August 19, 2025INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTOpen Access

An Explainable Intelligent System for Auto Insurance Fraud Detection Using Naïve Bayes

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The system achieved 92% accuracy in detecting fraudulent claims, highlighting its effectiveness in fraud detection.
Precision levels were also high, but recall performance was only 8%, indicating many fraudulent cases may go undetected.
The web-based system uses the C# ASP.NET framework and implements a multi-tiered user access structure for comprehensive operational management.
Successful implementation fosters better collaboration between insurance operations and police investigators in fraud detection.

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Implication

Web-based solution improves accuracy of insurance fraud detection using machine learning algorithms, suggesting enhanced collaboration in investigations.

Cite This Study

Reddy et al. (2025) studied this question.

synapsesocial.com/papers/68af33e9cf1dd9ea359e91a3 https://doi.org/10.55041/ijsrem51870

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Implication

Web-based solution improves accuracy of insurance fraud detection using machine learning algorithms, suggesting enhanced collaboration in investigations.

An Explainable Intelligent System for Auto Insurance Fraud Detection Using Naïve Bayes

Key Points

Discussion

Implication

Cite This Study

An Explainable Intelligent System for Auto Insurance Fraud Detection Using Naïve Bayes

Key Points

Discussion

Implication

Cite This Study

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