Credit Card Fraud Detection using reusable libraries
by sharmila Updated: Sep 2, 2021
Credit card plays a vital role in individual financial planning and transactions. The individual’s bank account will be mapped to their credit cards. Nowadays, people use credit facilities provided by their banks to the fullest of their potential. Along with the increased usage of credit cards, credit card transaction fraud has become a custom in the financial sector. Fraud is an illegal activity performed by an intruder to obtain money or property. A credit card transaction fraud can lead to a substantial financial loss. Some of the libraries can help you to detect or predict credit card transaction fraud.
Analysis of credit card fraud data
Python 59 Version:v1.2 License: Permissive (MIT)
Fraud Detection model build with Python (numpy, scipy, pandas, scikit-learn), based on anonymized credit card transactions. The dataset is publicly available here: https://clouda-labs-assets.s3-us-west-2.amazonaws.com/fraud-detection/creditcard.csv.zip
Python 41 Version:Current License: Permissive (Apache-2.0)
SCARFF (SCAlable Real-time Frauds Finder) is a framework which enables credit card fraud detection.
Scala 15 Version:Current License: Strong Copyleft (GPL-3.0)
Realtime Credit Card fraud detection, using CDC (Change Data Capture) data source and TensorFlow model from a Kaggle competition.
Java 12 Version:Current License: Permissive (Apache-2.0)
This project is an implementation of credit card fraud detection using Hidden Markov Model (HMM)
Python 4 Version:Current License: Permissive (Apache-2.0)
web cloud based application for credit card fraud detection
Python 2 Version:Current License: Permissive (MIT)
A classification model for Worldline & Université Libre de Bruxelles' credit card fraud dataset
Python 1 Version:Current License: Others (Non-SPDX)
A binary classification model trained using logistic regression to flag fraudulent payments.
Python 1 Version:Current License: Permissive (MIT)