Prevent loss

Fraud & return to origin (RTO) orders may be 50% of your e-commerce orders. Don’t let fraudulent returns get the better of your business.

Protect your revenue

Use our services to predict fraud transactions and strike first. Increase your revenue and reduce RTO losses.

Quick & Easy setup

Plug and play cloud based platform which enables you to analyse your product returns, detect fraud risk and suggest relevant action.

How does it work?

Workflow chart
Key Features
Detect

Use our ML model which considers more than 400 signals to develop an integrated fraud detection solution.

Suggest

Flipkart Fraud Manager suggests relevant action that should be taken on each transaction to help you proactively avoid frauds. You also get deeper insights into the model results through reasons for each suggested action.

Analyse

Get access to user friendly tools which helps you explore and Investigate each case in detail. A single view where you can monitor all order, account and seller related details for returns fraud.

Report

Each email ID, contact number, address and bank account is verified and tagged as per their risk profile to help you take an informed decisions.

Consult

Best practices for fraud management given our experience as India’s leading e-commerce portal. Optimize and contextualize the platform reports for better business decisions.

The Flipkart Advantage

Quick & easy setup
Quick & easy setup

Our solution is very simple to integrate and is completely API driven.

ML models trained on huge dataset
ML models trained on huge dataset

Our fraud and risk scoring models are trained on billions of actual transactions with high levels of accuracy.

Domain expertise through business consulting
Domain expertise through business consulting

We extend our own experience with Fraud management as the leading ecommerce portal of India.

Built for scale
Built for scale

Reliable and scale tested platform which can efficiently handle any volume of transactions. More than 1.5 billion transactions processed till date.

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