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AI Machine Learning for
Fraud Detection Solution

"SEON's machine learning finds similarities based on your input and proposes rules to spot abuses you wouldn't notice otherwise."

Pre-built, Customizable, and Suggested Rules & Risk Scores

Fraudsters have behavioral patterns. Lean on our machine learning engine to create complex rules to beat them, without ever giving up control.

Whitebox Machine Learning

We know fraudsters. Start fighting fraud with SEON within minutes thanks to our robust default rule set based on our experience and data. Detect suspicious devices, behavior patterns, and shady connections between users with minimal setup.

Blackbox Machine Learning

Our Blackbox ML crunches numbers behind the scenes, giving you another line of defense against fraud. Blackbox calculates a fraud probability using the transaction's characteristics and your historical data. You still always get the final say by setting what Blackbox can and cannot do.

Labels and Feedback

SEON’s AI learns with feedback; getting even more effective at detecting fraud risks unique to your business. Feedback via our interface, or use our Label API to automate it. Quick and frequent feedback loops sharpen our AI to be even smarter for you.

Bolster your Fraud Detection

With precise and dynamic rules based on a variety of data and methods

Perfect as

Scaling your fraud prevention efforts

Tackling risky markets with ease

Available as

Be trained on existing data

Deploy today with preset rules

Leverage the power of the C5.0 algorithm

Automatically approve or decline transactions

See How SEON Stops Fraud

Stop All Fraud-Related Threats

Identity theft

Account farming

Money laundering

Account takeover

Phishing attacks

Payment reversals

Disputed payments

Synthetic identity

Bot attacks

Regulatory fines

AI & Machine Learning

SEON includes powerful machine learning designed to help you identify risk patterns automatically. Based on flagged signups, logins, and transactions, it can recommend new rules to help spot patterns of user behavior. You can then calculate the accuracy of these rules and make decisions automatically according to confidence ratings.

Our whitebox rule suggestion algorithm is built on C5.0 and works best after processing at least 1,000 transactions. You can then receive suggestions for complex or heuristic rules to thwart even the most sophisticated fraudsters. Meanwhile, a separate blackbox ML module at SEON will examine each user’s activity and flag suspicious customers separately to the main engine, for added peace of mind.

The whitebox module provides human-readable reasoning to aid your analysts. The blackbox module uses CatBoost to calculate risk via a plug-and-play model that requires little interaction. As a SEON customer, you can choose to make use of both modules, just one or neither. The goal is always the same: to improve the accuracy of your fraud detection over time – based on your real and unique business landscape.

FAQ

Is SEON’s machine learning algorithm blackbox or whitebox?

SEON offers both whitebox and blackbox solutions. You can start straight out of the box with the blackbox machine learning tool, which will tell you when a user is demonstrating suspicious behavior. This is an extra check that does not interfere with your fully readable ruleset-based fraud scoring. Moreover, you can also make use of our separate whitebox solution that delivers human-readable and testable rules that will work specifically for you.

How long does it take for SEON’s whitebox machine learning to suggest rules?

Our whitebox machine learning engine delivers the best results after it’s been fed at least 1000 declined transactions (or user actions), ideally with labels

What algorithm is SEON’s machine learning model built on?

SEON’s whitebox machine learning algorithm, which suggests new rules, is built on C5.0. The blackbox module, which provides blackbox risk scoring, uses CatBoost.

Where can I find more information on using SEON Machine Learning Model?

You can learn more about how SEON’s SEON Machine Learning Model in our Knowledge Base. Here is an article too about fraud detection in machine learning too.

Start fighting fraud now

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AI Machine Learning for Fraud Detection Solution