SK

EN

FRAUD DETECTION SYSTEM

better identification of insurance fraud

using advanced prediction models

Better detection of insurance fraud via an automated machine learning system enables a two-thirds more successful follow-up investigation to be achieved compared to the traditional approach. The result is more than double the profitability of the process, achieved by more efficient use of investigator capabilities and higher protected value. Correct identification of suspicious claims enables a decision about the fulfilment to be made within 3 minutes.

The importance of fraud detection

is confirmed by statistical data

80%

of uninsured property owners try to

take out retroactive insurance

65%

of life insurance clients will not tell the

truth about their health

37%

of motor vehicle damage claims can be

classified as insurance frauds

20%

14%

of insurance frauds are committed by contractual partners of insurance companies

of all damage claims can be

classified as insurance frauds