Detect claims fraud quickly with automated claim scoring

Insurers need to determine quickly and efficiently whether a claim is likely to be fraudulent—or if it can be fast-tracked for settlement. ClaimDirectorSM uses automated, rules-based fraud analysis to quickly generate a score that reveals if a claim has questionable attributes.


Property/casualty insurance fraud costs insurers $34 billion a year

Does Your Claims Operation Look Like Easy Prey to Fraudsters?

Improve claims triage with our fraud analytics scoring system

ClaimDirector uses industry-based rules to analyze claims and identify fraud indicators. It then calculates a score to help adjusters decide whether to process a claim or triage it for investigation. SIU teams can use the solution to uncover potential fraud and explore suspect factors. The solution uses advanced algorithms to determine the likelihood of claims fraud:

  • Compares claims to 1.3 billion records in ISO ClaimSearch® plus NICB data
  • Evaluates claims by type, line of business, loss date, and loss type
  • Provides scores for both claim and entity
  • Revises scores in real time as claims are updated
  • Customizes claims triage based on company preferences


The ClaimDirector automated score is generated from comprehensive and customizable rules, including:

  • More than 300 claim and involved-party rules
  • More than 1,000 rule combinations

SIU and business intelligence dashboards highlight fraud insights

ClaimDirector displays dynamic visual analysis of scored claims.

  • Investigators can review scored claims in real time and identify fraud characteristics faster using the SIU triage page.
  • The business intelligence dashboard provides deeper insights into the rules and data that calculate scores.

Easily implement fraud detection analytics

ClaimDirector is easy to integrate into your claims system. It’s a SaaS solution that requires minimal IT lift and provides automatic enhancements and versioning. It’s easier and can require fewer resources to implement than building an internal fraud analytics system.

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