P&C Insurance Fraud Detection Solutions

Fraud and abuse cause significant losses in all major lines of P&C insurance: automobile, home, and worker’s compensation. Sometimes fraud may go undetected for decades because investigators are overloaded by the sheer amount of data and are looking only for already discovered fraud schemes. They might have no idea of what other forms fraud can take and how to discover it.

Zoom in on suspicious claims

Megaputer’s solution for fraud detection analyzes claim data to determine normal behavior patterns and detect possible fraud and abuse. It is based on combining statistical and machine learning techniques with text analytics. The solution helps investigators focus on a small amount of highly suspicious claims, agents, and customers instead of shooting in the dark.

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How it works

The solution uses several technological approaches to identify suspicious activity:

Detect anomalies

The solution creates multiple metrics enabling the comparison of behaviors of different entities. Based on statistical analysis and machine learning on all claims, it determines normal behavior patterns of individual agents and customers and identifies systematic anomalies.

Analyze claim notes

Going beyond the analysis of structured data, the solution can extract information from the associated textual claim notes. For example, it can pull information about the circumstances of an incident, related damage, involved parties, sustained injuries, and medical treatment.

Investigate anomalies

The solution identifies agents and customers singled out as anomalous by more than one analysis scenario and helps determining the exact behavior patterns that set them apart. The user can set up business rules that will capture similar behavior patterns to prevent fraud and abuse in the future.