AI without business context fails to drive supply chain decisions. Predictive models and control towers generate signals, but ...

Operational risk scenario analysis has existed for a long time. Why is it under more scrutiny now? Patrick Naim, Elseware: I wouldn’t describe it as scrutiny so much as more ambitious objectives for ...

Why industry leaders must look past the hype to the hard realities. Artificial intelligence is transforming banking at unprecedented speed — powering fraud detection, compliance automation, credit ...

Key insight: The proposal simplifies operational risk capital for the largest banks. Forward look: Critics warn lower capital ...

Atkar: Not necessarily on operational risk. For instance, the recent Basel paper on the treatment of insurance to mitigate operational risks proposes arguably a more complicated approach than ...

The U.S. bank supervisory agencies recently issued for public comment revised guidance regarding the implementation of the proposed Basel II-related, risk-based capital requirements. Among the ...

Regulators around the world differ in their approach to model risk management (MRM) regulation – including their definitions of what a model is. While some are more prescriptive, others such as the UK ...

Catastrophe risk software provider KatRisk has acquired RED, a specialist provider of catastrophe models, including earthquake, flood, landslide, and wind ...

Boards formally treat model risk as important, but in practice many banks treat it as a compliance box-ticking exercise that only attracts senior attention when something visibly breaks or a regulator ...

Relying on one giant AI model for everything is a trap; it’s too expensive and slow for simple tasks and too risky for the hard stuff when things go wrong.