User Risk Score

A user risk score is a numerical or categorical rating assigned to a customer based on factors that indicate their likelihood of engaging in fraud, money laundering, or other suspicious activity. Risk scores are calculated using data such as customer demographics, transaction behavior, geographic location, product usage, and links to high-risk entities. Institutions apply risk scoring at onboarding and update scores continuously throughout the customer lifecycle.High-risk scores trigger enhanced due diligence, additional verification, or transaction restrictions, while low-risk customers experience streamlined processes. Risk scoring enables financial institutions to implement a risk-based approach by allocating resources efficiently and focusing attention on higher-risk relationships. Modern systems use machine learning and behavioral analytics to refine scoring models, improving accuracy and reducing false positives. Banks, fintechs, and insurers rely on user risk scores to meet regulatory expectations for proportionate controls and effective risk management.