DandiMahendris/Auto-Insurance-Fraud-Detection
This research goal is to build binary classifier model which are able to separate fraud transactions from non-fraud transactions.
This project helps insurance companies identify fraudulent auto insurance claims. By inputting detailed claims data, it generates a prediction indicating whether a specific claim is likely fraudulent or not. This tool is designed for insurance fraud analysts, adjusters, and risk managers who need to efficiently flag suspicious claims.
No commits in the last 6 months.
Use this if you manage auto insurance claims and need a system to automatically flag potentially fraudulent submissions for further investigation.
Not ideal if you're dealing with fraud detection outside of the auto insurance domain, as this model is specifically trained for that industry.
Stars
22
Forks
5
Language
HTML
License
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Category
Last pushed
Nov 14, 2023
Commits (30d)
0
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