GENERATIVE AI FOR CLAIMS EXCEPTIONS AND INVESTIGATIONS: ENHANCING RESOLUTION EFFICIENCY IN COMPLEX INSURANCE PROCESSES

Abstract

Generative AI-enhanced solutions in claim excep- tions and investigations complete earlier work on generative AI support for speedy closure of complex claims, as well as a supporting foundation on AI models, architecture, and data sources. Exceptions and investigations matter because they create friction in the claims process. Exceptions can arise from risk assessment, underwriting, and fraud detection engines. Open questions, unexpected responses, or non-responses during the investigation contribute confusion, anxiety, and psychological pressure for both insureds and insurers. Consequently, these elements slow resolution, during and after initial closure. Gen- erative AI can help automate three dimensions of exception management and investigation: triaging cases for investigation, collecting the evidence needed to resolve investigations, and synthesizing the results from multiple investigations across claims or files into easy-to-follow narratives. By leveraging generative models across these three steps, any friction caused by exceptions and investigations and the associated delays can be tightened.