Antifraud Model For Internet Loan Using Machine Learning

Nowadays everyone has moved to online. In the same way frauds are also increased on internet. Although there are many approaches to detect these kind of frauds, they are not accurate. This has to be enhanced This research work make use of random forest and XGBOOST algorithms. This research work uses a big public loan dataset, such as that from Lending Club, to detect fraud. A random forest is used to fill in the missing values initially. The most discriminating features are then chosen using the XGBoost algorithm. Such a basic and successful model could improve the use of machine learning for detecting the frauds in Internet loans, which would help financial engineers.