Powered by machine learning

Insurance Fraud Detection solution enables:

  • Instant claims scoring
  • Real-time decision making
  • Claims automation
  • Faster payment of non-fraudulent claims
  • Lower claim payout due to improved fraud detection

If your company deals with many claims, investigators can only investigate and uncover a certain number of potential frauds. The criterion relies heavily on past behavior and experience of fraud investigators and senior experts in detecting fraud. But fraudsters are always looking for new ways. Large amounts of data can therefore be a challenge or an opportunity.

Problems we are solving

It is almost impossible to check all claims manually. Automating this process by evaluating claims against a predefined model and static rules makes a tremendous difference.

Claims below a predefined threshold can be paid out immediately. Only claims above the threshold need to be reviewed by an individual. But the real progress is achieved when machine learning is included in the equation.

The crucial question is how to detect the damage claims with a reasonable suspicion of fraud. A damage claim has many parameters, but an average person can remember a maximum of 5 when comparing different damage claims, and even then, the results from that comparison are not immediately available for processing. On the other hand, the computer can remember incomprehensibly more parameters, while also simultaneously comparing, sorting, and processing the claims.

It is not surprising that a computer fraud detection system is much better prepared for handling large amounts of data than a human being. If we implement machine learning, the system becomes additionally equipped for detection of new frauds that are not yet recognized or known to investigators.