Insurance Fraud Detection and Risk Analytics Systems

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The ClaimSmart anti-fraud module, ClaimGuard™, leverages AI and machine learning and a unique scoring system to assess fraud risks early on, so suspicious claims receive appropriate scrutiny, but low-risk claims are quickly resolved to lower processing costs.

Key Features

Powered by AI and machine learning algorithms, ClaimGuard constantly enhances its ability to identify concealed issues in the ever-changing landscape of fraud.

By leveraging machine learning and advanced analytics, ClaimGuard thoroughly analyzes numerous potential scenarios associated with each claim and assigns risk scores accordingly.

Each profile has access to a user interface (UI) that can be configured for each user with system preferences and custom alerts. The UI has a dashboard landing page that can be used for supervisors and team leads to manage their team, understand real-time metrics of fraud scoring and trends. Some examples include balance of high risk versus low scores, progress of high risk claims reviewed in a defined time period, number of claim scores reviewed in a defined time period, and more. The UI also displays claim and policy information, the evolving risk score from first notice of loss through claim closure in near real-time, primary features driving the risk score up or down, recommendations on next steps in the investigation, and guidance from management based on defined rules.

Users can provide feedback on each score. Feedback is fed into the retraining process which continues to enhance the performance score of the model.

Key Benefits

The benefits of ClaimGuard are as follows:

  • It enables straight through processing by identifying low risk claims that can be expedited through the claims process

  • It can flag high-risk claim and automate referral to the special investigative unit (SIU)

  • It increases the number of real fraud referrals to SIU and reduces the number of false positives that wind up in SIU

  • Loss payouts are reduced when ClaimGuard identifies fraud faster, allowing SIU to mitigate exposure and restrict payout to what is owed

  • It reduces investigator workload which, in turn, reduces loss adjustment expenses and improves loss ratios

  • Data can be pulled into the model from the historical claim and policy systems as well as from third party data sources to strengthen model performance

  • ClaimGuard helps strengthen decision making on each claim and collects analytics to make smarter downstream decisions that can reduce the claim lifecycle



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