Radix Analytics Pvt Ltd

Fraud Scoring for Insurance Claims

Radix Analytics Pvt Ltd > Scoring Models > Fraud Scoring for Insurance Claims

Issues & Objectives

  • A major insurance company in Singapore used to manually examine each travel insurance claim to identify potentially fraudulent one

  • Suspicious claims were subject to a more detailed investigation

  • This involved considerable manual effort & inconsistent processes
  • The project objective was to develop a score to identify potentially fraudulent claims which would be subject to greater scrutiny.

Challenges

  • Data included 77,445 claim records of which only 120 had been determined to be potentially fraudulent

  • So identified potentially fraudulent claims are rare events (0.15%) and therefore hard to detect

  • It was however expected that there could be a large number of undetected fraudulent claims

Project information

Skills

Advanced Statistical Techniques 

Client

Travel Insurance Provider

Domain

Scoring Models

Location

Singapore

Solution

  • Gradient Boosting – a powerful machine learning algorithm was used for detecting potentially fraudulent cases

  • Substantial lift demonstrated. – on the client test data set it sufficed to examine 7.75% of all claims to identify 91.67% of all fraudulent claims

Benefits

  • Process automation, ensuring consistency, cost saving and increased accuracy

  • Scrutiny restricted to high scorers reducing manual work by a factor of 5 -10