An AI that won’t be fooled by scammers

Anyone who bills incorrectly must reckon with AI

How things used to be

Our client, a private health insurance company, has about two million policy holders. The company used to rely on superficial processes to detect cases of fraud in billing. For example, the clerks checked whether the medication listed on the bill submitted is still being produced. This inadequate verification system made things easy for dishonest customers. The costs of such fraud cases are borne by everyone.

Then AI came along

The adesso experts collaborated with the customer to analyse how AI applications can improve these processes. The aim was to automate parts of the inspection process, increase the detection rate and reduce the damage. In the first step, the experts developed a model to detect aberrant customer behaviour. The idea was to be able to identify fraud cases in a targeted manner. To this end, the project team performed an ad-hoc analysis to ascertain the feasibility. Following this, they developed a prototype model.

The situation today

The AI application automatically filters out conspicuous events from the large number of billing statements. These are then submitted to the clerks for review. The experts perform a detailed examination, research the connections and, if necessary, talk with the parties involved. They focus on cases with a high probability of irregularities.

"Fraud detection in the insurance industry is a use case where AI solutions excel since they are fed large amounts of data and have a clear criterion for success. We were able to improve the quality of the inspection process. This has a direct impact on the profitability of our customer."

Dr Lukas Breuer, Team Lead Data Science
adesso AG

For which companies is the approach suitable?
Insurance, Health insurance
For which decision makers is the approach interesting?
Everyone
Backgrounds for the technically interested
Descriptive analysis, Machine learning, Anomaly detection

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