deepsense.ai’s client, a leading CEE insurance company, holds a major share in the car insurance market in the region. As motor insurance is a significant part of its portfolio, decreasing the cost of claims handling is of utmost importance.
Insurance companies frequently rely on external systems to provide information on repair processes and car parts that get damaged in road events. The challenge is in cutting the cost of queries to external systems by reusing information they already have.
To tackle the challenge, deepense.ai produced a machine learning model to identify repetitive inquiries on various models and damage types. The solution analyzes historical data to help estimate repair costs without querying external expert systems.
The solution showed the potential for reducing the costs of querying external expert systems by better utilizing insurers’ data. deepsense.ai’s team proposed changes in the process of preparing the inquiries to allow for greater automation and cost savings.