Model risk
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
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
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
The do-it-all machine: model risk in the age of generative AI
Banks race to understand risks posed by new breed of multi-purpose bots
Top 10 op risks: AI upends risk taxonomies
AI risk enters annual poll in fifth, but firms split over treating it as a standalone risk or a cross-cutting driver
Model validation of a generative-artificial-intelligence-based avatar for customer support in banking
The authors put forward a validation method for a gen-AI-based avatar designed to deal with customer inquiries in the banking sector.
Rising reliance on internal auditors spooks regulators and industry
Risk managers warn US is substituting supervisors with auditors; could compromise independence
Generative artificial intelligence in model risk management: emerging opportunities, supervisory challenges and validation frameworks
The author proposes a structured approach to validating generative AI models in line with the principles of current regulatory standards.
Interest rate crosswinds buffet IRRBB teams
Political intervention and rapid-fire law changes are skewering bank models for forecasting cashflows
FRTB internal models: quo vadis?
Two risk experts explore how to adjust the FRTB framework to promote internal model usage
The loneliness of the model risk manager
Boards may see them as a drag on innovation; risk functions need to show they embrace efficiency
Long way round: EU banks lament credit spread saga
EBA ditches some of banks’ preferred qualitative reasonings – and shortcuts – for CSRBB exclusion
FHLB Cincinnati explores AI to spot failing banks
Agentic model detects anomalies, monitors sentiment and drafts credit reports for analyst review
Validating bank risk models under trade war stress: a framework for adaptive stress testing with AI-driven calibration and cross-industry applications
Focusing on validating and enhancing risk models, the author proposes a comprehensive framework through which to stress test under trade war conditions.
Esma won’t soften regulatory expectations for cloud and AI
CCP supervisory chair signals heightened scrutiny of third-party risk and operational resilience