UPI Fraud Detection Using Machine Learning

Vatshayan
Oct 26, 2024
1 min read

Updated: Apr 19, 2025

UPI Fraud Detection Using Machine Learning is a project aimed at identifying and preventing fraudulent activities in UPI (Unified Payments Interface) transactions. With the increasing popularity of digital payments, ensuring the security of users and their financial transactions has become crucial. This project leverages the power of machine learning algorithms to analyze that transaction is fraud or not fraud.

https://www.youtube.com/watch?v=uzVdxlG1gIY

The solution involves collecting and pre-processing large datasets of UPI transactions to identify key features associated with genuine and fraudulent activities. By using different machine learning algorithms we can determine the fraud activities and also help save customer, clients and regular innocent people to get scammed.

Domain : Machine Learning Project

Tech Used:

Front End : html, css & js

Back End : python

Datasets : csv

Project Includes :

PPT
Synopsis
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Project Code
Base Research Papers
Video Tutorials

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2 Comments

AdamIHood

7 days ago

Great practical write-up on UPI Fraud Detection using machine learning. I like that it emphasizes collecting and preprocessing real transaction datasets and then extracting features to distinguish genuine vs fraudulent activity. It would be even more useful if you shared which evaluation metrics you focused on (precision/recall, ROC-AUC) and how you handle class imbalance. Also, for preparing datasets like CSV to SQL, CSV to SQL seems like a helpful tool to streamline the pipeline.

Unknown member

Apr 02, 2025

I want this project