The Global Risks Alliance (GRA)
Model risk management is the discipline of controlling the risks that arise from using quantitative models and AI systems in financial decisions. It developed in banking around valuation and capital models and now covers credit, insurance pricing, reserving, trading, fraud detection, anti-money-laundering, customer service and generative AI tools. This page describes the discipline as research rather than execution: where models are used, how they are governed and what shared understanding the industry needs.
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The AI and Financial Model Risk sector overview covers model governance and responsible AI use in financial decision processes and risk measurement. It sets out who is in scope, from model risk teams and quantitative validators, how risk reaches the sector and how it travels onward, analysed with model inventories, testing, validation and monitoring. GRA builds shared industry understanding and does not advise, rate or assess individual firms.
Fig.How GCRI, GRF and GRA share one field while the authorities decide. Design, not a record.
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
| Area | Typical models | Main risks |
|---|---|---|
| Lending | Credit scoring, probability of default, affordability | Unfair outcomes, poor performance in new conditions |
| Insurance | Pricing, reserving, catastrophe and claims models | Mispricing, reserve shortfalls, discrimination |
| Markets | Valuation, trading, market risk | Mis-valuation, correlated behaviour in stress |
| Capital and liquidity | Regulatory and economic capital, stress testing | Understated risk, false comfort |
| Financial crime | Fraud and transaction monitoring | Missed crime, excessive false alerts |
| Operations and service | Generative AI assistants, document processing | Inaccurate output, data leakage, dependency |
AI and Financial Model Risk frames are set by US agencies, PRA and EU.
| Part | Channel AI and Financial Model Risk studies |
|---|---|
| Credit | Scoring |
| Insurance | Pricing |
| Markets | Trading |
| Crime | Detection |
Shocks travel between these parts, and AI and Financial Model Risk studies the links: When does a model fail, and who notices? The evidence base is model records and monitoring data.
Knowing every model in use, its owner and its materiality. See model risk governance.
Documented design, data and assumptions, with testing before use.
Effective challenge by people independent of the developers.
Ongoing checks of performance and drift, with thresholds for review. See model monitoring and drift.
Human oversight and limits on where a model may be used. See human-in-the-loop controls.
Each institution governs its own models. What none can see alone is how model risk accumulates across the sector: how many firms rely on similar data, vendors or techniques, how methods for validating machine learning and generative AI compare, and where common failures are emerging. That precompetitive picture is the focus of this platform. How model failures can spread is set out on financial-system transmission.
Methods include uncertainty quantification and model validation, AI evaluation and assurance engineering, machine learning and statistics. Sector scenarios appear on the scenarios page as they are reviewed.
Nothing on this platform validates, approves or certifies any model, vendor or institution, and nothing is legal, regulatory or investment advice. Analysis is sector-level research.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Transmission channel | The route by which a shock reaches financial institutions' balance sheets. |
| Model risk | The potential for adverse consequences from decisions based on incorrect or misused model outputs, as SR 11-7 describes it. |
| Model validation | Independent testing that a model performs as intended and is fit for a stated use. |
| Systemic risk | The risk of disruption to financial services caused by impairment of all or parts of the financial system, with serious consequences for the real economy, as the IMF, FSB and BIS define it. |
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
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.