Domain - Banking Technologies
Language - R
IDE - R script
Dataset link :- https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud


Business Impact

In 2019, credit card fraud losses amounted to $28.65 billion worldwide. 
We developed an ML model, which works on XGBOOST to reduce the loss faced by these credit card companies.  
About 90% reduction in the cost could be achieved using this technique.


Dataset Overview

The dataset contains European cardholder transactions that occurred over two days.
* Time - the seconds elapsed between each transaction and the first transaction in the dataset
* V1, V2, ..., V28 - principal components obtained through dimensionality reduction (PCA)
* Amount - the transaction amount
* Class - the response variable, indicating whether a transaction was fraudulent or not