Transforming Claims Processing: The Role of Artificial Intelligence in Enhancing Efficiency and Fraud Detection in the Insurance Industry

The integration of Artificial Intelligence (AI) into insurance claims processing is transforming traditional operational frameworks by enhancing efficiency and reducing instances of fraud. This study explores the deployment of AI-driven technologies including machine learning algorithms, natural language processing (NLP), and computer vision in automating claims workflows, validating data, assessing damages, and identifying fraudulent activities. Through a critical review of recent academic literature and industry reports, the paper evaluates the impact of AI on the accuracy, speed, and transparency of claims settlements. It also addresses regulatory and ethical considerations, implementation challenges, and the broader implications for workforce dynamics and customer satisfaction. Based on the findings, a conceptual framework is proposed to identify key enablers and barriers to effective AI adoption in claims processing. This research contributes to the ongoing discourse on digital transformation in the insurance sector and offers strategic insights for both practitioners and scholars

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Publication Details

Published
2025-05-18
DOI
https://doi.org/10.56472/iccsaiml25-134
Citations
1
Primary Topic
Insurance and Financial Risk Management
Type
article
Field-Weighted Citation Impact
3.13
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article

Transforming Claims Processing: The Role of Artificial Intelligence in Enhancing Efficiency and Fraud Detection in the Insurance Industry

Shwetang N. Pandya
1 citations
Insurance and Financial Risk Management
3.13
article

Transforming Claims Processing: The Role of Artificial Intelligence in Enhancing Efficiency and Fraud Detection in the Insurance Industry

Shwetang N. Pandya
article en
1 citations

Abstract

The integration of Artificial Intelligence (AI) into insurance claims processing is transforming traditional operational frameworks by enhancing efficiency and reducing instances of fraud. This study explores the deployment of AI-driven technologies including machine learning algorithms, natural language processing (NLP), and computer vision in automating claims workflows, validating data, assessing damages, and identifying fraudulent activities. Through a critical review of recent academic literature and industry reports, the paper evaluates the impact of AI on the accuracy, speed, and transparency of claims settlements. It also addresses regulatory and ethical considerations, implementation challenges, and the broader implications for workforce dynamics and customer satisfaction. Based on the findings, a conceptual framework is proposed to identify key enablers and barriers to effective AI adoption in claims processing. This research contributes to the ongoing discourse on digital transformation in the insurance sector and offers strategic insights for both practitioners and scholars

Integrated Software (United States) (US)
Decent work and economic growth
Openalex Percentile: Top 8%
Insurance and Financial Risk Management
3.13
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