Rajshri Deshvena

1.Credit Card Fraud Detection,

The goal of this project is to develop a robust machine learning model that accurately detects fraudulent credit card transactions. With the increase in online transactions and digital payments, detecting and preventing credit card fraud has become crucial for financial institutions and customers.

This project involves analyzing a large dataset of credit card transactions, identifying patterns indicative of fraud, and building a model that can classify transactions as fraudulent or legitimate in real-time.

2.Loan Default Prediction,

The objective of this project is to develop a machine learning model that predicts the likelihood of a borrower defaulting on a loan. Predicting loan defaults is crucial for financial institutions to minimize risk, make informed lending decisions, and ensure financial stability.

This project involves analyzing historical loan data, identifying key risk factors, and building a predictive model that classifies borrowers as likely defaulters or non-defaulters.