Introduction
Risk scoring is a fundamental mechanism for prioritising work in insurance fraud detection and investigation. Rather than treating all cases equally, risk scores allow insurers to allocate resources based on the likelihood and potential impact of fraud.
Effective risk scoring supports both efficiency and fairness.
What Risk Scoring Is
Risk scoring assigns a numerical value to indicate the probability of fraud or non-compliance. Scores are typically generated using predictive models, rules, or a combination of both.
These scores provide a relative measure of risk rather than a definitive judgement.
Using Risk Scores in Operations
In practice, risk scores are used to:
- Rank claims or policies
- Trigger investigative thresholds
- Inform routing and allocation decisions
This allows high-risk cases to receive appropriate attention without delaying low-risk claims.
Balancing Accuracy and Capacity
Risk scoring must account for operational capacity. Thresholds should be aligned with investigator availability and business priorities rather than model performance alone.
Regular review ensures that scoring remains effective as volumes and behaviour change.
Risk Scoring and Customer Trust
Transparent, explainable risk scoring supports fair treatment of customers. When decisions are reviewed or challenged, clear rationale helps maintain trust and regulatory confidence.
Related Topics
Predictive modelling
Threshold tuning
Explainable AI
Human-in-the-loop
