Model risk
Why a hybrid approach works best for AI in credit risk modelling
AI helps models look beyond quarterly reports, but CRO says governance curtails full automation
Beyond mirror validation: the cost of ineffective challenge in model risk management
The authors demonstrate that the practice of confirming a developer’s model is correctly reimplemented and discrimination metrics are acceptable while leaving calibration under changing conditions unchallenged fails to detect calibration degradation.
Why AI agents are like staff you can’t trust
Uncertainty implicit in GenAI systems means risk managers have to take a more adversarial approach
As LLMs spread, quants confront ‘lexical risk’
Users are finding the uncertainty in GenAI models is hard to measure
A robust hybrid structural learning framework for robust structural learning and feature selection for credit risk prediction
The authors propose a robust hybrid structural learning framework for feature selection designed to address key challenges in credit risk prediction.
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
The fundamental representation of pricing adjustments
A unified representation of derivative pricing adjustments is presented
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