Digitalization of voluntary motor insurance underwriting based on machine learning technology

Abstract

The article discusses the problem of increasing the efficiency of underwriting in voluntary motor insurance using digital technology. For this purpose, we propose to introduce an underwriter decision support system, developed based on machine learning technology, into the operational activities of an insurance company. Increased accuracy of risk assessment is ensured by using the large volumes of collected data for both risk analysis and forecasting. The proposed solution was successfully tested on real data using a developed program. This program allows the underwriter to determine the underwriting rate for CASCO contracts based on the passive digital footprint of the Insured-Vehicle pair.