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Claims Fraud Detection for P&C Insurance

August 15, 2020

Leading Personal Lines Insurance Carrier in NE of US

Problem Statement

  • Basic business rules for fraud detection and prevention was in place and the need for improving their fraud detection and prevention tools was considered
  • A POC was developed to analyze Customers’ claims data to provide trends and patterns of suspected fraudulent transactions

Analytics Led Approach

  • Given are high level process steps which were followed:
    • Sensitive data encryption
    • Load the data from
    • multiple sources Logistic Regression Model creation
    • Data cleansing ; Data transformation; Business Significant variables deduction
    • Distribution analysis
    • Correlation analysis
    • Multi- dimensional Analysis
    • Fraud analysis through data profiling
    • Identify key suspect indicators which indicated possible provider frauds

Business Impact

  • Designed a proof of concept whereby Customers’ auto claims data for specific calendar year were analyzed and trends and patterns from analysis  were presented
  • The solution helped to identify the potential losses due to fraud or suspect claims and thereby helped to reduce claims leakage to a great extent

Critical Success Factors

  • $ 3.5 million potential losses were identified due to potential suspects
  • $ 600 k of potential losses were identified due to potential suspects with fortune coverage

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