Credit Card Fraud Detection Using Machine Learning Model
K. S. Swarnalatha, Krishna Kumar Shah, Kishore Kumar, Krishna Kumar Patel, Aashutosh Raj Sah · 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon) · 2022
The most frequent issue in the modern world is detection of credit card fraud. The rise of e-commerce platforms and digital transactions is to blame for this. In most cases, credit card fraud occurs when the card is stolen and used for any unauthorised activity, and even when the scammer utilises the card’s information for his own gain. We have a range of credit card issues in the modern world. The credit card theft detection technology was introduced to identify fraudulent actions. The proposed work aim is to build and create a novel fraud detection algorithm for Streaming Transaction Data, with the goal of analysing customers’ historical transaction details and extracting behavioural patterns. The dataset for Cardholders transaction is created and classifying each transaction for genuine and fraud. Then, ML classifier, aggregate the transactions performed by cardholders from various categories in order to derive the behavioural patterns of the various groupings. Later, Random Forest Classifier (RFC) is trained over dataset and accuracy is evaluated for the classifier which resulted above 75.