Article ID: ab15ada17d25ae0c35509a3514578aed461179625a2255b7ac9635edaf3b69fa
Source ID: regulatory:risk.net
Published At: -
Extraction Method: trafilatura
URL: https://www.risk.net/topics/model-risk
Body Text
Model risk Banks building GenAI governance in parallel to model risk Risk Benchmarking: Majority have established AI governance committees, but ownership is fragmented Agentic AI set to drive end-to-end automation of MRM workflows Risk Live: Validator role likely to shift towards oversight and expert judgement Model risk managers are being asked to do more with less Risk Benchmarking study finds function being handed expanding AI workload, on flat resources 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 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 Treat AI models as would-be hackers, says quant Risk Live: Models capable of “strategic deception” require different risk management, says former Risk.net quant of the year Managing AI models is reshaping three lines of defence, say banks Risk Live: Model managers want seat at table during development, and expect first line to take charge of AI model testing AI use fastest-growing area of op risk regulatory scrutiny Risk Benchmarking study finds EU AI Act the dominant driver of nascent bank risk frameworks, even well beyond Europe’s borders Second line seeks to stamp its authority on AI risk Risk Benchmarking study finds fragmented accountability for AI risk among banks, and most are short of controls to contain it Op Risk Benchmarking: Banks seek a home for AI risk Risk.net’s 2026 study sees record participation and collective unease, as banks race to incorporate AI into op risk frameworks Regulators question human-in-the-loop as AI governance tool Bank of England and FSB executives suggest it’s more important to retain overall accountability MI9: runtime governance for agentic AI systems A real-time telemetry system for banks to control and authorise for agentic AI actions Banks in Asia turn to integrated third-party risk units Regional and global firms create centres of excellence bridging first and second lines All models are wrong. Some might be OK! The authors investigate three key sources of model uncertainty and potential difficulties in addressing them. Do banks still need to validate GenAI models? Regulators carved out GenAI models from new risk guidance. Banks shouldn’t see this as a reason to stop validating them. In simplifying credit risk models, EBA could compound capital costs Skipping hard yards of internal ratings-based approach might trip higher capital charges and implementation costs Barclays built a risk framework for GenAI from scratch Eleven teams contribute to assessing generative AI use cases in a system that includes 35 controls Hopes, fears and ‘mass confusion’: the sudden end of SR 11-7 Banks welcome chance to prioritise model reviews, but fret over future policy changes and AI MRM: how banks are scaling models in the age of AI MRM capabilities are evolving to ensure compliance while helping organisations retain a competitive edge AI risk management and the shift to capability control By reframing validation, banks can align innovation with regulatory demands and maintain robust risk discipline, argues risk manager In the age of GenAI, why do we still need good models? Jean-Philippe Bouchaud says models can guide artificial intelligence through regime shifts and away from overfitting
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