Why smaller, domain-trained AI models outperform general-purpose LLMs in enterprise settings.

Critical infrastructure has long been associated with physical assets—power plants, transportation networks, hospitals, and ...

This research initiative highlights applied AI and business analytics for financial risk management, cybersecurity, and ...

Financial institutions are in the business of risk management and reallocation, and they have developed sophisticated risk management systems to carry out these tasks. The basic components of a risk ...

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 ...

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 ...

The gap between AI and traditional risk modelling is substantial. Traditional models often fall short when dealing with complex, non-linear relationships. In contrast, AI models thrive in detecting ...

A proactive, resilience-driven model treats risk as every team’s responsibility and integrates a security mindset into daily decisions, workflows and priorities.

This article was written by Antonios Lazanas, Head of Portfolio and Index Research at Bloomberg. Modern risk modelling is not just about monitoring risk. Sure, the specialists who manage risk are ...

Following the global financial crisis that began in 2007–08, policy- makers have multiplied their efforts and implemented reforms to strengthen the resilience of the financial sector. But – while ...