	2,530	489	4,335	4,853		6,166		13,668	2,379	9	94,147
Natural Resources	2,623	1,346	1,017	685	129	3,789	2,511	429	10,608	8,237	9,785	941	295	42,394
Real Estate	16,907	10,986	1,111	2,184	1,551	420	3,563	2,901	3,492	3,323	1,367	3,709		51,515
Commercial Banks	1,217	404	4,050	601	353	4,488	5,070	4,155	6,757	9,833	8,182	719	210	46,040
Non-Bank Financial Institutions	2,573	1,457	5,710	2,532	652	6,837	4,631	4,274	4,269	20,118	3,884	950		57,889
Central Governments	1,620	9,046	699	8,614	5,491	41	79	2,255	9,384	13,752	520	526	593	52,621
Transportation & Logistics	3,860	2,198	1,277	1,598	658	2,113	596	784	8,177	3,511	7,044	456	618	32,890
Utilities	2,419	1,634	3,516	792	912	2,723	480	619	4,469	4,424	1,306	2,041	173	25,509
Food, Beverages & Personal Care	7,138	3,127	550	2,242	490	540	1,505	1,250	2,455	2,652	1,140	281	18	23,386
Services	5,073	8,463	1,725	1,325	71	745	502	380	1,052	1,576	469	642		22,023
General Industries	5,746	2,604	1,193	2,827	333	199	649	287	3,661	2,848	761	18		21,126
Lower Public Administration	253	6,607	5,349	669	350		249	3,488	356	1,550	7	4,826		23,704
Other	16,510	13,657	6,774	7,858	1,309	2,615	1,326	1,356	10,532	9,141	4,120	1,562	163	76,922
Total	213,486	115,921	155,067	49,317	38,240	28,974	29,363	24,650	85,558	81,114	52,374	55,389	2,098	931,552

Rating class
Investment grade	170,067	71,730	136,675	31,772	29,583	24,299	24,083	18,692	56,404	63,652	44,481	44,139	24	715,602
Non-Investment grade	40,399	40,236	16,929	15,785	8,134	4,508	5,013	5,713	25,967	16,003	6,770	10,715	1,776	197,949
Performing restructuring	1,433	799	349	830	230	2	105	122	1,983	245	72	132	26	6,327
NPL grade	1,587	3,156	1,114	929	293	165	162	124	1,205	1,213	1,051	403	272	11,673
Total	213,486	115,921	155,067	49,317	38,240	28,974	29,363	24,650	85,558	81,114	52,374	55,389	2,098	931,552
1 Geographical areas are based on country of residence, except for private individuals for which the geographical areas are based on the primary country of risk.


Outstandings by economic sectors and geographical area (*) 1
in € million	Region													Total
Industry	Netherlands	Belgium	Germany	Poland	Spain	United Kingdom	Luxembourg	France	Rest of Europe	America	Asia	Australia	Africa	2022
Private Individuals	114,625	44,193	101,529	13,767	24,865	138	3,486	2,731	13,654	161	131	35,528	24	354,831
Central Banks	35,202	14,338	21,041	1,060	347	427	6,820	35	18,092		4,962	2,695	24	105,043
Natural Resources	3,084	1,356	809	746	169	4,442	2,764	470	12,154	8,771	10,398	1,028	361	46,549
Real Estate	17,586	10,112	1,388	2,374	1,391	413	3,797	3,155	3,378	3,474	1,180	4,263	2	52,513
Commercial Banks	1,358	265	3,974	551	402	4,933	4,480	4,371	6,368	9,945	12,041	1,765	409	50,862
Non-Bank Financial Institutions	2,710	1,041	5,054	2,299	99	8,229	4,489	3,220	4,495	19,971	4,091	896		56,594
Central Governments	3,342	7,716	1,179	6,578	4,578	46	175	1,797	8,444	13,979	333	636	551	49,356
Transportation & Logistics	3,967	2,183	608	1,300	690	1,787	583	733	7,808	3,378	6,806	531	608	30,982
Utilities	1,551	1,630	2,814	679	1,227	2,953	572	980	4,302	4,347	1,545	1,897	200	24,698
Food, Beverages & Personal Care	7,249	3,002	573	2,334	475	739	1,667	469	2,668	3,245	942	248	13	23,623
Services	4,819	8,816	1,254	1,101	67	685	808	1,066	1,120	1,821	357	632		22,546
General Industries	5,430	2,689	1,007	2,849	311	330	604	245	3,152	2,926	1,311	9		20,865
Lower Public Administration	272	5,638	5,197	644	200		313	3,126	402	1,310		4,564		21,666
Other	17,353	13,602	6,302	6,946	1,416	3,058	1,164	1,179	10,952	9,457	4,891	1,424	188	77,932
Total	218,548	116,580	152,730	43,229	36,237	28,179	31,720	23,576	96,989	82,786	48,989	56,116	2,381	938,061

Rating class
Investment grade	174,971	76,244	130,285	27,501	28,556	23,160	26,053	17,545	64,884	64,206	39,903	41,476	213	714,997
Non-Investment grade	40,325	36,036	20,967	14,596	7,330	4,634	5,442	5,814	27,617	17,615	7,638	13,914	1,858	203,786
Performing restructuring	1,508	984	579	422	105	41	80	16	2,903	311	124	257	239	7,569
Non-performing loans	1,743	3,316	899	710	246	344	145	201	1,584	654	1,325	470	72	11,708
Total	218,548	116,580	152,730	43,229	36,237	28,179	31,720	23,576	96,989	82,786	48,989	56,116	2,381	938,061
1 Geographical areas are based on country of residence, except for private individuals for which the geographical areas are based on the primary country of risk.

Portfolio analysis per geographical area (*)

The portfolio analysis per geographical area re-emphasises the international distribution of ING’s credit

portfolio. The share of the Netherlands in the overall portfolio (ex-Central Banks) reduced to 21.8% (2022:

22.0%).

The most noticeable trend in the Netherlands was the decrease in exposure with central banks (-€4.2

billion). Outstandings to private individuals are at 63.9% (2022: 62.5%) of total outstandings (excl. Central

Banks). In Belgium, no substantial changes were observed in the portfolio.

In terms of rating distribution in individual countries, the total share of investment grade/non-investment

grade remains substantial for the Netherlands at 98.6% (2022: 98.5%) and in Belgium 96.6% (2022: 96.3%).

Performing restructuring grade assets remained flat in the Netherlands at 0.7%, whereas Belgium

decreased from 0.8% to 0.7%. The NPL share decreased in 2023, from 0.8% to 0.7% in the Netherlands, and

from 2.8% to 2.7% in Belgium.

In Challengers & Growth Markets, ING has a sizeable residential mortgages portfolio in Germany, Australia,

Spain and Poland.

The top five countries within Rest of Europe based on outstandings were: Italy (€18.7 billion), Romania

(€11.5 billion), Switzerland (€11.2 billion), Türkiye (€7.2 billion) and Ireland (€4.7 billion).

In Europe, outside the Benelux, rating distribution in most countries remained stable. The most noticeable

changes in rating distribution were observed in Rest of Europe, where the development of the Russian

portfolio caused a decrease into Performing Restructuring from 3.0% to 2.3%. Note the paragraph on

Russian exposures in section 'Risk management at ING Group'. Apart from Russia, noticeable changes

occurred in the UK, where NPL decreased from 1.2% to 0.6%.

In terms of rating distribution for the Americas region, an increase in NPL is observed to 1.5% (from 0.8%),

whereas in Asia, NPL decreased from 2.7% to 2.0%. In Africa, NPL increased from 3.0% to 13.0%, driven by

one well-covered file.

Credit risk mitigation (*)

ING uses various techniques and instruments to mitigate the credit risk associated with an exposure and to

reduce the losses incurred subsequent to a default by a customer. The most common terminology used in

ING for credit risk protection is ‘cover’. While a cover may be an important mitigant of credit risk and an

alternative source of repayment, generally it is ING’s practice to lend on the basis of the customer’s

creditworthiness rather than exclusively relying on the value of the cover.

Cover forms (*)

Within ING, there are two distinct forms of covers. First, where the asset has been pledged to ING as

collateral or security, ING has the right to liquidate it should the customer be unable to fulfil its financial

obligation. As such, the proceeds can be applied towards full or partial compensation of the customer's

outstanding exposure. This may be tangible (such as cash, securities, receivables, inventory, plant and

machinery, and mortgages on real estate properties) or intangible (such as patents, trademarks, contract

rights and licences). Second, where there is a third-party obligation, indemnification or undertaking (either

by contract and/or by law), ING has the right to claim from that third party an amount if the customer fails

on its obligations. The most common examples are guarantees, such as parent guarantees, export credit

insurances or third-party pledged mortgages. Insurance or reinsurance covers, including comprehensive

private risk insurance (CPRI) may be recognised as guarantees and effectively function in an equivalent

manner. ING accepts credit risk insurance companies and export credit agencies (ECAs) as cover providers.

Cover valuation methodology (*)

General guidelines for cover valuation are established with the objective of ensuring consistent application

within ING. These also require that the value of the cover is monitored on a regular basis. Covers are

revalued periodically and whenever there is reason to believe that the market is subject to significant

changes in conditions. The frequency of monitoring and revaluation depends on the type of cover.

The valuation method also depends on the type of covers. For asset collateral, the valuation sources can be

the customer’s balance sheet (e.g. inventory, machinery and equipment), nominal value (e.g. cash and

receivables), market value (e.g. securities and commodities), independent valuations (e.g. commercial real

estate) and market indices (e.g. residential real estate). For third-party obligations, the valuation is based on

the value that is attributed to the contract between ING and that third party.

Where collateral values are used in the calculation of stage 3 individual loan loss provisions, haircuts may be

applied to the valuation in specific circumstances, to sufficiently include all relevant factors impacting future

cash flows. ING applies haircuts to the collateral values of real estate, shipping and aviation assets that are

used in the calculation of the loss-given-default in recovery scenarios. The haircut reflects the risks of

adverse price developments between the moment of valuation of an asset and the actual settlement/cash

receipt.

Cover values (*)

This section provides insight into the types of cover and the extent to which exposures benefit from

collateral or guarantees. The disclosure differentiates between risk categories (lending, investment, money

market and pre-settlement). The most relevant types of cover include mortgages, financial collateral (cash

and securities) and guarantees. ING obtains cover that is eligible for credit risk mitigation under CRR/CRDIV,

as well as cover that is not eligible. Collateral covering financial market transactions is valued on a daily

basis, and as such not included in the following tables. To mitigate the credit risk arising from financial

markets transactions, the bank enters into legal agreements governing the exchange of financial collateral

(high-quality government bonds and cash).

The cover values are presented for the total portfolio of ING, both the performing and non-performing

portfolio. Our definition of non-performing is explained in detail in ‘Credit restructuring’ (below).

The next table gives an overview of the collateralisation of the ING’s total portfolio.


Cover values including guarantees received (*)
in € million		Cover type and value				Collateralisation
2023	Outstandings	Mortgages	Financial Collateral	Guarantees	Other covers	No Cover	Partially covered	Fully covered
Consumer lending	360,124	804,994	22,401	25,269	29,070	6.2%	2.0%	91.8%
Business lending	363,826	162,491	26,333	115,944	428,531	35.2%	22.5%	42.3%
Investment and money market	158,506			1,040	549	99.0%	0.6%	0.4%
Total lending, investment and money market	882,455	967,485	48,735	142,252	458,149	34.8%	10.2%	55.0%
of which NPL	11,653	8,880	1,609	3,204	9,241	25.7%	26.9%	47.4%
Pre-settlement	49,096
Total Group	931,552


Cover values including guarantees received (*)
in € million		Cover type and value				Collateralisation
2022	Outstandings	Mortgages	Financial Collateral	Guarantees	Other covers	No Cover	Partially covered	Fully covered
Consumer lending	353,323	700,961	5,626	24,231	42,817	6.2%	7.6%	86.2%
Business lending	379,405	167,122	29,501	118,294	438,864	37.5%	22.3%	40.2%
Investment and money market	141,432		5	1,213	2	99.1%	0.6%	0.3%
Total lending, investment and money market	874,160	868,083	35,132	143,738	481,683	34.8%	12.9%	52.3%
of which NPL	11,637	7,738	1,007	3,648	3,045	25.2%	25.7%	49.2%
Pre-settlement	63,901
Total	938,061

Excluding the pre-settlement portfolio, 55.0% (2022: 52.3%) of ING’s outstandings were fully collateralised in

2023. Since investments traditionally do not require covers, the percentage for ‘no covers’ in this portfolio is

above 95%. However, 99% of the investment outstanding is investment grade. Improved economic

conditions in ING’s main markets contributed to improved collateral valuations, observed in consumer

lending.

Consumer lending portfolio (*)

The consumer lending portfolio accounts for 38.7% (2022: 37.7%) of ING’s total outstanding, primarily

consisting of residential mortgage loans and other consumer lending loans. As a result, most collateral

consists of mortgages. Mortgage values are collected in an internal central database and in most cases

external data is used to index the market value. A significant part of ING’s residential mortgage portfolio is in

the Netherlands (34.8%), Germany (28.0%), Belgium including Luxembourg (13.3%) and Australia (10.9%).

Note that the large increase in Financial Collateral and decrease in Other covers is related to a

reclassification of certain cover types.

Business lending portfolio (*)

Business lending accounts for 39.1% (2022: 40.4%) of ING’s total outstanding. Business lending presented in

this section does not include pre-settlement, investment and money market exposures.

Credit quality (*)


Credit quality outstandings (*)
in € million	2023	2022
Performing not past due	795,942	799,990
Business lending performing past due	8,825	7,659
Consumer lending performing past due	846	780
Non-performing	11,653	11,691
Total lending and investment	817,266	820,120
Money market	65,189	54,039
Pre-settlement	49,096	63,901
Total	931,552	938,061

Past due obligations (*)

Retail Banking measures its portfolio in terms of payment arrears and determines on a monthly basis if

there are any significant changes in the level of arrears. This methodology is applicable to private

individuals, as well as business lending. An obligation is considered ‘past due’ if a payment of interest or

principal is more than one day late. ING aims to help its customers as soon as they are past due by

reminding them of their payment obligations. In its contact with the customers, ING aims to solve the

(potential) financial difficulties by offering a range of measures (e.g. payment arrangements, restructuring).

If the issues cannot be cured, for example because the customer is unable or unwilling to pay, the contract

is sent to the recovery unit. The facility is downgraded to risk rating 20 (non-performing) when the facility or

obligor – depending on the level at which the non-performing status is applied – is more than 90 days past

due and to risk rating 21 or 22 in case of an exit scenario.

ING has aligned the regulatory concept of non-performing with that of the definition of default. Hence, in

WB, obligors are classified as non-performing when a default trigger occurs:

•ING believes the borrower is unlikely to pay. The borrower has evidenced significant financial difficulty, to

the extent that it will have a negative impact on the future cash flows of the financial asset. The

following events could be seen as indicators of financial difficulty:

•The borrower (or third party) has started insolvency proceedings;

•A group company/co-borrower has NPL status;

•Indication of fraud (affecting the company’s ability to service its debt);

•There is doubt as to the borrower’s ability to generate stable and sufficient cash flows to service its

debt;

•Restructuring of debt.

•ING has granted concessions relating to the borrower’s financial difficulty, the effect of which is a

reduction in expected future cash flows of the financial asset below current carrying amount.

•The obligor has failed in the payment of principal, interest or fees, the total past due amount is above the

materiality threshold and this remains the case for more than 90 consecutive days.

Further, WB has an individual name approach, using early warning indicators to signal possible future issues

in debt service.


Ageing analysis (past due but performing): Consumer lending portfolio by geographic area, outstandings (*)
in € million		2023				2022
Region		Past due for 1–30 days	Past due for 31–60 days	Past due for 61–90 days	Total	Past due for 1–30 days	Past due for 31–60 days	Past due for 61–90 days	Total
Europe	Belgium	223	43	29	295	294	27	18	339
	Germany	89	40	18	147	68	34	13	116
	Poland	76	8	5	89	59	8	4	71
	Netherlands	67	24	6	97	36	10	5	51
	Luxembourg	21	2	2	25	43	4	2	48
	Spain	19	13	6	38	13	9	5	27
	Rest of Europe	64	19	12	94	62	16	8	86
America		1			1	1			1
Asia					1
Australia		43	15	1	59	29	11	2	42
Total		602	164	79	846	604	119	57	780

The past due but performing consumer lending outstanding increased by €66 million, mainly due to

increase in 31-60 (+€45 million) and 61-90 (+€22 million). The largest increase was observed in the

Netherlands (+€47 million) and Germany (+€31 million) mainly in the 1-30-day bucket; the largest decrease

was seen in Belgium (-€44 million) driven by the decrease in the 1-30 bucket.


Ageing analysis (past due but performing): Business lending portfolio by geographic area, outstandings (*)
in € million		2023				2022
Region		Past due for 1–30 days	Past due for 31–60 days	Past due for 61–90 days	Total	Past due for 1–30 days	Past due for 31–60 days	Past due for 61–90 days	Past due for >90 days	Total
Europe	Belgium	929	98	11	1,037	579	49	10		639
	United Kingdom	623	659	128	1,410	1,147	77	512		1,736
	Luxembourg	577	8	11	596	302	1			303
	Netherlands	509	10	12	531	730	30	15		775
	Poland	346	26	10	383	279	35	14		329
	France	58	132		190	83	6			90
	Germany	131	110	1	242	44	16			60
	Rest of Europe	972	2	2	977	474	239	1	1	715
America		2,508	101	41	2,650	1,901	67	19		1,986
Asia		284		22	306	553	48			601
Australia		501	1		502	359	61	4	2	426
Total		7,437	1,148	240	8,825	6,452	629	575	4	7,659

Total past due but performing outstanding of business lending increased by €1.2 billion. Increase is observed

in the 1-30 days (€1.0 billion) past due bucket and in the 31-60 days (€0.5 billion), partly offset by a

decrease in the 61–90 days past due bucket (-€336 million), driven by the United Kingdom (-€383 million).

Credit restructuring (*)

Global Credit Restructuring (GCR) is the dedicated and independent department that deals with non-

performing loans and loans that hold a reasonable probability that ING will end up with a loss, if no specific

action is taken. GCR handles accounts or portfolios requiring an active approach, which may include

renegotiation of terms and conditions and business or financial restructuring. The loans are managed by

GCR or by units in the various regions and business units. ING uses three distinct statuses to categorise the

management of clients with (perceived) deteriorating credit risk profiles, i.e. there is increasing doubt as to

the performance and the collectability of the client’s contractual obligations:

•Watch list: Usually, a client is first classified as watch list when there are concerns of any potential or

material deterioration in credit risk profile that may affect the ability of the client to adhere to its debt

service obligations or to refinance its existing loans. Watch list status requires more than usual attention,

increased monitoring and quarterly reviews. Some clients with a watch list status may develop into a

restructuring status or even a recovery status.

•Restructuring: A client is classified as restructuring when there are concerns about the client’s financial

stability, credit worthiness, and/or ability to repay, but where the situation does not require the

termination or acceleration of facilities or the liquidation of collateral. ING’s actions aim to maintain the

going concern status of the client by:

•restoring the client’s financial stability;

•supporting the client’s turnaround;

•restoring the balance between debt and equity; and

•restructuring the debt to a sustainable situation.

•Recovery: A client is classified as in recovery when ING and/or the client concludes that the client’s

financial situation cannot be restored and a decision is made to terminate the (credit) relationship or

even to enter into bankruptcy. ING prefers an amicable exit, but will enforce and liquidate the collateral

or claim under the guarantees if deemed necessary.

Watch list, restructuring and recovery accounts are reviewed at least quarterly by the front office, GCR and

the relevant credit risk management executives.

Forbearance (*)

Forbearance occurs when a client is unable to meet their financial commitments due to financial difficulties

they face or are about to face and ING grants concessions towards them. Forborne assets are assets in

respect of which forbearance measures have been granted.

Forbearance may enable clients experiencing financial difficulties to continue repaying their debt.

For business clients, ING mainly applies forbearance measures to support clients with fundamentally sound

business models that are experiencing temporary difficulties with the aim of maximising the client’s

repayment ability and therewith avoiding a default situation or helping the client to return to a performing

situation.

For ING retail units, clear criteria have been established to determine whether a client is eligible for the

forbearance process. Specific approval mandates are in place to approve the measures, as well as

procedures to manage, monitor and report the forbearance activities.

ING reviews the performance of forborne exposures at least quarterly, either on a case-by-case (business) or

on a portfolio (retail) basis.

All exposures are eligible for forbearance measures, i.e. both performing (risk ratings 1-19) and non-

performing (risk ratings 20-22) exposures. ING uses specific criteria to move forborne exposures from non-

performing to performing or to remove the forbearance statuses that are consistent with the corresponding

European Banking Authority (EBA) standards. An exposure is reported as forborne for a minimum of two

years. An additional one-year probation period is applied to forborne exposures that move from non-

performing back to performing.


Summary Forborne portfolio (*)
in € million	2023				2022
Business line	Outstandin gs	Of which: performi ng	Of which: non- performing	% of total portfolio	Outstandin gs	Of which: performi ng	Of which: non- performing	% of total portfolio
Business line	Outstandin gs	Of which: performi ng	Of which: non- performing	% of total portfolio	Outstandin gs	Of which: performi ng	Of which: non- performing	% of total portfolio
Wholesale Banking	6,063	3,919	2,144	1.8%	8,359	5,880	2,478	2.7%
Retail Banking	7,026	4,128	2,898	1.4%	8,080	4,973	3,107	1.6%
Total	13,089	8,047	5,042	1.5%	16,438	10,853	5,585	2.0%


Summary Forborne portfolio by forbearance type (*)
in € million	2023				2022
Forbearance type	Outstandin gs	Of which: performi ng	Of which: non- performing	% of total portfolio	Outstandin gs	Of which: performi ng	Of which: non- performing	% of total portfolio
Forbearance type	Outstandin gs	Of which: performi ng	Of which: non- performing	% of total portfolio	Outstandin gs	Of which: performi ng	Of which: non- performing	% of total portfolio
Loan modification	11,881	7,550	4,331	1.4%	15,317	10,428	4,889	1.9%
Refinancing	1,208	497	711	0.1%	1,121	426	695	0.1%
Total	13,089	8,047	5,042	1.5%	16,438	10,853	5,585	2.0%

As of 31 December 2023, ING’s total forborne assets decreased by €3.3 billion compared to 31 December

2022. WB decreased by €2.3 billion and Retail Banking decreased by €1.1 billion. The decreases are mainly

caused by passing the two-year probation period following the Covid-19 pandemic.

Wholesale Banking (*)

As of December 2023, WB forborne assets amounted to €6.1 billion (2022: €8.4 billion), which represented

1.8% (2022: 2.7%) of the total WB portfolio.


Wholesale Banking: Forborne portfolio by geographical area (*)
in € million		2023			2022
Region		Outstandings	Of which: performing	Of which: non-	Outstandings	Of which: performing	Of which: non-
Region		Outstandings	Of which: performing	performing	Outstandings	Of which: performing	performing
Europe	Netherlands	361	301	60	720	630	90
	Belgium	454	446	8	659	651	8
	Germany	288	148	139	580	466	115
	United Kingdom	583	425	158	1,044	721	323
	Italy	54	19	34	205	157	48
	Norway	6	0	6	33	0	33
	Poland	520	519	0	203	189	14
	Rest of Europe	1,421	1,142	279	2,176	1,749	427
America		1,025	532	493	1,353	1,032	321
Asia		1,198	277	921	1,107	143	964
Australia		87	87	0	217	132	85
Africa		68	23	45	61	10	51
Total		6,063	3,919	2,144	8,359	5,880	2,478


Wholesale Banking: Forborne portfolio by economic sector (*)
in € million	2023			2022
Industry	Outstandings	Of which: performing	Of which: non- performing	Outstandings	Of which: performing	Of which: non- performing
Industry	Outstandings	Of which: performing	Of which: non- performing	Outstandings	Of which: performing	Of which: non- performing
Natural Resources	788	321	467	1,239	603	636
Real Estate	1,320	1,254	66	2,000	1,917	84
Transportation & Logistics	315	175	139	1,073	868	205
Food, Beverages & Personal Care	866	465	401	1,082	543	539
Services	284	254	30	697	665	32
Automotive	138	98	40	172	125	46
Utilities	510	255	255	469	255	214
General Industries	145	74	71	255	176	80
Retail	282	104	178	302	227	76
Chemicals, Health & Pharmaceuticals	571	559	11	191	168	23
Builders & Contractors	133	72	61	168	94	74
Other	712	287	425	710	240	469
Total	6,063	3,919	2,144	8,359	5,880	2,478

The main concentration of forborne assets in a single country was in United States with 13.6% (2022:

11.5%) of the total WB forborne assets.

WB forborne assets decreased by €2.3 billion compared to 2022, also driven by passing the two-year

probation period following the Covid-19 pandemic. Decrease is mainly visible in the performing forborne

assets (-€2.0 billion), mainly in the industries Transportation & Logistics, Real Estate and Services. The

decrease was partial offset by an increase for Chemicals, Health and Pharmaceuticals, driven by a few large

individual clients.

WB's forborne assets are mainly concentrated in Real Estate, Food Beverages & Personal Care, Natural

Resources, Chemicals, Health & Pharmaceuticals, and Utilities.These five economic sectors accounted for

67% of the total WB forborne outstandings

Retail Banking (*)

As of the end of December 2023, Retail Banking forborne assets totalled €7.0 billion, which represented 1.4%

of the total Retail Banking portfolio. The majority of forborne exposures were in private individuals with

50.5%.


Retail Banking: Forborne portfolio by geographical area (*)
in € million		2023			2022
Region		Outstandings	Of which: performing	Of which: non-	Outstandings	Of which: performing	Of which: non-
Region		Outstandings	Of which: performing	performing	Outstandings	Of which: performing	performing
Europe	Netherlands	1,483	981	502	2,832	2,043	789
	Belgium	2,153	838	1,315	2,644	1,331	1,314
	Germany	1,309	1,064	246	804	610	194
	Poland	852	522	330	588	309	279
	Türkiye	25	15	10	64	31	32
	Italy	123	51	71	131	52	79
	Romania	135	49	86	124	53	71
	Spain	138	118	21	35	15	20
	Rest of Europe	88	58	30	73	48	25
America		21	20		13	12
Asia		2	1	1	3	1	1
Australia		697	411	286	768	467	302
Africa					1
Total		7,026	4,128	2,898	8,080	4,973	3,107

The main concentration of forborne assets in a single country was in Belgium with 30.6% (2022: 32.7%) of

total Retail Banking forborne assets and 45.4% (2022: 42.3%) of the non-performing forborne assets. Next to

that, Netherlands had 21.1% (2022: 35.0%) of the total Retail forborne assets and Germany 18.6%

(2022:10.0%). The increase in Germany is driven by mortgages, where clients that choose for a repayment

percentage below a certain threshold, though contractually allowed, are conservatively considered forborn.

Non-performing loans (*)

ING’s loan portfolio is under constant review. Loans to obligors that are considered more than 90 days past

due and above applicable thresholds are reclassified as non-performing. For business lending portfolios,

there generally are reasons for declaring a loan non-performing prior to the obligor being 90 days past due.

These reasons include, but are not limited to, ING’s assessment of the customer’s perceived inability to meet

its financial obligations, or the customer filing for bankruptcy or bankruptcy protection.

The table below represents the breakdown by industry of credit risk outstandings that have been classified

as non-performing.


Non-performing Loans: outstandings by economic sector and business lines (*)1
in € million	Wholesale Banking		Retail Benelux		Retail Challengers & Growth Markets		Total
Industry	2023	2022	2023	2022	2023	2022	2023	2022
Private Individuals	4		2,210	2,174	2,206	1,954	4,419	4,129
Natural Resources	669	1,369	60	34	25	17	754	1,421
Food, Beverages & Personal Care	565	672	363	438	157	122	1,085	1,233
Transportation & Logistics	437	367	69	165	65	51	572	583
Services	101	119	415	448	66	61	582	628
Real Estate	592	172	398	486	64	54	1,053	712
General Industries	111	114	270	268	115	100	497	482
Builders & Contractors	124	139	291	244	162	110	577	493
Retail	207	98	121	107	67	39	395	244
Utilities	331	387	12	7	6	7	348	401
Chemicals, Health & Pharmaceuticals	101	175	97	115	35	20	233	310
Telecom	378	288	9	12	3	3	390	303
Other	412	440	270	260	66	52	748	753
Total	4,034	4,340	4,583	4,759	3,036	2,592	11,653	11,691

1 Based on lending and investment outstandings.


Non-performing Loans: outstandings by economic sectors and geographical area (*)
in € million	Region													Total
Industry	Netherlands	Belgium	Germany	Poland	Spain	United Kingdom	France	Luxembourg	Rest of Europe	America	Asia	Australia	Africa	2023
Private Individuals	609	1,535	885	225	235	3	8	45	489	2	2	380	1	4,419
Natural Resources	30	60	1	23				55	164	31	369		20	754
Food, Beverages & Personal Care	281	157	1	131		139	7		158	82	128			1,085
Transportation & Logistics	110	50	2	51	47	20		1	168	49	1	2	72	572
Services	121	342	2	55	2		3	8	13	37				582
Real Estate	40	297	53	55	9		36	16	7	519		21		1,053
General Industries	145	127	49	99			2	7	24	42				497
Builders & Contractors	113	181	2	135				22	91	32				577
Retail	51	82	36	52			2		14	149	7			395
Utilities	14	5		21					18	153	138			348
Chemicals, Health & Pharmaceuticals	31	77	13	25			64		11	12				233
Telecom	12	1	28	3					13	56	277			390
Other	28	239	42	55		2	1	6	23	46	128		179	748
Total	1,586	3,153	1,114	929	293	165	124	162	1,193	1,210	1,050	403	272	11,653


Non-performing Loans: outstandings by economic sectors and geographical area (*)
in € million	Region													Total
Industry	Netherlands	Belgium	Germany	Poland	Spain	United Kingdom	France	Luxembourg	Rest of Europe	America	Asia	Australia	Africa	2022
Private Individuals	574	1,538	739	185	194	4	11	36	470	3	4	370	1	4,129
Natural Resources	57	33		14				53	432	77	649	85	21	1,421
Food, Beverages & Personal Care	310	179	24	109		173	7		228	77	126			1,233
Transportation & Logistics	232	58	1	36	47	20		2	154	24	7	1		583
Services	136	375	2	43	5		3	2	21	40				628
Real Estate	89	376		54		84	25	19	7	47		11		712
General Industries	127	142	17	78			31	2	26	58				482
Builders & Contractors	65	187	2	86				20	101	32				493
Retail	31	85	38	26			18	1	13	22	7	2		244
Utilities	6	6	26	23					17	194	129			401
Chemicals, Health & Pharmaceuticals	51	100	2	15		14	100		28					310
Telecom	24	1		3						5	270			303
Other	40	232	48	38		50		10	79	75	130		51	753
Total	1,742	3,312	899	710	246	344	196	145	1,578	654	1,324	470	72	11,691

In 2023, the NPL portfolio stayed relatively flat at €11.7 billion. An increase in Challengers and Growth retail

(+€0.4 billion) was offset by decreases in Wholesale Banking (-€0.3 billion) and Retail Benelux (-€0.2 billion).

The increase in Challengers & Growth Markets was mainly witnessed in private individuals. In Wholesale

Banking, the decrease in the Natural Resources sector was partially compensated by an increase in Real

Estate sector, especially in the Americas. The top three countries by NPL outstanding are Belgium, the

Netherlands and the Americas.

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.

IFRS 9 models (*)

ING's IFRS 9 models leverage on the internal rating-based (IRB) models (PD, LGD, EAD), which include certain

required conservatism. To include IFRS 9 requirements, such regulatory conservatism is removed from the

ECL parameters (PD, LGD and EAD). The IFRS 9 models apply two other types of adjustments to the IRB ECL

parameters: (i) to the economic outlook and (ii) for Stage 2 and Stage 3 assets only, to the lifetime horizon.

The IFRS 9 model parameters are estimated based on statistical techniques and supported by expert

judgement.

ING has aligned the definition of default for regulatory purposes with the definition of ‘credit-impaired’

financial assets under IFRS 9 (Stage 3). ING has also aligned its definition of default between IFRS9 and the

regulatory technical standards (RTS) and EBA guidelines. More information can be found in section 1.5.6 of

the consolidated financial statements.

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 depreciation/ erosion of

collateral values which would translate into higher credit losses and loan-to-value ratios in the lending

portfolio of ING.

At this point in time it is not yet possible to incorporate climate risk separately into IFRS 9 ECL models given

the lack of sufficient empirical historical data and data limitations in the risk assessments on client level.

Where climate and environmental factors have impacted the economy in the recent past or present, these

impacts will currently be implicitly embedded in ING's IFRS9 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, after which a mean reversion approach is applied.

With regard to our evaluation of climate-related matters, where such events 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 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.

Over the near-term time horizon, ING plans to continue to refine its methodologies to evaluate climate risks.

ING is working on putting into practice quantitative methodologies for climate and environmental (C&E) risk

identification, materiality assessment and risk appetite setting. Refer to ESG risk paragraph for further

details on ESG risk management. Going forward, ING aims to continue to close the gaps on climate risk data,

which will enable us to embed climate risks eventually into the IFRS 9 ECL models.

Portfolio quality (*)

The table below describes the portfolio composition over the different IFRS 9 stages and rating classes. The

Stage 1 portfolio represents 91.5% (2022: 91.5%) of the total gross carrying amounts, mainly composed of

investment grade, while Stage 2 makes up 7.4% (2022: 7.3%) and Stage 3 makes up 1.2% (2022: 1.2%) of

the total gross carrying amounts, respectively.


Gross carrying amount per IFRS 9 stage and rating class (*)1,2,3
in € million		12-month ECL (Stage 1)		Lifetime ECL not credit impaired (Stage 2)		Lifetime ECL credit impaired (Stage 3)		Total
2023		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
Investment grade	1 (AAA)	87,071	1	439				87,510	1
	2-4 (AA)	132,159	8	2,553	2			134,711	9
	5-7 (A)	231,018	24	6,188	6			237,206	30
	8-10 (BBB)	302,967	85	17,004	24			319,971	108
Non-Investment grade	11-13 (BB)	157,387	226	19,273	93			176,661	319
	14-16 (B)	26,414	164	19,336	455			45,750	618
	17 (CCC)	617	10	4,125	233			4,742	242
Performing Restructuring	18 (CC)			4,617	402			4,617	402
Performing Restructuring	19 (C)			1,919	221			1,919	221
Non-performing loans	20-22 (D)					11,956	3,887	11,956	3,887
Total		937,633	517	75,454	1,435	11,956	3,887	1,025,043	5,839
1 Compared to the credit risk portfolio, the differences are mainly undrawn committed amounts (€151billion) and other positions (€9 billion) not included in credit outstandings and non-IFRS 9 eligible assets (€67 billion, mainly pre-settlement exposures) included in credit outstandings but not in the gross carrying amounts. 2 Includes impact from change in accounting policy as disclosed in table Changes in gross carrying amounts and loan loss provisions. 3 Stage 3 lifetime credit impaired provision includes €11 million on purchased or originated credit impaired.


Gross carrying amount per IFRS 9 stage and rating class (*)1,2
in € million		12-month ECL (Stage 1)		Lifetime ECL not credit impaired (Stage 2)		Lifetime ECL credit impaired (Stage 3)		Total
2022		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
Investment grade	1 (AAA)	100,885	2	284				101,169	2
	2-4 (AA)	98,181	5	2,493	1			100,675	6
	5-7 (A)	177,617	23	4,596	4			182,214	27
	8-10 (BBB)	321,308	98	14,714	29			336,023	127
Non-Investment grade	11-13 (BB)	155,910	277	17,365	91			173,275	368
	14-16 (B)	23,649	168	19,386	471			43,035	639
	17 (CCC)	7,671	8	4,572	194			12,244	202
Performing Restructuring	18 (CC)			5,198	595			5,198	595
Performing Restructuring	19 (C)			2,116	293			2,116	293
Non-performing loans	20-22 (D)					11,708	3,841	11,708	3,841
Total		885,222	581	70,725	1,679	11,708	3,841	967,655	6,101
1 Compared to the credit risk portfolio, the differences are mainly undrawn committed amounts (€150.1 billion) and other positions (€4.4 billion) not included in credit outstandings and non-IFRS 9 eligible assets (€116.1 billion, mainly guarantees, letters of credit and pre- settlement exposures) included in credit outstandings but not in the gross carrying amounts. 2 IAS 37 provisions are established for non-credit replacement guarantees not in the scope of IFRS 9. Total IAS 37 provisions (€109 million) are excluded.

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:

•The opening balance is impacted by a change in accounting policy following the adoption of IFRS 17,

more specifically for loans with death waivers that no longer meet the ‘solely payments of principal and

interest’ (SPPI) criterion (€-55 million loan loss provisions impact) which are no longer recorded at

amortised cost, and a change in policy for non-financial guarantees that are subject to contractual

indemnification rights which led to a reclassification of the existing IAS 37 provision (€109 million loan

loss provisions impact) and a remeasurement of these non-financial guarantees (€42 million loan loss

provisions impact). Reference is made to Note 1 'Basis of preparation and significant changes in the

current reporting period'.

•Stage 3 gross carrying amount increased slightly to €12.0 billion as at 31 December 2023 as new inflow

into NPL (credit impaired) in 2023 was only partly offset by repayments, derecognitions and write-offs.

Stage 3 provisions remained more or less flat at €3.9 billion.

•Stage 2 gross carrying amount increased by €0.1 billion from €75.4 billion (after changes in accounting

policies) as at 31 December 2022 to €75.5 billion as at 31 December 2023. An increase of Stage 2

exposure, driven by the implementation of an updated methodology for interest-only mortgages in the

Netherlands, was offset by outflow due to improved macro economic outlook, decrease of exposure due

to sales and repayments (including Russian exposure), forborne customers returning to Stage 1 after the

probation period has ended and other improved risk drivers. As a result, Stage 2 provisions also

decreased by €0.3 billion to €1.4 billion as of 31 December 2023.


Changes in gross carrying amounts and loan loss provisions (*)1, 2
in € million	12-month ECL (Stage 1)		Lifetime ECL not credit impaired (Stage 2)		Lifetime ECL credit impaired (Stage 3)		Total
2023	Gross carrying amount	Provisions	Gross carrying amount	Provisions	Gross carrying amount	Provisions	Gross carrying amount	Provisions
Opening balance	885,222	581	70,725	1,679	11,708	3,841	967,655	6,101
Impact of changes in accounting policies	37,078	9	4,704	13	158	73	41,939	95
Adjusted Opening balance	922,300	590	75,429	1,692	11,866	3,914	1,009,595	6,196
Transfer into 12-month ECL (Stage 1)	11,832	28	-11,583	-239	-249	-36		-247
Transfer into lifetime ECL not credit impaired (Stage 2)	-29,470	-67	30,185	449	-716	-105		277
Transfer into lifetime ECL credit impaired (Stage 3)	-2,053	-10	-1,775	-115	3,828	978		853
Net remeasurement of loan loss provisions		-149		-94		59		-184
New financial assets originated or purchased	195,775	204					195,775	204
Financial assets that have been derecognised	-121,991	-72	-14,239	-215	-1,475	-266	-137,705	-553
Net drawdowns and repayments	-38,758		-2,525		-229		-41,511
Changes in models/risk parameters		8		10		84		102
Increase in loan loss provisions		-58		-204		714		452
Write-offs	-3	-3	-38	-38	-1,070	-1,070	-1,111	-1,111
Recoveries of amounts previously written off						71		71
Foreign exchange and other movements		-12		-15		258		231
Closing balance	937,633	517	75,454	1,435	11,956	3,887	1,025,043	5,839
1 Stage 3 lifetime credit impaired provision includes €11 million on purchased or originated credit impaired. 2 The addition to the loan provision (in the consolidated statement of profit or loss) amounts to €520 million of which €483 million related to IFRS 9 eligible financial assets, -€31 million related to non-credit replacement guarantees and €68 million to modification gains and losses on restructured financial assets.


Changes in gross carrying amounts and loan loss provisions (*)1, 2
in € million	12-month ECL (Stage 1)		Lifetime ECL not credit impaired (Stage 2)		Lifetime ECL credit impaired (Stage 3)1		Total
2022	Gross carrying amount	Provisions	Gross carrying amount	Provisions	Gross carrying amount	Provisions	Gross carrying amount	Provisions
Opening balance	890,386	501	49,476	1,016	12,072	3,851	951,934	5,368
Transfer into 12-month ECL (Stage 1)	8,513	21	-8,105	-142	-408	-47		-168
Transfer into lifetime ECL not credit impaired (Stage 2)	-42,439	-76	43,222	730	-784	-90		564
Transfer into lifetime ECL credit impaired (Stage 3)	-3,524	-8	-1,216	-82	4,740	1,234		1,144
Net remeasurement of loan loss provisions		8		223		199		430
New financial assets originated or purchased	248,443	228					248,443	228
Financial assets that have been derecognised	-138,250	-70	-11,312	-94	-2,805	-215	-152,366	-379
Net drawdowns and repayments	-77,907		-1,340		21		-79,226
Changes in models/risk parameters		-8		13		25		30
Increase in loan loss provisions		95		648		1,106		1,849
Write-offs				-1	-1,129	-1,129	-1,129	-1,130
Recoveries of amounts previously written off						71		71
Foreign exchange and other movements		-15		16		-58		-57
Closing balance	885,222	581	70,725	1,679	11,708	3,841	967,655	6,101
1 Stage 3 Lifetime credit impaired provision includes €7 million on purchased or originated credit impaired.
2 The addition to the loan provision (in the consolidated statement of profit or loss) amounts to €1,861 million of which €1,850 million related to IFRS 9 eligible financial assets, -€3 million related to non-credit replacement guarantees and €14 million to modification gains and losses on restructured financial assets.

Modification of financial assets (*)

The table below provides the following information:

•Financial assets that were modified during the year (i.e. qualified as forborne) while they had a loss

allowance measured at an amount equal to lifetime ECL.

•Financial assets that were reclassified to stage 1 during the period.


Financial assets modified (*)
in € million	2023	2022
Financial assets modified during the period
Amortised cost before modification	1,565	1,304
Net modification results	-75	-124

Financial assets modified since initial recognition
Gross carrying amount at 31 December of financial assets for which loss allowance has changed to 12-month measurement during the period	2,599	2,382

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 are reviewed and challenged by two panels of ING experts. The first panel

consists of (economic) experts from Global Markets Research, risk and modelling, while the second panel

consists of relevant senior managers in ING.

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 for 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 going through a weak

spell. Inflation has been coming down as energy prices have moderated, demand has weakened and

pandemic-related supply problems have eased. Higher interest rates play their part in slowing demand.

Although central banks could well be done with hiking interest rates – as inflation continues to fall – the

lagged impact of past monetary tightening is still feeding through to the real economy. This is expected to

cause GDP growth to come in even weaker in 2024, but pickup thereafter as the negative effects from tight

monetary policy and high inflation fade. The high-interest rate environment is currently causing corrections

in house prices, especially in markets where prices surged during the pandemic. Housing market corrections

are assumed to gradually decrease in strength.

The December 2023 consensus expects global output (as measured by the weighted average GDP growth

rate of ING's 25 main markets) to slow from 2.6% in 2022, to 2.4% in 2023 and 1.8% in 2024. For 2025-2026,

economic growth is expected to pick up again to 2.3% and 2.4%.

The US economy outperformed expectations in 2023, driven by strong consumer spending and fiscal

support. Still, headwinds have been building up, in part driven by the much higher interest rates currently

experienced. While an outright recession is not expected, the consensus does foresee a marked slowdown in

economic activity in the US in 2024. After this, the US economy is expected to gather strength again in

2025. The consensus expects the growth rate of the US economy to fall from 2.2% in 2023 to 0.9% in 2024

and to recover to 2% on average in 2025-2026.

The eurozone economy is facing broad stagnation as it deals with the impact of the war in Ukraine, energy

crisis, and higher interest rates. While inflation is coming down, the impact of last year’s purchasing power

shock is still being felt. Monetary tightening works with a lag, which will still affect economic activity next

year. Overall, the eurozone economy is forecasted to have grown by just 0.5% in 2023, but Germany has

gone through recession reflecting its large (energy-intensive) manufacturing sector, and exposure to a

disappointing Chinese economy. For next year, the recovery is expected to be very modest as consensus

expects the eurozone to grow by only 0.8% in 2024, before recovering to 1.4% on average in 2025-2026.

Elsewhere in Europe, the outlook is mixed. In Poland, after an expected 0.4% growth in 2023, the economy is

expected to recover by 2.5% in 2024 led by household consumption growth. Wage growth is set to remain

strong while inflation has subsided substantially. The consensus expectation for Türkiye is to see growth

slow substantially in 2024 with unemployment remaining around 10% for the foreseeable future. The

consensus sees economic growth in Türkiye slowing from 3.5% in 2023, to 2.1% in 2024 and increasing

again to 3.3% on on average in 2025-2026. The Russian economy has started to recover from the 2022

recession, but growth is set to moderate after 1.7% in 2023 to 1.2% on average in 2024-2026.

2023 was supposed to be the year of a strong reopening for China, but growth did not meet expectations.

Weak global demand for goods has resulted in a weaker than expected industrial performance and the real

estate sector continues to be a source of concern. For the 2024-2026 period, economic growth is expected

to come in at only 4.2% despite increased stimulus.

The global economic slowdown and tighter monetary policy continue to weigh on economic growth in

Australia. After growing by 1.7% in 2023, the outlook sees a growth rate of 1.3% for 2024 and some pick-up

to 2.4% and 2.5% for 2025-2026.Unemployment is expected to run up a little more, from 4.1% in 2023 to

4.4% ,but decrease again thereafter.

When compared to the December 2022 consensus forecast, used for the 2022 Annual Report, the December

2023 forecast assumes somewhat better economic circumstances in 2023 but weaker for 2024. The

forecast assumes to have Global GDP increased by 2.4% in 2023 (compared to 1.3% assumed before) and is

expected to grow by 1.8% in 2024 (2.4% assumed before). The upgrade for 2023 reflects the better than

expected economic performance of the US and eurozone as a recession on the back of the energy crisis was

avoided, while the downgrade for 2024 reflects the impact of substantial monetary tightening.

Alternative scenarios and risks (*)

Because of the possible consequences of geopolitical risks, uncertainty surrounding the forecasts was higher

in 2022. During 2023, the uncertainty level around the forecasts gradually decreased. To take this into

account, ING applies normal levels of dispersion in the alternative scenarios used for year-end 2023

provisioning. For year-end 2022 half-widened dispersion levels were used, by which the near-term

dispersion of the forward-looking distributions (from which the alternative scenarios are derived) was larger

than in normal times.

The baseline scenario assumes a further easing of inflation in 2024 and relatively resilient labour markets.

However, a longer period of weakness, due to even more concerning geopolitical tensions, persistent

elevated inflation and a slowdown in China 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 from a leading third-party

service provider. The downward skew remained stable compared to what has been applied for year-end

2022, continuing to reflect risks related to possible escalation of geopolitical tensions, a prolonged surge in

inflation and tightening monetary policy.

The downside scenario, though technical in nature, sees for most countries a recession in 2024.

Unemployment increases strongly in this scenario and house prices in most countries show outright falls.

The downside scenario captures a possible escalation of geopolitical tensions, a prolonged surge in inflation

and further slowing in China.

The upside scenario – while equally technical in nature – reflects the possibility of a better economic outturn

if consumers spend more of their excess savings, geopolitical risks subside and China stimulus works out

more strongly than expected.

Management adjustments applied this year (*)

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.

ING has internal governance frameworks and controls in place to assess the appropriateness of all

management adjustments, involving first- and second lines of defence.


Management adjustments to ECL models (*)
in € million	2023	2022
Economic sector based adjustments	36	71
Inflation and interest rate increases / second-order impact adjustments	351	334
Mortgage portfolio adjustments	126	105
Other post model adjustments	64	-57
Total management adjustments	577	453

The economic sector-based adjustments of €36 million as of 31 December 2023 (€71 million as at 31

December 2022) fully relates to Business Banking clients that have benefited from Covid-19 related

government support programmes in the Netherlands. In line with 2022, it became clearer during 2023 that

the Covid-19 pandemic had less impact than expected on the number of defaults in related sectors with

relatively high tax debt to be repaid; the economic sector-based management adjustment has therefore

been partially released. The remaining management adjustment is related to sectors with relatively high tax

debt to be repaid and is expected to materialise with delayed effect. The €10 million adjustment on the

livestock farming sector in the Netherlands that was also included in December 2022, related to nitrogen

reduction targets has been fully released following improved risk metrics.

ING has performed further assessment for both WB and Retail Banking on the impact of second-order

effects. The second-order adjustments as at December 2022 captured a wider range of indirect effects such

as supply chain issues, staffing shortages and high energy prices. In 2023, the risks from high inflation and

rapidly increasing interest rates became more apparent compared to other indirect effects, causing a shift

in focus of this adjustment. This resulted in an overall adjustment for inflation and interest rate increases of

€351 million in total as at 31 December 2023, of which €138 million (31 December 2022: €164 million)

relates to Retail Banking segments and €213 million (31 December 2022: €170 million) to the Wholesale

Banking segment.

As the credit risk models in Retail Banking generally assume that inflation and interest rate increases risks

materialise via other risk drivers such as GDP and unemployment rates with a delay, an overlay approach

was determined. The methodology considers debt-to-income ratios and the percentage of loans that are

expected to reprice within one year to timely estimate the expected credit losses related to reduced

repayment capacity and affordability for private individuals and business clients in the Retail Banking

segment.

In Wholesale Banking, the IFRS 9 credit risk models mostly leverage on GDP growth as a generic

macroeconomic variable. High inflation and rapidly increasing interest rates however trigger economic

heterogeneity (i.e. some businesses benefit, while others suffer), as such the current circumstances are

expected to cause more defaults than normally predicted using GDP growth. A sector-based heatmap

approach was used to adjust the probability of default for clients in sectors that are expected to be

significantly impacted by high inflation and increased interest rates, including refinancing risk. The

adjustment is predominantly visible in the commercial real estate sector and reflected in Stage 1 and Stage

The overall mortgage portfolio adjustment as at 31 December 2023 increased to €126 million (31 December

2022: €105 million), as an adjustment of €115 million has been recognised in 2023 following new insights

from a risk segmentation model that captures affordability, repayment and refinancing risk on performing

mortgage customers with a bullet loan in the Netherlands.

The mortgage portfolio adjustment that relates to significant increase of house prices was reduced to €11

million as at 31 December 2023, coming from €105 million as at December 2022. This decrease is reflecting

the decline in house prices in various countries, subsequent materialisation into increased model-based ECL

as well as an improved market outlook on the recovery value of residential real estate. ING still recognises a

management adjustment related to house prices in Stage 2 and Stage 3 on the mortgage portfolios in

Germany to maintain an appropriate level of ECL. The management adjustments are determined by

calculating the impact of lower house prices on loan-to-value (LTV) and loss given default (LGD).

Other post-model adjustments (PMAs) 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 can result from both regular model maintenance and

ING’s multi-year programme to update ECL models for the definition of default. 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 PMAs because of model updates that have been

implemented, and ii) new PMAs recognised for new redevelopments and recalibrations.

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 December 2023 (*)
		2024	2025	2026	Un-weighted ECL (€ mln)	Probability -weighting	Reportable ECL (€ mln)1
Netherlands Upside scenario	Real GDP	1.3	3.3	2.8	214	20%	310
	Unemployment	3.7	3.3	3.3
	HPI	10.4	11.2	4.0
Baseline Scenario	Real GDP	0.8	1.6	1.5	282	60%
	Unemployment	4.1	4.3	4.5
	HPI	0.9	3.0	3.9
Downside scenario	Real GDP	-1.7	-1.2	0.1	487	20%
	Unemployment	5.9	7.2	8.1
	HPI	-10.9	-7.4	3.7
Germany Upside scenario	Real GDP	1.4	3.1	1.6	472	20%	525
	Unemployment	2.6	2.0	1.7
	HPI	0.9	6.6	8.0
Baseline Scenario	Real GDP	0.5	1.3	1.2	513	60%
	Unemployment	3.0	3.0	3.0
	HPI	-1.4	3.4	4.5
Downside scenario	Real GDP	-2.4	-1.4	0.3	615	20%
	Unemployment	4.5	5.2	5.5
	HPI	-6.0	-0.8	0.4
Belgium Upside scenario	Real GDP	1.5	2.7	2.3	568	20%	619
	Unemployment	5.3	5.0	4.9
	HPI	1.3	5.6	4.5
Baseline Scenario	Real GDP	0.9	1.5	1.8	604	60%
	Unemployment	5.6	5.5	5.4
	HPI	0.4	5.2	3.9
Downside scenario	Real GDP	-1.3	-0.2	1.2	713	20%
	Unemployment	7.3	8.0	7.9
	HPI	-2.2	3.9	2.6
United States Upside scenario	Real GDP	1.8	3.2	3.4	102	20%	165
	Unemployment	4.1	3.3	3.1
	HPI	0.6	8.7	8.7
Baseline Scenario	Real GDP	0.9	1.9	2.1	144	60%
	Unemployment	4.5	4.5	4.4
	HPI	-0.7	3.5	3.3
Downside scenario	Real GDP	-1.3	-1.4	-0.1	292	20%
	Unemployment	6.6	8.2	8.8
	HPI	-4.2	-2.7	-3.0
1Excluding management adjustments.


Sensitivity analysis as at December 2022 (*)
		2023	2024	2025	Un-weighted ECL (€ mln)	Probability -weighting	Reportable ECL (€ mln)1
Netherlands Upside scenario	Real GDP	2.2	2.3	2.9	274	20%	381
	Unemployment	4.0	3.9	3.8
	HPI	13.0	11.8	2.5
Baseline Scenario	Real GDP	0.2	1.4	1.8	349	60%
	Unemployment	4.5	4.8	4.9
	HPI	3.7	3.7	2.4
Downside scenario	Real GDP	-4.2	0.7	0.9	583	20%
	Unemployment	6.4	7.8	8.7
	HPI	-8.0	-6.5	2.2
Germany Upside scenario	Real GDP	1.7	2.3	1.8	606	20%	745
	Unemployment	2.6	2.2	1.8
	HPI	0.6	3.9	6.2
Baseline Scenario	Real GDP	-0.7	1.4	1.5	726	60%
	Unemployment	3.2	3.1	3.1
	HPI	-1.8	0.9	2.7
Downside scenario	Real GDP	-4.8	0.1	1.0	942	20%
	Unemployment	4.8	5.3	5.6
	HPI	-6.2	-3.3	-1.4
Belgium Upside scenario	Real GDP	1.7	2.1	2.1	535	20%	596
	Unemployment	5.5	5.5	5.3
	HPI	2.3	2.6	3.1
Baseline Scenario	Real GDP	—	1.6	1.8	584	60%
	Unemployment	6.1	6.3	6.1
	HPI	1.4	2.2	2.5
Downside scenario	Real GDP	-3.2	1.0	1.5	692	20%
	Unemployment	7.5	8.5	8.4
	HPI	-1.2	0.9	1.2
United States Upside scenario	Real GDP	3.0	1.5	3.4	100	20%	221
	Unemployment	3.4	2.8	2.5
	HPI	3.7	7.4	8.1
Baseline Scenario	Real GDP	0.2	1.1	2.3	188	60%
	Unemployment	4.3	4.4	3.9
	HPI	2.5	2.2	2.8
Downside scenario	Real GDP	-4.1	0.2	0.6	442	20%
	Unemployment	6.4	7.7	8.2
	HPI	-1.2	-3.8	-3.5
1 Excluding management adjustments.

When compared to the sensitivity analysis of 2022, the macroeconomic inputs for 2023 are somewhat

more favourable and for 2024 less favourable as the lagged impact of monetary tightening is still feeding

through to the real economy. The sensitivities for 2022 contain half-widened dispersion around the upside

and downside scenarios, whereas half-widened dispersion was removed for these scenarios for the 2023

sensitivity analysis following a continued decrease in forecast uncertainty.

On a total ING level, the unweighted model ECL for all collective provisioned clients in the upside scenario

was €2,510 million, in the baseline scenario €2,802 million and in the downside scenario €3,668 million. This

reconciles as follows to the reported ECLs:


Reconciliation of model (reportable) ECL to total ECL (*)
in € million	2023	2022
Total reportable collective provisions	2,856	3,209
ECL from individually assessed impairments	2,406	2,439
ECL from management adjustments	577	453
Total ECL	5,839	6,101

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 since initial origination or purchase. ING considers the credit risk of an asset

to have significantly increased when either a threshold for absolute change in lifetime probability of default

(PD) or a relative change in lifetime PD is reached.

It should be noted that the lifetime PD thresholds are not the only drivers of stage allocation. An asset can

also change stages as a result of other triggers, such as having over 30 days arrears, being on a watch list or

being forborne. Refer to section 1.5.6 of Note 1 ‘Basis of preparation and significant accounting policies’ for

an exhaustive list. Furthermore, this analysis is rudimentary in the sense that other parameters would

change when an asset changes stages.

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 expert-based thresholds for the absolute change in lifetime PD vary between

75bps for Retail portfolios, 100bps for WB and 250bps for SMEs, based on the characteristics of the specific

portfolio. ING is in the process of refining the thresholds on a portfolio level. These have already been

implemented for part of the portfolio, resulting in calibrated instead of expert-based absolute lifetime PD

thresholds.

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 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 that is optimised depending on the observed default rates and overall average riskiness

of the portfolio. While the scaling factor is associated with a whole portfolio/segment, the PD at origination

is facility-specific and, in this sense, the relative threshold may differ facility by facility.

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 2022 and year-end 2023.

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 (*)
	2023		2022
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	2.5	2.3	2.7	2.3
Consumer Lending	2.9	2.1	2.8	1.8
Business Lending	2.7	2.1	2.8	2.1
Governments and Financial Institutions	3.0	1.9	3.0	1.9
Other Wholesale Banking	2.8	1.8	2.8	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, is €1,412 million. To demonstrate the

sensitivity of the ECL to these PD thresholds bands, hypothetically solely applying the upside scenario would

result in total model ECL on performing assets of €1,054 million and a decrease in the Stage 2 ratio by

-0.5%-percentage point, while solely applying the downside scenario in our models would result in total

model ECL on performing assets of €2,290 million and an increase in the Stage 2 ratio by 3.8%-point.

Market risk

Introduction (*)

Market risk is the risk that movements in market variables, such as interest rates, equity prices, foreign

exchange rates, credit spreads and real estate prices negatively impact the bank’s earnings, capital, market

value or liquidity position. Market risk either arises through positions in banking books or trading books. The

banking book positions are intended to be held for the long term (or until maturity) or for the purpose of

hedging other banking book positions. The trading book positions are typically held with the intention of

short-term trading or to hedge other positions in the trading book. This means that financial instruments in

the trading books should be free of trade restrictions. Policies and processes are in place to monitor the

inclusion of positions in either the trading or banking book as well as to monitor the transfer of risk between

the trading and banking books.

ING recognises the importance of sound market risk management and bases its market risk management

framework on the need to identify, assess, control and manage market risks. The approach consists of five

recurring activities: risk identification, risk assessment, risk control, risk monitoring and risk reporting.

Governance (*)

A governance framework has been established defining specific roles and responsibilities of business

management units, market risk management units, and internal approval bodies per activity.

Supervision of market risk falls under the responsibility of the EB/MBB and is delegated to the ALCO function,

where ALCO Bank is the highest approval authority and sets the market risk appetite. ALCO Bank monitors

ING’s adherence to the risk appetite for market risk and sets additional limits where appropriate. These limits

are cascaded through the organisation through lower level ALCOs. This ALCO structure facilitates top-down

risk management, limit setting, limit monitoring and control of market risk.

FR maintains a limit framework in line with ING’s Risk Appetite Framework. The businesses are responsible

for adhering to the limits which are reviewed on an annual basis and are ultimately approved by the ALCO

Bank. Limit excesses are reported to senior management in line with the ALM Risk Appetite Statement

Setting procedure and Market Risk in the Trading Book Framework, upon which the business needs to act

accordingly. To adhere to the established limit framework, ING implements hedging and risk mitigation

strategies that range from the use of traditional market instruments, such as interest rate swaps, to more

sophisticated hedging strategies.

The organisational structure facilitates top-down risk management by recognising that risk taking and risk

management occur to a large extent at the regional/local level. Bottom-up reporting from regional/local

units to head office units allows each management level to assess the market risks relevant at the

respective levels.

Several committees govern communication between the parties involved in market risk management:

•The Market Risk Model Committee (MRMC), is the dedicated authority for the approval of all funding &

liquidity risk, market risk (includes banking and trading risk), counterparty credit risk and business risk

models and parameters for ING Bank within its mandate delegated by ALCO Bank.

•The Valuation Model Committee approves pricing models for trading and banking books.

Financial Risk provides risk reporting to the EB and MBB, the ALCO Bank and the senior executive

management of related business functions.

The following sections elaborate on the various elements of the risk management framework for:

•Market risk economic capital;

•Market risk in banking books;

•Market risk in trading books.

Market risk in banking books (*)

ING makes a distinction between the trading and banking (non-trading) books. Positions in banking books

originate from the market risks inherent in commercial products that are sold to clients, Group Treasury

exposures, and from the investment of our own funds (core capital). Both the commercial products and the

products used to hedge related market risk exposures are intended to be held until maturity, or at least for

the long term.

Risk transfer (*)

Market risks in the banking book are managed via the risk transfer process. In this process the interest rate,

FX, funding and liquidity risks are transferred from the commercial books through matched funding or

replication to Group Treasury, where centrally managed. The scheme below presents the transfer and

management process of market risks in the banking books.

Risk measurement (*)

The main concepts and metrics used for measuring market risk in the banking book are described below per

risk type.

Interest rate risk in banking book (*)

Interest rate risk in the banking book is defined as the exposure of a bank’s earnings, capital, and market

value to adverse movements in interest rates originated from positions in the banking book.

Governance (*)

The management of interest rate risk follows the Interest Rate Risk in the Banking Book (IRRBB) framework

as approved by ALCO Bank. This framework describes roles, responsibilities, risk metrics, and the policies and

procedures related to interest rate risk management. Furthermore, ALCO Bank reviews and sets the risk

appetite for interest rate risk on an annual basis. The risk appetite is translated into limits for the interest

rate risk metrics.

As a result of this framework, ING centralises interest rate risk management from commercial books (that

capture the products sold to clients) to globally managed interest rate risk books. This enables a clear

demarcation between commercial business results and results based on unhedged interest rate positions.

ING distinguishes between three types of activities that generate interest rate risk in the banking book:

•Investment of own funds;

•Commercial business;

•Group Treasury exposures including strategic interest rate positions.

Group Treasury is responsible for managing the investment of own funds (core capital). Capital is invested

for longer periods to contribute to stable earnings within the risk appetite boundaries set by ALCO Bank. The

main objective is to maximise the economic value of the capital investment book while having stable

earnings.

Commercial activities can result in linear interest rate risk, for example, tenors and duration of new

production and re-pricing of assets differ from those of liabilities. Also, interest rate risk can arise from

customer behaviour and/or convexity risk, depending on the nature of the underlying product

characteristics.

Customer behaviour risk is defined as the potential future (value) loss due to deviations in the actual

behaviour of clients versus the modelled behaviour with respect to the embedded options in commercial

products. General sources of customer behaviour risk, among other things, include the state of the

economy, competition, changes in regulation, legislation and tax regime, developments in the housing

market and interest rate developments.

From an interest rate risk perspective, commercial activities can typically be divided into the following main

product types: savings and current accounts (funds entrusted), demand deposits, mortgages and loans.

Savings and demand deposits are generally invested in such a way that both the value is hedged and the

sensitivity of the margin to market interest rates is minimised. The contractual nature of investments

(assets) implies that the adjustment to market rates (repricing of assets) is not immediate, therefore the

interest rate risk can arise with either positive or negative impact on the income. Interest rate risk is

modelled based on the stability of deposits and the pass-through rate. This takes account of different

elements, such as pricing strategies, volume developments and the level and shape of the yield curve.

Savings volumes are typically assumed to be relatively stable and less sensitive to rate changes.

Interest rate risk for mortgages arises due to prepayment or other embedded optionalities. In modelling this

risk, both interest-rate-dependent pre-payments and constant prepayments, are considered. Next to a

dependence on interest rates, modelled prepayments may include other effects such as loan-to-value,

seasonality and the reset date of the loan. In addition, the interest sensitivity of embedded offered rate

options may be considered.

Wholesale Banking loans typically do not experience interest-rate-dependent prepayment behaviour. These

portfolios are match-funded taking the constant prepayment model into account and typically do not

contain significant convexity risk. Wholesale Banking loans can have an all-in rate floor or a floor on a

reference rate.

Customer behaviour in relation to mortgages, loans, savings and demand deposits is modelled, based on

extensive research. However, the substantial change in the interest rate environment makes extensive

research more challenging than before and may increase model risk. Models are backtested and updated

when deemed necessary in an annual procedure. Model parameters and the resulting risk measures are

approved by (local) ALCO and are closely monitored on a monthly basis.

Linear risk transfers take place from commercial business books to the treasury book (Group Treasury), if

necessary, by using estimations of customer behaviour. The originating commercial business is ultimately

responsible for estimating customer behaviour, leaving convexity risk and (unexpected) customer behaviour

risk with the commercial business. Risk measurement and the risk transfer process take place at least

monthly. However, if deemed necessary, additional risk transfers can take place.

The commercial business manages the convexity risk that is the result of products that contain embedded

options, like mortgages. Here the convexity risk is defined as the optionality effects in the value due to

interest rate changes, excluding the first-order effects. In some cases, convexity risk is transferred from the

commercial books to treasury books using cap/floor contracts and swaptions.

In the following sections, the interest rate risk exposures in the banking books are presented. ING quantifies

risk measures from both earnings and value perspectives. Net interest income (NII)-at-Risk is used to provide

the earnings perspective and the net present value (NPV)-at-Risk figures provide the value perspective.

Please note that the interest rate risk that stems from the commercial business is assumed to be linearly

hedged but no additional corrective management actions are taken into account in the NPV-at-Risk

measure. In the NII-at-Risk measure, a more dynamic hedging process is taken into account.

During 2023, the following activities related to the risk measurement for IRRBB were performed:

•Annual review of the risk appetite for market risks in the banking book including further enhancements;

•Further assessment and development of sub-risk types, such as tenor basis risk, vega optionality risk and

client behaviour risk;

•Set up of standardised risk measurement related to global crisis risk;

•Annual review of the interest rates scenarios used for calculating NII-at-Risk and NPV-at-Risk;

•Annual savings/current account model updates;

•Annual update of parameters of prepayment models for market developments;

•Further enhancement of the IRRBB framework in relation to upcoming regulatory requirements (e.g.

anticipation on implementation and measurement of the upcoming regulatory metric NII SOT,

development of additional requirements coming forward from latest EBA guidelines);

•Further strengthening of customer behaviour risk and model risk frameworks

Net interest income (NII) at Risk (*)

The NII-at-Risk measures the impact of changing interest rates on the forecasted net interest income

(before tax) of the banking book, excluding the impacts of credit spread sensitivity, fees and fair value

impact. Future projected balance sheet developments are included in this risk metric. NII-at-Risk is a metric

that helps provide insight as to what extent ING's NII under alternative interest rates developments deviates

from what was assumed in our dynamic plan projections.

In its risk management, ING monitors the NII-at-Risk under a three-year timeframe. Interest rates are

stressed during the first year versus the prevailing curve, taking gradual changes over the first year. The rate

changes considered comprise both upward and downward scenarios, as well as parallel (equal movements

across the yield curve) and non-parallel scenarios.

The impact of changing interest rates on ING’s NII is predominantly caused by the following factors:

•Change in returns of (re-)investments of client deposits;

•Change in client deposit rates (mainly savings), (partially) tracking changes in market interest rates;

•Change in the amortization profile of mortgages, due to an increase or decrease in expected

prepayments;

•Higher/lower returns of (re-)investments of capital investment;

•Open interest rate positions, leading to changes in return because of different market rates;

•Assumed volume development of the balance sheet in line with ING's dynamic plan.

For projecting the change in client deposit rates, ING uses a client rate model that describes the relation to

market interest rates and client deposit rates. The model is calibrated under a range of interest rate

scenarios. Per scenario the actual change in client deposit rates may deviate from this calibrated model. The

actual NII development of customer deposits may, indeed, differ from the provided scenarios, depending on,

amongst others, actual interest rate and savings client rate evolution, as well as changes to ING’s balance

sheet composition such as net deposit growth and relative share of savings deposits and non-remunerated

current accounts.

The NII-at-Risk figures in the table below reflect a parallel, linear interest rate movement during a year

('ramped') under the assumption of balance sheet developments in line with the ING's dynamic plan with a

time horizon of one year. The majority of the risk comes from fixed-rate positions, most notably non-

remunerated current accounts and variable-rate savings accounts.

The NII-at-Risk is primarily driven by the difference in sensitivity of client liabilities, mainly savings, versus

the sensitivity of client assets and investments to rate changes. The investment of own funds only impacts

the earnings sensitivity marginally, as only a relatively small part has to be (re)invested within the one-year

horizon.


NII-at-Risk banking book per currency - year one (*)
in € million	2023		2022
	Ramped, unfloored		Ramped, unfloored
	parallel ▼	parallel ▲	parallel ▼	parallel ▲
By currency
Euro	-165	155	-119	114
US dollar	-12	12	-1	2
Other	-62	69	-23	27
Total	-239	236	-142	142
EUR ramped (unfloored) is at +/- 110bps in 1 year (2022: +/-100bps)
USD ramped (unfloored) is at +/- 110bps in 1 year (2022: +/-120bps)

The change in NII under a declining and upward interest rate scenarios may not be equal. This is due to

different expected reactions in prepayment behaviour of mortgages and different pricing developments of

commercial loans and deposits products (mainly savings). This is caused by embedded options, explicit or

implicit pricing floors and other (assumed) pricing factors.

Year-on-year variance analysis (*)

In our customer deposit composition current accounts decreased and term deposits increased. Over 2023

the one-year asset repricing versus liability repricing increased, leading to a higher NII-at-Risk.

In 2023 central banks tightened monetary conditions, a continuation of a trend started in 2022 to counter

high inflation. The interest rates, however, stabilised in the second half of the year as inflation started to

ease. ING applied a dynamic hedging process, by which interest rate risk was transferred from the business

to Group Treasury and subsequently hedged in the markets. This process mitigates interest rate risk

resulting in a lower sensitivity for rate changes of ING's NII. However, the main drivers of a potential change

of NII sensitivity are balance sheet developments, specifically relating to mortgages, loans and savings. In

the eurozone, mortgage production was impacted by an increase in interest rates. Next to the impact on

new production, the prepayment incentive generally decreased due to the increase in interest rates. The

funds entrusted volume did not change significantly. The impact of explicit and implicit floors on both rates

of client assets and savings phased out in the course of the year on the back of the interest rate increases.

Pre-existing hedges, as executed by Group Treasury, were also adjusted continuously throughout the year

to hedge any interest rate risk coming from higher interest rates. Furthermore, ING’s investment of own

funds took place against a lower duration reducing sensitivity. Excluding Model Risk, the total NII-at-Risk

remains relatively limited in comparison to ING’s total interest income.

Net Present Value (NPV) at Risk (*)

NPV-at-Risk measures the impact of changing interest rates on the value of the positions in the banking

book. The NPV-at-Risk is defined as the outcome of an instantaneous increase or decrease in interest rates

from applying currency-specific scenarios. The NPV-at-Risk asymmetry between the downward and upward

shock is mainly caused by convexity risk in the mortgage and savings portfolio.

The full value impact cannot be directly linked to the financial position or profit or loss account, as fair value

movements in banking books are not necessarily reported through the profit or loss account or through

other comprehensive income (OCI). The changes in value are expected to materialise over time in the profit

and loss account if interest rates develop according to forward rates throughout the remaining maturity of

the portfolio. The majority of the risk comes from the investments of own funds and from positions

exhibiting negative convexity due to embedded optionality (most notably variable rate savings rate and

fixed rate mortgages).


NPV-at-Risk banking books per currency (*)
in € million	2023		2022
	unfloored		unfloored
	parallel ▼	parallel ▲	parallel ▼	parallel ▲
By currency
Euro	-291	-645	392	-926
US dollar	186	-178	137	-147
Other	131	-146	66	-79
Total	27	-969	594	-1,153
EUR ramped (unfloored) is at +/- 110bps (2022: +/-100bps)
USD ramped (unfloored) is at +/- 110bps (2022: +/-120bps)

Year-on-year variance analysis (*)

The overall NPV sensitivity remained limited in 2023, reflecting of proper risk transfer and hedging process.

The worst case scenario, parallel up, remained relatively unchanged. Most of the year-to-year move is

coming from mortgages, partly offset by savings and derivatives from hedging activities.

IBOR transition (*)

In line with the recommendations of the Financial Stability Board, a fundamental review of important

interest rates benchmarks has been undertaken. Some interest benchmarks have been reformed, while

others have or will be replaced by risk-free rates (RFR) and discontinued. USD LIBOR in its current form

ceased on 30 June 2023, whereas the cessation of GBP, CHF, JPY, and EUR LIBOR rates occurred on 31

December 2021.

To support these changes, the financial sector has issued several guidance papers and other initiatives to

help phase the transition.

To facilitate the transition away from USD LIBOR, for new USD contracts, ING started using the

recommended alternative rates based on SOFR in 2022. Also, during 2022 and 2023, ING sought to ensure

that existing loan and derivative contracts were either transitioned to alternative rates or transition

arrangements agreed, such as taking steps to ensure a large portion of the derivative portfolio was covered

by ISDA fallbacks. Despite extensive and timely communication on the desirability of fully agreeing

transition arrangements before 30 June 2023, some clients have agreed to complete the required work

before the first interest reset date after cessation. A limited number of clients in restructuring or those

subject to sanctions need to rely on existing fallback language or synthetic LIBOR.

Due to the discontinuation of this important rate, ING, its customers, and the financial services industry have

faced and continue to face a number of risks. These risks include legal, financial, operational, reputational

and conduct risk. Legal risks are related to any required changes to existing transactions. Financial risks may

arise due to declining liquidity and may impact a contract directly or the ability to hedge the risks in that

contract. Operational risks arise due to the requirement to adapt IT systems, trade reporting infrastructure

and operational processes. Conduct risk also plays a role, as renegotiation of loan contracts requires active

engagement from all parties to a contract and may lead to negotiations concentrated in a period close to

actual cessation. ING continues to work with the very limited number of clients that are yet to complete the

USD LIBOR transition.

The progress of the IBOR transitioning between 2018 and 2023 was tracked in the global ING IBOR

programme, governed by business line steering committees, which reported to a central IBOR steering

committee. The programme coordinated the actions necessary to manage the required changes to internal

processes and systems, including pricing, risk management, legal documentation, hedge arrangements, as

well as the impact on customers. The limited amount of remaining USD LIBOR contracts continues to be

monitored within the commercial business lines following the closure of the bank-wide IBOR programme in

November 2023. The ING Benchmark Committee continues to monitor market developments and reform

plans for other rates, to anticipate the impact on any related risks.

One such development concerns the plans published by the Polish National Working Group, which advises

the market to be ready for a cessation of WIBOR and WIBID reference rates at the end of 2027 (originally

expected in 2025, but in the last quarter of 2023 the cessation date was postponed to the end of 2027) with

the offering of financial products using the new benchmark (Warsaw Interest Rate Overnight or WIRON) to

progress gradually and no new products using WIBOR and WIBID beyond 1 July 2024. The WIBOR rates are

used in several of our lending and derivative products, and hence a project team has been established to

manage the transition. WIBOR transition is especially important for our Polish subsidiary ING Bank Slaski S.A.

with a significant amount of Polish zloty-denominated assets and liabilities including derivatives that are

continuously rebalanced to hedge the risk exposures.

The tables below summarise the approximate gross exposures of ING that have yet to transition related to

USD LIBOR and WIBOR. For WIBOR, as of 31 December 2023, they exclude exposures expiring before the

transition date 31 December 2027 and of 31 December 2022 they exclude exposures expiring before the

previously expected transition date 1 January 2025. Therefore, WIBOR exposures are not directly

comparable between 31 December 2023 and 31 December 2022 as a consequence of the recent

developments in the Polish National Working Group.


Non derivative Financial instruments to transition to alternative benchmarks (*)
in € million at 31 December 2023	Financial Assets non- derivative	Financial Liabilities non-derivative	Off balance sheet commitments
	Carrying value	Carrying value	Nominal value
By benchmark rate
USD LIBOR	915	16	9
WIBOR	18,064		1,021
Total	18,979	16	1,030


Non derivative Financial instruments to transition to alternative benchmarks (*)
in € million at 31 December 2022	Financial Assets non- derivative	Financial Liabilities non-derivative	Off balance sheet commitments
	Carrying value	Carrying value	Nominal value
By benchmark rate
USD LIBOR	30,040	1,637	7,644
WIBOR	22,154		1,411
Total	52,194	1,637	9,055

The total of non-derivative financial assets linked to USD LIBOR is reduced from €30,040 million on 31

December 2022 to €915 million on 31 December 2023. The majority of the non-derivative financial assets

exposure on 31 December 2023 are related to contracts using synthetic USD LIBOR up until the transition to

SOFR is complete during 2024. In addition, ING reduced its committed undrawn credit facilities linked to USD

LIBOR from €7,644 million on 31 December 2022 to €9 million on 31 December 2023. The total of non-

derivative financial liabilities linked to USD LIBOR is reduced from €1,637 million on 31 December 2022 to

€16 million on 31 December 2023. The remaining non-derivative financial instruments linked to USD LIBOR

are expected to transition before the next interest rate reset date. Therefore, the remaining exposure to USD

LIBOR is expected to reduce further during the first half of 2024.


Derivative Financial instruments to transition to alternative benchmarks (*)
	31 December 2023	31 December 2022
in € million	Nominal value	Nominal value
By benchmark rate1
USD LIBOR	151	495,318
WIBOR	77,238	136,318
Total	77,388	631,636

1 For cross-currency swaps all legs of the swap are included that are linked to a main IBOR that is significant to ING.

In addition to the amounts in the table above, ING transitioned the interest rate swaptions that referred to

the USD LIBOR ICE swap rate (nominal value on 31 December 2022: €10,810 million). The transition of these

contracts was in general governed by a specific ISDA protocol.

Derivative financial instruments linked to USD LIBOR were reduced from €495,318 million on 31 December

2022 to only €151 million on 31 December 2023. The majority of derivatives linked to USD LIBOR rates were

transacted with clearing houses and transitioned through a standardised exercise during the second quarter

of 2023. For non-centrally cleared derivatives, the main transition occurred using the ISDA IBOR fallback

arrangements. The majority of the remaining derivative financial instruments linked to USD LIBOR are

related to contracts using synthetic USD LIBOR and linked to non-derivative financial assets that are

expected to transition before the next interest rate reset date during 2024. Therefore, a steady reduction of

these last few USD LIBOR contracts is expected during the first half of 2024.

Given that IBOR reform may have various accounting implications, the International Accounting Standards

Board (IASB) has undertaken a two-phase project:

• Phase 1 addresses those issues that affect financial reporting before the replacement of an existing

benchmark. This allows ING to apply a set of temporary exceptions to continue hedge accounting even

when there is uncertainty about contractual cash flows arising from the reform. Under these temporary

exceptions, interbank offered rates are assumed to continue unaltered for the purposes of hedge

accounting until such time as the uncertainty is resolved.

• Phase 2 focuses on issues that may affect financial reporting when the existing benchmark rate is

reformed or replaced. Phase 2 amendments to IFRS relate mainly to accounting for changes in the basis for

determining the contractual cash flows of financial assets and liabilities due to the IBOR reform and impact

on hedge accounting when an existing benchmark rate is reformed or replaced with an alternative risk-free

rate.

Specifically, Phase 2 amendments require that the effective interest rate on debt financial instruments is

adjusted, and hedge accounting continues on transition to risk free rates, but only to the extent that the

modifications made to financial instruments are those necessary to implement the IBOR reform and that

the new basis for calculating cash flows is ‘economically equivalent’ to the previous basis. By applying these

mandatory amendments, ING Group avoids recognising modification gains and losses on debt instruments

that would otherwise be required in the absence of Phase 2 amendments (changes to debt instruments

resulting from IBOR reform are treated as a reset to the instrument’s variable interest rate). In addition, ING

Group avoids hedge accounting discontinuations when modifying both hedged items and hedging

instruments (and related hedge documentation) as a consequence of IBOR reform that would otherwise be

required in the absence of Phase 2 amendments.

As explained above, Phase 1 and Phase 2 IBOR amendments to IFRS, amongst other changes, provide

specific hedge accounting reliefs that allow hedge accounting relationships to continue when IBOR Reform is

ongoing. Phase 1 reliefs cease to apply when uncertainty arising from IBOR reform is no longer present with

respect to the timing and amount of the IBOR-based cash flows of the relevant instruments. It is ING Group’s

policy to cease to apply Phase 1 reliefs when the applicable contract (either hedging instrument or hedged

item) is actually modified. As a result, for these hedge accounting relationships the applicable Phase 1 reliefs

ceased to apply and Phase 2 became applicable. Refer to section 1.5.4 of Note 1 ‘Basis of preparation and

material accounting policy information’ for more information on the Phase 1 and Phase 2 amendments.

Furthermore, hedging relationships are being amended to incorporate the new benchmark rates. During

2023, ING focused on USD LIBOR contracts and all hedging relationships have been amended to incorporate

the new benchmark rates and do no longer reference USD LIBOR rates.

On 31 December 2023, Phase 1 reliefs are applicable to WIBOR indexed fair value and cash flow hedge

accounting relationships as there is uncertainty arising from the WIBOR reform with respect to the timing

and the amount of the underlying cash flows that the Group is exposed to. Therefore, for WIBOR financial

instruments designated in hedge accounting the applicable Phase 1 reliefs will continue to apply until the

relevant contract is modified. At that point in time, Phase 2 reliefs will become applicable. For these affected

fair value and cash flow hedge relationships ING assumes that the WIBOR based cash flows from the

hedging instrument and hedged item will remain unaffected.

The same assumption is used to assess the likelihood of occurrence of the forecast transactions that are

subject to cash flow hedges. The hedged cash flows in cash flow hedges directly impacted by the WIBOR

reform still meet the highly probable requirement, assuming the WIBOR benchmark on which the hedged

cash flows are based is not altered as a result of the reform.

The total gross notional amounts of hedging instruments that are used in the ING's hedge accounting

relationships for which the Phase 1 amendments to IAS39 were applied are:


Notional amounts of Hedging instruments (*)
	31 December 2023	31 December 2022
in € million	Nominal value	Nominal value
By benchmark rate
USD LIBOR		28,316
WIBOR	89,338	57,774

As at 31 December 2023, all USD LIBOR hedging relationships have been amended to incorporate the new

benchmark rates and do no longer reference USD LIBOR rates. At 31 December 2022 approximately 89% of

the notional amounts for USD LIBOR had a maturity date beyond the transition date 30 June 2023.

Approximately 29% of the notional amounts for WIBOR have a maturity date beyond the new transition

date 31 December 2027. At 31 December 2022, approximately 71% of the notional amounts for WIBOR had

a maturity date beyond the previously expected transition date of 1 January 2025. The WIBOR amounts are

not directly comparable between 31 December 2023 and 31 December 2022 as a consequence of the

recent postponement of the cessation of WIBOR by the Polish National Working Group.

The notional amounts of the derivative hedging instruments provide a close approximation of the extent of

the risk exposure ING manages through these hedging relationships.

Credit spread risk in banking books (*)

Credit spread risk is defined as risk driven by the changes of the market price for credit risk, for liquidity and

potentially other characteristics of credit-risky instruments, which is not captured by another existing

prudential framework such as IRRBB or by expected credit/(jump-to-) default risk.

EBA guidelines

The updated guidelines on credit spread risk in the banking book (CSRBB) became effective on 31 December

2023. Following the EBA guidelines, the scope in terms of positions and metrics has been reviewed and

updated during 2023. Metrics used are NPV-at-Risk, NII-at-Risk and Market Value Changes-at Risk and view

the positions across different accounting treatments.

Governance

The management of credit spread risk follows the CSRBB framework as approved by ALCO Bank. This

framework describes roles, responsibilities, risk metrics, and the policies and procedures related to credit

spread risk management. Furthermore, ALCO Bank reviews and sets the risk appetite for credit spread risk

on an annual basis. The risk appetite is translated into limits for the risk metrics.

Foreign exchange (FX) risk in banking books (*)

FX exposures in banking books result from core banking business activities (business units doing business in

currencies other than their base currency), foreign currency investments in subsidiaries (including realised

net profit and loss), and strategic equity stakes in foreign currencies. The policy regarding these exposures is

briefly explained below.

Governance – Core banking business (*)

Every business unit hedges the FX risk resulting from core banking business activities into its base currency

to prevent volatility in profit and loss. Consequently, assets and liabilities are matched in terms of currency,

within certain friction limits.

Governance – FX translation result (*)

ING’s strategy is to protect the CET1 ratio against adverse impact from FX rate fluctuations, while limiting

the volatility in the profit and loss account due to this CET1 hedging and limiting the RWA impact under the

regulatory framework. Hedge accounting is applied to the largest extent possible. Taking this into account,

the CET1 ratio hedge can be achieved by deliberately taking foreign currency positions equal to certain

target positions, such that the CET1 capital and risk-weighted assets are equally sensitive in relative terms

to changing FX rates.

Risk profile – FX translation result (*)

The following table presents the currency exposures in the banking books for the most important currencies

for the FX translation result. Positive figures indicate long positions in the respective currency. As a result of

the strategy to hedge the CET1 ratio an open structural FX exposure exists.

To measure the volatility of the CET1 ratio from FX rate fluctuations, different metrics are used including the

CET1 Ratio-at-Risk. The impact is controlled via the Solvency and Market Risk Banking Book RAS.


Foreign currency exposures banking books (*)
in € million	Foreign Investments		Hedges		Net exposures
	2023	2022	2023	2022	2023	2022
US Dollar	10,337	10,470	-3,416	-2,376	6,921	8,093
Pound Sterling	1,659	1,364	-156	-58	1,503	1,306
Polish Zloty	3,976	2,714	-1,254	-321	2,722	2,393
Australian Dollar	3,620	3,781	-2,273	-2,673	1,346	1,108
Turkish Lira	517	750	0	0	517	750
Chinese Yuan	1,815	1,871	-348	0	1,466	1,871
Russian Rouble	375	391	0	0	375	392
Romanian Leu	895	860	-134	-154	761	706
Thai Baht	1,128	1,109	-697	-699	431	410
Other currency	3,704	3,771	-2,897	-2,908	806	863
Total	28,024	27,081	-11,175	-9,189	16,849	17,892

*The FX sensitivity is expressed as the FX spot equivalent position.

Equity price risk in banking books (*)

Governance (*)

ING maintains a portfolio with substantial equity exposure in its banking books. Local offices are responsible

for the management of the equity investment positions. Financial Risk is responsible for monitoring the

regulatory capital for equity investments on a monthly basis and acts independently from ING/local

management when monitoring these positions.

Risk profile (*)

Equity price risk arises from the possibility that an equity security’s price will fluctuate, affecting the values

of the equity security itself as well as other instruments whose values react similarly to the particular

security, a defined basket of securities, or a securities index. ING’s equity exposure mainly consists of the

investments in associates and joint ventures of €1,509 million (2022: €1,500 million) and equity securities

held at fair value through other comprehensive income (FVOCI) of €1,885 million (2022: €1,887 million).The

value of equity securities held at FVOCI is directly linked to equity security prices with increases/decreases

being recognised in the revaluation reserve. Investments in associates and joint ventures are measured in

accordance with the equity method of accounting and the balance sheet value is therefore not directly

linked to equity security prices. The equity sensitivity is expressed as the equity position.

Year-on-year variance analysis (*)

In 2023, the revaluation reserve equity securities decreased by €34 million from €1,187 million to €1,152

million mainly due to revaluation of the shares in Bank of Beijing with €-24 million. In 2023, the equity

securities at fair value through OCI decreased slightly by €2 million.


Revaluation reserve equity securities at fair value through other comprehensive income (*)
in € million	2023	2022
Positive re-measurement	1,158	1,190
Negative re-measurement	-6	-4
Total	1,152	1,187

Market risk in trading books (*)

Within the trading portfolios, the positions are maintained in the financial markets. These positions are often

a result of transactions with clients and may benefit from short-term price movements. In 2023, ING

continued its strategy of undertaking trading activities to develop its client-driven franchise and deliver a

differentiating experience by offering multiple market and trading products.

Governance (*)

The Financial Markets Risk Committee (FMRC) is the market risk committee that, within the risk appetite set

by the ALCO Bank, sets the market risk limits both on an aggregated level and on a desk level. The FMRC has

delegated authority from ALCO Bank for the management of market risk related to all trading and banking

book activities within Financial Markets (FM). Financial Risk/ Trading Risk Management (FR/ TRM) advises both

FMRC and ALCO Bank on the market risk appetite of the trading activities.

With respect to the trading portfolios, TRM focuses on the management of market risks of Wholesale

Banking (mainly Financial Markets) as this is the only business line within ING where trading activities take

place. Trading activities include facilitation of client business and market making. TRM is responsible for the

development and implementation of trading risk policies and risk measurement methodologies, and for

reporting and monitoring risk exposures against approved trading limits. TRM also reviews trading mandates

and global limits, and performs the gatekeeper role in the product review process (PARP).

Risk measurement (*)

ING uses a comprehensive set of methodologies and techniques to measure market risk in trading books:

Value at Risk (VaR) and Stressed Value at Risk (SVaR), Incremental Risk Charge (IRC), and stress testing.

Systematic validation processes are in place to validate the accuracy and internal consistency of data and

parameters used for the internal models and modelling processes.

Value at Risk (*)

TRM uses the historical simulation VaR methodology (HVaR) as its primary risk measure. The HVaR for

market risk quantifies, with a one-sided confidence level of 99 percent, the maximum overnight loss that

could occur in the trading portfolio of ING due to changes in risk factors (e.g. interest rates, equity prices,

foreign exchange rates, credit spreads, implied volatilities) considering the positions remains unchanged for

a time period of one day.

Next to general market movements in these risk factors, HVaR also takes into account market data

movements for specific moves in, for example, the underlying issuer or securities. A single model which

diversifies general and specific risk is used. In general, a full revaluation approach is applied, while for a

limited number of linear trading positions and risk factors in commodity and equity risk classes a sensitivity-

based approach is applied. The potential impact of historical market movements on today’s portfolio is

estimated, based on equally weighted observed market movements of the previous year (260 business

days). When simulating potential movements in risk factors, depending on the risk factor type, either an

absolute or a relative shift is used.

The data used in the computations is updated daily. ING uses HVaR with a one-day horizon for internal risk

measurement, management control, and backtesting, and HVaR with a 10-day horizon for determining

regulatory capital. To compute HVaR with a 10-day horizon, the one-day risk factor shifts are scaled by the

square root of 10 and then used as an input for the revaluation. The same model is used for all legal entities

within ING with market risk exposure in the trading portfolio.

Limitations (*)

HVaR has some limitations: HVaR uses historical data to forecast future price behaviour, but future price

behaviour could differ substantially from past behaviour. Moreover, the use of a one-day holding period (or

10 days for regulatory capital calculations) assumes that all positions in the portfolio can be liquidated or

hedged in one day. In periods of illiquidity or market events, this assumption may not hold. Also, the use of

a 99 percent confidence level means that HVaR does not take into account any losses that occur beyond

this confidence level.

Backtesting (*)

Backtesting is a technique for the ongoing monitoring of the plausibility of the HVaR model in use. Although

HVaR models estimate potential future trading results, estimates are based on historical market data. In a

backtest, the actual daily trading result (excluding fees and commissions) is compared with the one-day

HVaR.

In addition to using actual results for backtesting, ING also uses hypothetical results, which exclude the

effects of intraday trading, fees, and commissions. When an actual or a hypothetical loss exceeds the HVaR,

an ‘outlier’ occurs. Based on ING’s one-sided confidence level of 99 percent, an outlier is expected once in

every 100 business days.

On an overall level in 2023, there was one outlier for hypothetical P&L and zero outliers for actual P&L. The

hypothetical outliers occurred during the past year concentrated in the first quarter of 2023, mainly due to

the increased market volatility arising from major American banks being collapsed.

Stressed HVaR (*)

The stressed HVaR (SVaR) is intended to replicate the HVaR calculation that would be generated on the

bank’s current portfolio with inputs calibrated to the historical data from a continuous 12-month period of

significant financial stress relevant to the bank’s portfolio.

To calculate SVaR, ING uses the same model that is used for 1DHVaR, with a 10-day horizon. The data for

the historical stress period used currently includes the height of the credit crisis around the fall of Lehman

Brothers (2008-2009), and this choice is reviewed regularly. The historical data period is chosen so that it

gives the worst scenario loss estimates for the current portfolio. The same SVaR model is used for

management purposes and for regulatory purposes. The same SVaR model is used for all legal entities

within ING with market risk exposure in the trading portfolio.

Incremental risk charge (*)

The incremental risk charge (IRC) for ING is an estimate of the default and migration risks for credit products

(excluding securitisations) in the trading book, over a one-year capital horizon, with a 99.9% confidence

level. Trading positions (excluding securitisations) of ING, which are subject to specific interest rate risk

included in the internal model approach for market risk regulatory capital, are in scope of the IRC model. By

model choice, equity is excluded from the model. For the calculation of IRC, ING performs a Monte Carlo

simulation based on a multi-factor t-copula. In the multi-factor IRC model the supervisory asset correlations

are no longer applicable and the calibration of the correlations is based on historical market data. The rating

change is simulated for all issuers over the different liquidity horizons (i.e. time required to liquidate the

position or hedge all significant risks) within one year. Movements across different rating categories and

probabilities of default are governed by a credit-rating transition matrix. An internal transition matrix along

with internal LGDs is used, to comply with the consistency requirement. The financial impact is then

determined for the simulated migration to default, or for the simulated migration to a different rating

category, based on LGD or credit spread changes, respectively.

The liquidity horizon has been set to the regulatory minimum of three months for all positions in scope. ING

reviews the liquidity horizons on a yearly basis, based on a structured assessment of the time it takes to

liquidate the positions in the trading portfolio.

Stress testing and event risk (*)

Stress testing is a valuable risk management tool. In addition to the bank-wide stress test framework as

described in the stress-testing section, Trading Risk Management performs stress tests specific to the

trading book with various frequencies. ING went live with a new Trading Book Stress Testing model in 2023,

replacing the previously used Event Risk model. With the new model, the trading book stress tests evaluate

the impact on the bank’s trading book under severe but plausible stress scenarios, using full revaluation

approach. The framework is based on historical as well as hypothetical scenarios. The stress result is an

estimate of the profit and loss caused by a potential event and its worldwide impact for ING. The results of

the stress tests are used for decision-making aimed at maintaining a financially healthy going-concern

institution after a severe event occurs.

In stress scenarios, shocks are applied to prices (credit spreads, interest rates, equity, commodities, and FX

rates) and volatilities. Depending on the type of the stress test, additional scenario assumptions can be

made, for example on correlations, dividends, or recovery rates. The structural scenarios are defined to

cover market moves in various directions and capture different asset class correlations. Scenarios are

calculated using full revaluation approach. The worst scenarios are determined for each product line,

business line and super business line, and compared against limits.

Sensitivities (*)

As part of the risk monitoring framework, TRM actively monitors the sensitivities of the trading portfolios.

Sensitivities measure the impact of movements in individual market risk factors (foreign exchange rates,

interest rates, credit spreads, equity and commodity prices) on profit and loss results of the trading

positions and portfolios.

The following tables show the five largest trading positions in terms of sensitivities to foreign exchange,

interest rate and credit spread risk factor movements. These largest exposures also reflect concentrations of

risk in FX risk per currency, interest rate risk per currency, and credit spread risk per country, rating and

sector. Due to the nature of the trading portfolios, positions in the portfolios can change significantly from

day to day, and sensitivities of the portfolios can change daily accordingly.


Most important foreign exchange year-end trading positions (*)
in € million	2023		2022
Foreign exchange		Foreign exchange
Japanese Yen	61	US Dollar	-187
Taiwan Dollar	-58	Romanian Leu	88
Romanian Leu	58	Japanese Yen	86
Chinese Yuan	49	Chinese Yuan	32
Hong Kong Dollar	-38	South Korean Won	28


Most important interest rate and credit spread sensitivities at year-end (*)
in € thousand	2023		2022
Interest Rate (BPV) 1		Interest Rate (BPV) 1
Euro	-309	Euro	-334
Czech koruna	71	British Pound	-95
Korean Won	-41	US Dollar	-79
US Dollar	-40	Taiwan Dollar	67
British Pound	-35	Japanese Yen	63

Credit Spread (CSO1) 2		Credit Spread (CSO1) 2
Germany	405	Netherlands	162
Netherlands	120	United States	151
Korea	-111	Japan	102
Japan	106	France	88
United Kingdom	101	Germany	87
1Basis point value (BPV) measures the impact on value of a one basis point increase in interest rates. 2Credit Spread Sensitivity (CS01) measures the impact on value of a one basis point increase in credit spreads. Exposures to supranational institutions are not assigned to a specific country.


Credit spread sensitivities per risk class and sector at year-end (*)
	2023		2022
in € thousand	Corporate	Financial Institutions	Corporate	Financial Institutions
Credit Spread (CSO1) 1
Risk classes
1 (AAA)	0	0	2	-1
2–4 (AA)	12	50	-1	-7
5–7 (A)	57	50	154	-13
8–10 (BBB)	106	13	249	-11
11–13 (BB)	25	-25	7	7
14–16 (B)	17	-4	23	-4
17–22 (CCC and NPL)	-8	-20	3	-7
Not rated	0	0	0	0
Total	208	65	437	-36
1Credit Spread Sensitivity (CS01) measures the impact on value of a 1 basis point increase in credit spreads.

Funding and liquidity risk (*)

Introduction (*)

Funding and liquidity (F&L) risk is the risk that ING or one of its subsidiaries cannot meet their financial

liabilities upon their maturity date at a reasonable cost and in a timely manner. ING incorporates funding

and liquidity risk management in its business strategy, and has established a funding and liquidity risk

framework to manage these risks within predefined boundaries.

A high-level overview of the F&L framework is provided in the next figure.

Governance (*)

Funding and liquidity risk management within ING falls under the supervision of the ALCO Bank function,

which approves the funding and liquidity risk appetite and subsequently cascades it throughout the

organisation. ALCO Bank has delegated the responsibilities of the Internal Capital and Liquidity Adequacy

Assessment Process (ICLAAP) and documents, as per the ICLAAP framework of ING, to the ICLAAP

Committee. The ICLAAP Committee therefore focuses on technical liquidity documents and oversees

business processes and deliverables concerning the Internal Liquidity Adequacy Assessment Process

(ILAAP). The EB, MBB, and staff departments from the CRO and CFO domains, as well as Group Treasury,

have oversight of, and are responsible for, managing funding and liquidity risks.

ING’s funding and liquidity risk governance is based on the three-lines-of-defence structure. This sets a clear

division of responsibilities as well as an independent risk control challenge process. Group Treasury and the

business lines have the first-line-of-defence functions, which include management of ING’s (regulatory)

liquidity and funding position, maintaining access to the professional funding markets, and managing the

liquidity buffer. Financial Risk, as the second line of defence, is responsible for developing and maintaining

ING’s policies, standards and guidelines on F&L risk management, as well as for setting the F&L risk appetite

through stress testing and other risk measurement activities. The Finance function is responsible for

management information and regulatory reporting related to funding and liquidity risk management. As

the third line of defence, Corporate Audit Services is responsible for independently assessing the design,

effectiveness, and implementation of the Funding & Liquidity framework.

Funding and liquidity management strategy and objectives (*)

The main objective of ING’s funding and liquidity risk management is to maintain sufficient liquidity to fund

the commercial activities of ING, both under normal and stressed market circumstances across various

locations, currencies, and tenors.

ING’s funding consists mainly of retail and corporate deposits contributing around 50 percent and 25

percent of total funding, respectively. These funding sources provide a relatively stable funding base. The

remainder of the required funding is attracted primarily through a combination of long-term and short-term

professional funding. Group Treasury manages the professional funding in line with the F&L risk appetite,

with the aim of ensuring a sufficiently diversified and stable funding base.

Funding and liquidity adequacy and risk appetite (*)

ING identifies key drivers of short-term and future liquidity and funding needs on an ongoing basis through

the periodic risk identification process. Taking into consideration the identified risk drivers, ING regularly

assesses its current and future liquidity adequacy and, if deemed necessary, takes action to further improve

ING’s liquidity position and maintain sufficient counterbalancing capacity. A liquidity adequacy statement is

formulated on a quarterly basis to substantiate and reflect the management view on the current funding

and liquidity position as well as the potential future challenges. The quarterly liquidity adequacy statement

is an important part of ING’s ILAAP process.

Additionally, ING completes ad-hoc funding and liquidity assessments if deemed necessary. Following the

banking turmoil in March 2023, ING completed a lessons-learned deep-dive. This deep-dive included peer

and internal analysis of deposit structures and liquidity buffers, and a review of the influence of mobile

banking apps and social media on financial institutions. The F&L risk appetite subsequently incorporated

elements of this analysis, as well as the impacts of quantitative tightening, TLTRO III redemptions, increased

competition for savings in the higher-interest-rate-environment and potentially higher deposit outflows in

certain countries, in the 2023 review.

ING assesses its F&L adequacy through three lenses – stress, economic and normative:

•Through the stress lens, ING evaluates its ability to withstand periods of prolonged F&L stress for both

normative and economic requirements or limits under idiosyncratic, market-related, a combination of

idiosyncratic and market-related and climate risk scenarios, which lead to customer deposit outflows,

deterioration of access to funding markets, and lower liquidity value of counterbalancing capacity.

•Through the economic lens, ING assesses the extent to which its customers, professional counterparties

and investors are comfortable to provide deposits and funding in the tenors, currencies, and instruments

necessary to sustainably fund the business (intraday, short-term and long-term) in a going-concern

situation.

•Through the normative lens, ING ascertains that the bank is in the position to meet current and future

home and host regulatory requirements.

For each lens, ING has established a related set of risk appetite statements, which define ING’s risk appetite

commensurate with the principles of liquidity adequacy. These risk appetite statements are summarised in

the following illustration:

The F&L risk appetite statements are translated into a number of metrics with appropriate boundaries and

instruments, which are used to regularly measure and manage ING’s funding and liquidity risk. The risk

appetite with respect to the stress lens aims to have sufficient counterbalancing capacity under various

internally defined stress scenarios. Regarding the economic perspective, an internally defined stable funding

to loans (SFtL) ratio and stable funding surplus metric (supplemented by other metrics) is used to stimulate

a diversified funding base and to prevent overreliance on professional funding. Finally, the liquidity coverage

ratio (LCR) and the net stable funding ratio (NSFR) regulatory metrics are monitored in terms of both ING’s

risk appetite and normative requirements.

The macroeconomic and market environment are also important considerations in ING’s funding and

liquidity framework. The macroeconomic environment comprises various exogenous factors over which ING

has no control, but which may have a material impact on ING’s F&L position. The main macroeconomic

factors analysed on a regular basis include:

•Performance of global and local economic performance e.g. shifts in GDP, inflation rates, unemployment

rates, and public deficit/surplus;

•Developments and risks arising from geopolitical tensions and related trends;

•Monetary policy with a focus on the alternative monetary measures employed by central banks in

recent years as a result of the global energy crisis and the recent period of high inflation;

•Regulatory requirements; e.g. understanding the changing regulatory landscape as well as the impact of

ING’s actions on existing regulatory boundaries.

The strategic ambitions of ING, together with the design and execution of the funding plan, are assessed

under both current and projected market conditions. An emphasis is placed on understanding overall

market trends and developments, credit rating changes, and peer comparisons.

Liquidity stress-testing (*)

Funding and liquidity stress-testing forms part of the overall F&L framework. It allows ING to examine the

effects of exceptional but plausible future events on ING’s funding and liquidity position. It also provides

insight into which entities, business lines or portfolios are vulnerable to which types of risk drivers or

scenarios.

The stress-testing framework encompasses the funding and liquidity risks of the consolidated balance sheet

of ING Group, including all entities, business lines as well as on-, and off-balance-sheet positions. The net

liquidity position (NLP) is the main stress-testing measure and is measured at different time buckets.

The stress-testing framework considers idiosyncratic, market-wide, combined (idiosyncratic and market-

wide), and climate and environmental stress scenarios. The design of the framework is based on empirical

evidence supplemented by expert judgement. The framework can be extended to additional ad-hoc

scenarios. For example, it can be used as input for firm-wide stress testing and reverse stress testing.

Outcomes of the stress tests are considered in the key aspects of ING’s F&L risk framework and F&L risk

management, including:

•Risk Appetite Framework (through risk appetite statements);

•Risk identification and assessment;

•Monitoring of the liquidity and funding position;

•Business actions (if needed);

•Contingency funding plan;

•Early-warning indicators.

The funding and liquidity stress-testing framework is also subject to regular internal validation by model

validation.

In line with supervisory expectations, ING’s liquidity position is stress tested on at least a monthly basis

using scenarios that form part of the F&L risk appetite statement. The results of all internal stress scenarios

are monitored and assessed on a regular basis. In addition, ad-hoc scenarios based on current economic

and market developments are run to determine their potential impacts on the funding and liquidity position

of ING. In 2023, this included stress test scenarios dedicated to the impact of rapid deposit outflows on the

bank, as well as a shutdown of short and long-term funding markets. The internal stress scenarios also serve

as input in the decision on additional contingency measures.

Contingent F&L risks are addressed in the contingency capital and funding plan with a focus on early-

warning indicators as well as organisation and planning of liquidity management in times of stress. The

contingency funding measures are developed in conjunction with the ING recovery plan and are reviewed

and tested on a regular basis