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Fraud Detection

Flag unusual transactions and behaviors that might indicate fraud attempts. Analyzing historical transaction patterns per customer/customer segment, spot anomalies. Examples of fraud include credit card fraud, loan fraud fraud, on-boarding customers fraud

Business value: Reduces Fraud Loss, Gain Customer Trust, and Improve Customer Experience.

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ROI Examples
Data Needed

1. Get Inspired

Understand the Use-case under 5 minutes

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2. Know More

Get to know more Business and Technical details about the use-case (15-30 minutes)

Deeper Intro

More detailed introduction covering business and technical aspects

Business Focused

Case studies, Organizational Aspects, Return on Investment examples

Tech focused

More details on the technical aspects of the use-case

3. Do

Technical resources that will help you implement the use-case (notebooks, tutorials..)

Data Sets

Data Sets you can use to build Demos, POCs, or test Algorithms

Synthetic Financial Datasets For Fraud Detection

Synthetic datasets generated by the PaySim mobile money simulator

Credit Card Fraud Detection

The dataset contains transactions made by credit cards in September 2013 by European cardholders.
This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions

IEEE-CIS Fraud Detection

The data comes from Vesta’s real-world e-commerce transactions and contains a wide range of features from device type to product features (with “isFraud” as an attribute, for fraudlent transactions)


Off-the-Shelf Products using AI for Fraud Detection