The Global Risks Alliance (GRA)
Credit risk is the chance that a borrower or counterparty fails to pay in full and on time, and it remains the main source of loss for most banks. This page sets out how credit quality deteriorates, how losses concentrate in sectors, regions and single names, and how counterparty exposures in derivatives and securities financing pass stress from one institution to another. It names the measures risk committees and supervisors use and the limits of each.
GRA · Established · service level R0
Credit risk is the chance that a borrower or counterparty fails to pay in full and on time, and it is the main source of loss for most banks. Quality erodes before default, losses concentrate in sectors, regions and single names, and counterparty exposure on derivatives moves with markets.
How physical and transition risk could reach a loan book under different scenarios. Illustrative design values.
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
Credit and counterparty risk · Bank B · Reporting date Q3
% of RWA vs requirement and buffers
% vs minimum
Credit quality, concentration and contagion. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Arrears, covenant breaches, rating downgrades and forbearance usually precede default by several quarters. Under IFRS 9 a significant increase in credit risk moves a loan from a twelve-month to a lifetime loss allowance, so provisions rise before losses are realised.
Exposures cluster in sectors, regions, collateral types and large single names. A shock to one segment, such as commercial property or an export industry, can drive losses well beyond what a diversified portfolio model implies.
In derivatives and securities financing the amount owed changes with prices. Wrong-way risk arises when exposure grows just as the counterparty weakens, and margin calls in volatile markets can drain liquidity at the same moment.
A large counterparty failure imposes losses on creditors, freezes collateral and triggers close-out across many contracts. Uncertainty about who holds the exposure can lead lenders to withdraw from sound institutions as well.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Non-performing loan | A loan ninety days or more past due, or unlikely to be repaid in full without collateral. |
| IFRS 9 stage 2 | Loans whose credit risk has increased significantly since origination, provisioned for lifetime expected loss. |
| Wrong-way risk | Exposure to a counterparty that rises as the counterparty's credit quality falls. |
| Loss given default | The share of an exposure lost if the borrower defaults, after recoveries. |
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Non-performing loan ratio | percent of gross loans | quarterly | Supervisory returns, Pillar 3 disclosures | OFFICIAL |
| Stage 2 and stage 3 loan share | percent of gross loans | quarterly | IFRS 9 financial statements | REPORTED |
| Coverage ratio of non-performing loans | percent of non-performing loans provisioned | quarterly | Supervisory returns | OFFICIAL |
| Probability of default by rating grade | percent over one year | annual | Internal ratings-based models | MODELLED |
| Loss given default | percent of exposure at default | annual | Workout and recovery data | ESTIMATED |
| Large exposures to single counterparties | percent of Tier 1 capital | quarterly | Large exposures reporting | OFFICIAL |
| Sectoral concentration index | Herfindahl index of exposures by sector | quarterly | Credit registers, supervisory returns | ESTIMATED |
| Potential future exposure on derivatives | currency units at a stated confidence level | daily | Counterparty credit risk models | MODELLED |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| IMF Financial Soundness Indicators | Non-performing loans, provisioning and sectoral loan distribution reported by national authorities | Free, IMF terms of use |
| EBA risk dashboard and EU-wide transparency exercise | Bank-level asset quality, forbearance and IFRS 9 stage data for EU banks | Free, attribution |
| ECB Supervisory Banking Statistics | Asset quality and credit risk aggregates for significant institutions in the euro area | Free, attribution |
| FFIEC Call Reports and Federal Reserve FR Y-9C | Loan categories, past-due and charge-off data for US banks and holding companies | Public domain |
| BIS consolidated banking statistics | Banks' foreign claims by counterparty country and sector on an ultimate-risk basis | Free, BIS terms of use |
| Rating agency default and recovery studies | Historical default and recovery rates by rating grade and sector | Licensed, subscription |
| National central credit registers | Borrower-level exposures for concentration and interconnection analysis | Restricted, supervisory access |
Banking Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Bank board and board risk committee | What credit risk appetite to set, and which sector and single-name limits to impose | Concentration measures, stage migration and stress losses by segment |
| Chief risk officer and credit committee | When to tighten underwriting, raise provisions or reduce exposure to a weakening sector | Early warning indicators, rating migration and the assumptions of loss models |
| Prudential supervisor | Whether asset quality, provisioning and large exposures warrant supervisory action or a Pillar 2 add-on | Peer comparison of non-performing loans, coverage and concentration |
| Macroprudential authority | Whether a sectoral systemic risk buffer or a borrower-based measure is needed | System-wide concentration and interconnection measures |
How income loss, collateral damage and refinancing difficulty translate into missed payments and losses.
Common exposures to regions, sectors and large borrowers across many lenders.
How losses on derivatives, repo and interbank exposures pass between institutions.
Which data signal credit migration before it appears in defaults.
Credit losses depend on three elements: the likelihood of default, the exposure at default and the loss given default after recovering collateral. Shocks can move all three at once: a disaster raises defaults, draws on credit lines increase exposure and damaged collateral lowers recoveries.
Defaults are correlated. Borrowers in the same region or sector are hit by the same shocks, so portfolio losses are lumpier than models assuming independence suggest. Correlations tend to rise in stress, precisely when diversification is most needed.
Concentration amplifies. Large exposures to a single borrower group, or many banks lending to the same exposed sector, mean that one failure can cause large losses across the system.
Counterparty risk links institutions directly. Margining and central clearing reduce it but create liquidity demands in stress, when collateral must be posted quickly.
Credit cycles have their own dynamics. Lending standards loosen in good times and tighten in bad, amplifying economic swings.
| Method or data | What it shows | Its limit |
|---|---|---|
| Loan-level data | Borrower characteristics and performance | Confidential; access limited and aggregated |
| Credit scoring and rating models | Relative default likelihood | Calibrated on past conditions |
| Portfolio models | Loss distributions and concentration | Sensitive to correlation assumptions |
| Network analysis | Interbank and counterparty linkages | Exposure data often incomplete |
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.