A risk scoring model is a structured framework used to quantify and assess the risk level of a customer, entity or transaction based on various criteria.

This model assigns numerical values or weightings to different risk factors, such as jurisdiction, business activities, transaction patterns and associations with high-risk entities.

The total risk score determines whether a subject is categorized as low, medium or high risk.

Risk scoring models help financial institutions and businesses apply a standardized, data-driven approach to risk assessment, ensuring consistency in decision-making, compliance with regulatory obligations and improved detection of suspicious activities.

Advanced risk scoring models often incorporate machine learning and automation to enhance accuracy and adaptability in response to evolving financial crime threats.