Android, Web, Django
This project is developed as a solution for a problem statement in Codeshastra 5.0 (Round 1) 24 hrs. Hackathon, in which detection of fraudulent claims is done based on various parameters. Used Decision Tree Classifier to train our model and then predicted claims which resulted in around 80% accurate predictions.
- Life/Health Fraud Detection :- This feature aims to automatically detect fradulent claims in the domain of Lif/Health Insurance based on the available parameters.
- Generalized to All Providers : This feature aims to provide generalized services to all the companies and not limited to specific company.
- Visualization of Data : This feature aims to provide graphical analysis of the data based on its various parameters that are understandable to the user.
- Prediction with different Algorithms :- This feature aims to provide the best possible prediction for a particular claim by using various available supervised learning algorithms.
- Responsive UI :- This feature aims to provide responsive user interface which enhances user experience and can be accessed from any device.
- Scalability :- This feature allows other developers or company's to use the system in order to develop more advanced system for specific domain of insurance.
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Backend
- Django
- Scikit Learn
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Frontend
- App : Android
- Web : Bootstrap, Charts.js
- Bhavin Mehta - [email protected] https://github.com/mehtabhavin10
- Jigar Avalani – [email protected] https://github.com/jigaravalani143
- Priyam Vora - [email protected] https://github.com/priyamvora99
- Preet Shah - [email protected] https://github.com/preetshah21699