The problem

Insurance fraud causes huge financial loss to insurance companies every year and is undoubtedly one of the most important challenges they have to face. Insurance fraud takes various forms, such as overcharging, false declaration, concealment of information, etc. and its detection is a difficult task.

The purpose

Insurance fraud detection i.e. the set of activities undertaken to prevent money from being obtained through false pretenses.

The solution

With the use of machine learning and artificial intelligence models that will rely on historically recorded and confirmed insurance fraud attempt data, correlations and patterns between historically suspicious activities will be identified and based on these it will be easier to identify attempted fraud in the future.

The benefit

The use of machine learning tools allows insurance companies to quickly and efficiently detect cases of fraud.

This mainly entails the following:

  • Reduction of damage arising from insurance claims
  • Reduction in the cost of handling compensation claims
  • Cost reduction from expert services
  • Enhancing the company’s competitiveness in the market, as well as customer retention, because the resulting cost from the insurance fraud is passed on to all the insurance company’s customers, (due to the increase in the claims ratio) through the increase in the insurance premium.