Detecting fraud from customer transactions

Ruojia Qi


Supervised by Yuhua Li; Moderated by Richard Booth

This project aims to develop a method that detects fraudulent e-commerce transactions so that customers are protected from financial fraud. It will apply suitable machine learning techniques to deal with distinct characteristics of e-commerce transaction data which is highly imbalanced. You may get dataset(s) for your project, but a potential dataset that can be used for this project can be downloaded from https://www.kaggle.com/c/ieee-fraud-detection/overview.

This project requires you to have good knowledge and skills in programming, machine learning and maths.

Final Report (02/10/2020) [Zip Archive]

Publication Form