Learn about model risk, its causes, management strategies, and real-world examples from financial industry pitfalls. Unlock ...

Risk.net’s 2026 study sees record participation and collective unease, as banks race to incorporate AI into op risk ...

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 ...

Operational risk management encompasses the identification, assessment, monitoring and mitigation of losses arising from inadequate or failed internal processes, people, systems or external events.

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 ...

Global advisory firm Celent has named the financial institutions demonstrating excellence in technology use across banking, buy side/sell side, insurance, risk management, and wealth management.

Artificial intelligence has become the new language of corporate ambition. CEOs speak about it as a productivity engine.

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 ...

Learn how 4 pillars—unified data, risk sensing, AI modeling, and autonomous actions—help life sciences firms navigate ...