Insurance companies must prioritize when investigating claims because not all submitted cases can be verified. The damage report of the reporting party is a valuable resource for the assessment of the case, and the assessment usually requires many years of experience. A large German insurance company faced the challenge of needing to process claim reports more efficiently.
To make the processing of claims more efficient, a voice-based tool was developed to assist claims handlers. For this purpose, a large volume of claims reports was combined with the assessments of experienced claims handlers and the outputs of investigations looked into. Using this data, a Natural Language Processing model was trained to detect fraud attempts with significant precision. The damage reports marked in this way are processed with special attention in the further process.