Claims Fraud Detection for Auto Insurer

Share on twitter
Share on facebook
Share on linkedin
Share on whatsapp
Share on email

Leading Auto Insurer in India

Problem Statement

  • A scenario of an estimated 3% fraudulent/improper claims against an industry average of 1%.
  • Objective was to enhance the upstream fraud detection capabilities not only at the claims level but also at the customer level

Analytics Led Approach

  • Broad 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

  • A proof of concept wherein Customers’ auto claims data for specific calendar year were analyzed and trends and patterns from analysis were presented to the business team
  • Claims fraud detection 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

  • Significant reduction in false positive
  • 3.5% of 2010 claims identified as potential fraud
  • 26 Crores of potential losses due to fraud

    XTechalpha: Launching a “next-in class“ platform of exponential technologies: AI, Blockchain, Cloud, Cybersecurity, IoT & emerging segments: GCCs, Startups and Academic Institutions & Edtech accentuated with an enviable line up of proven and seasoned thought leaders bringing together and ensemble, curated content, networking interventions and learning enhancement. A must visit primer for GIC heads, Technology leaders, Exponential technologies enthusiasts, Academic deans and Entrepreneurs.

    Watch the Launch video:

    XTechalpha: reimagine your THINKING