Inverse residual variance (IRV) weighting reduces noise and improves factor performance. Country and industry betas replace dummy variables for deeper, more accurate risk insight. PCA shrinkage ...

With the new challenges of agentic AI, insurers will increasingly expect evidence of AI-governance maturity, not just ...

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 ...

The global reinsurance broker Guy Carpenter, a partner to @Nasdaq and user of the Nasdaq Risk Modelling for Catastrophes service, continuously develops new catastrophe risk models. Mark Weatherhead, ...

How AI, privacy-preserving computation, and explainable models quietly strengthen payments, protect data, and bridge traditional finance with crypto systems.

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 ...

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 ...

At the San Antonio Breast Cancer Symposium, researchers presented findings on Clarity BCR, a multimodal multitask ...

OpenAI has drawn a rare bright line around its own technology, warning that the next wave of its artificial intelligence ...

The LIFE-T1D model, demonstrated an ability to estimate the lifetime risk of heart disease among several groups of people with type 1 diabetes (T1D). Researchers have developed a tool they say can ...