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Volume 12 Issue 07
July 2026
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Author(s)
Pushpavalli P Shamitha M Aishwarya S Shyleshwari M Shetty
Abstract
Concern Over Insurance Fraud In The Machine Sedulity Is Growing, As It Can Affect In Significant Financial Losses And Advanced Decorations For Law- Abiding Policyholders. This Study Offers A Machine Knowledge- Predicated System For Further Directly Relating False Claims. To Address Class Imbalance, We Use A Kaggle Dataset And The SMOTE Fashion. With A Python Flask- Predicated Web Interface That Lets Stoners Enter Claim Details And Get Immediate Fraud Discovery Results, Our System Predicts Fraud Using Random Forest, Decision Tree, And Logistic Regression Models.
Keywords
Vehicle Insurance
Fraud Detection
SMOTE
Random Forest
Flask
Machine Learning.
Paper ID
IJSARTV11I5103468
Publication Date
May 5, 2025
Research Area
CSE