Navigating the intricacies of AI accountability in suptech

This is the second article in the series "Artificial intelligence (AI) in financial supervision: Promises, pitfalls, and pragmatic approaches." It addresses the intricacies involved in navigating AI's complexities, including ethics, biases, explainability, data privacy, security, and the need for technical expertise. It emphasizes the importance of collaboration between the public and private sectors, academia, and other stakeholders in shaping the future direction of AI in suptech and the broader financial services sector.