Research project AI to detect unclear insurance claims
Can AI help us come to terms with fraud? In this project, we use machine learning models to identify indicators for unclear insurance claims in order to deter suspicious damage payments and insurance fraud.
Photo: Andrey Popov/Mostphotos.
The process of identifying unclear insurance cases is complex and require manual oversight. The identification and selection of unclear insurance cases are dependent on the claims officer’s diligence.
In the absence of technical tools for handling large amounts of data, identification and selection is made largely based on the claims officer’s intuition. The selection of unclear insurance cases is likely to be affected by, for example, detected historical frauds at the expense of things that characterize ongoing fraud. When the claims adjuster has identified an unclear insurance case, an investigator takes over.
The purpose of this research project is to develop machine learning models that can, with high precision, identify indicators of unclear insurance cases.