Damage Quantification and Coverage Eligibility Inference: AI-Based Systems for Automated Insurance Claims Assessment and Adjudication

Authors

  • Tatyana Lyalina Associate Professor of Applied Mathematics and Information Technologies, Belarusian State University

Keywords:

damage quantification, coverage eligibility inference, systems, automated insurance claims assessment, machine learning

Abstract

A crucial step in the insurance process is the assessment of claims. Traditionally, insurance assessors would process claims by reviewing documentation and determining the validity of the claim after subjective human evaluation. While these traditional methodologies were unstructured and time-consuming, recent studies have explored applying intelligent systems to the claim assessment process to expedite it.

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Published

31-12-2024

How to Cite

[1]
“Damage Quantification and Coverage Eligibility Inference: AI-Based Systems for Automated Insurance Claims Assessment and Adjudication”, J. Computational Intel. & Robotics, vol. 4, no. 2, pp. 1–12, Dec. 2024, Accessed: Jun. 04, 2026. [Online]. Available: https://thesciencebrigade.com/jcir/article/view/716