Model Risk | Benchmarking
Model risk
Banks building GenAI governance in parallel to model risk
Risk Benchmarking: Majority have established AI governance committees, but ownership is fragmented
Lower-risk models face excessive reviews, banks say
Risk Benchmarking: Validation workload stretching teams, amid emerging regulatory divergence
Model risk managers see growing regulatory divergence
Risk Benchmarking study finds most banks expect easing of model risk supervisory scrutiny in the US, but tightening in Europe
Many banks do not document failure plans for Tier 1 models
Risk Benchmarking: Strong predeployment validation gives way to ad hoc escalation of breaches, even at some large lenders
Explore the data
Scaling model risk
Banks’ model inventories vary hugely. Some functions manage just 25-74 models, including the odd superregional, while one US G-Sib maintains between 2,500-4,999 models.
Check out more findings from Risk.net’s Model Risk Management study here.
Model risk managers are being asked to do more with less
Risk Benchmarking study finds function being handed expanding AI workload, on flat resources
Banks are automating GenAI testing, but scope varies widely
Risk Benchmarking: LLM-as-judge offers model testing at scale, but few lenders use it to facilitate autonomous sign-off
Model Risk Benchmarking 2026: explore the data
View interactive charts from Risk.net’s 44-bank study, covering model inventories, resourcing, GenAI governance, validation and regulation
A third of banks do not maintain logs for GenAI models
Risk Benchmarking study finds few banks review prompt logs systematically, with larger firms focusing on higher risk use cases
Few banks formally evaluate GenAI human-in-the-loop controls
Risk Benchmarking: G-Sibs and challengers use tools to test controls efficacy; others rely on judgement
From gatekeeper to coach: model risk bids to reinvent itself
Model Risk Benchmarking data reveals a function in flux, grappling with resource cuts, AI models, regulatory divergence
