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The rapid growth of the healthcare insurance industry has led to an increase
in fraudulent claims, resulting in significant financial losses. This paper presents
an AI-Based Health Insurance Claim Fraud Detection System developed using
Python, Django, and machine learning techniques. The system aims to identify
fraudulent claims accurately by analyzing patient details, treatment information,
and billing patterns.
The fraud detection module utilizes Optical Character Recognition
(OCR) to extract text from medical bills and a Logistic Regression model to
calculate a fraud probability score. A Smart Audit engine further enhances the
system by applying automated business rules, such as policy velocity checks.
Results show that the system improves auditing efficiency and reduces manual
effort
"AI-Based Health Insurance Claim Fraud Detection System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.c558-c563, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604339.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator