Inadequate risk models can result in large financial losses for firms and can seriously damage their financial condition. It is vital for firms to have robust risk models which can measure and control risk, proactively detect and prevent fraud, and effectively evaluate capital reserve adequacy. Many conventional analytical tools are failing to account for important subtleties in data, and struggle to keep pace with evolving market conditions, customer behaviour, products and regulation.
This white paper looks into the current approaches to risk model development, validation, and monitoring. It goes further by discussing the challenges business face within these areas and examines how machine intelligence can provide solutions.