Whitebox Machine Learning

Updated on 02.12.24
5 minutes to read
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Overview

In SEON, the whitebox machine learning algorithms are trained on each customer's separated data to identify patterns and behaviors. You can then implement rules to block certain user actions, such as suspicious logins, identity theft, or fraudulent transactions.

 

SEON's machine learning tools

Glance at our different machine learning tools to understand how they differ.

 WhiteboxBlackbox
Automatic retraining several times a dayYesYes
Uncovers complex fraud patternsYesYes
Human-readable rulesYesNo
Transparent decision-makingYesNo
Automatic rule creationYesNo
Can be used in rulesNoYes
Can effect fraud scoreNoYes
Can change transaction stateYesYes
Fraud probability scoringNoYes
Keeps you in controlYesYes
Fully automatable as neededYesYes
Available from Day 1No*Yes

* Whitebox machine learning requires account-specific training data to begin recommending rules: at least 1000 transactions with 100 in the DECLINE and 100 in the APPROVE state.

 

Using whitebox machine learning

The algorithm retrains itself even multiple times a day and creates human-readable rule suggestions with specific accuracy percentages. Our dedicated data scientists can also help you with resources and reporting.

Visit the Machine Learning tab of the Scoring Engine to review the rules created by the whitebox algorithm. Machine learning rules are divided into three rule categories by default: Complex rules, Heuristic rules, and Email clustering rules.

The algorithm automatically calculates the accuracy of all rules it creates based on past transactions. Accuracy scores compare the number of declined and accepted transactions the rule would affect. For example, a rule that would affect ten past transactions is 90% accurate if nine of these transactions are in the DECLINE state and only one is in APPROVE.

You can choose to enable these rules above a set accuracy threshold automatically or turn them on or off manually at any time by using the toggle on the rule list.

AI Rule Explanation

Our AI-based rule explanation makes machine learning rules even easier to understand. Just click on a rule to open up the Rule details window, where you’ll get an explanation of what each rule does and how it arrived at a risk score.

Complex rules

Complex rules are based on surprising connections between data points. These are flagged in past and future transactions. Complex rules contain several parameters and data points.

Complex rules listed on the Machine Learning tab of the Scoring Engine.

Heuristic rules

These rules are designed to decline transactions from fraudulent accounts after the second offense. Heuristic rules target a single identified parameter (e.g., IP=X).

Heuristic Rules listed on the Machine Learning tab of the Scoring Engine.

Email clustering rules

Email clustering was designed to enhance your fraud detection capabilities by identifying and grouping likely algorithmically generated email addresses, using data from the past 30 days. Learn more here.

Email clustering rules listed under Machine Learning rules

Review and enable rules

  1. Head to the Scoring Engine.
  2. Open the Machine Learning tab.
  3. Here, you can review the rules created by the algorithm. Click a rule to check details.
  4. Use the toggle on the left to enable and disable rules.

 

Machine Learning rule details

When you click on a machine learning rule, the modal includes advanced options. 

The Filter transactions button will take you to a list of all past transactions the rule would affect. Choose Add to custom rules if you'd like to tweak the parameters of the rule before turning it on.

The Rule Details modal includes advanced options to help you use whitebox rules.

 

Whitebox settings

Whitebox machine learning is enabled on your account by default. However, we won't turn rules on automatically unless you change your settings.

The Machine Learning tab of the Settings page houses all settings related to your whitebox and blackbox models. Find settings related to the whitebox model divided into Complex Rule Settings and Heuristic Rule Settings, and Segmentation.

Segmentation

You can automatically generate Machine Learning rules for a specific market segment and define which data point or models should consider your main market separator.

Complex rule settings

Using these settings, you can tell SEON to enable new Complex rules in your account automatically. All you need to do is set an accuracy threshold, and we'll do the rest. 

The algorithm will also maintain these rules in the long run – if a rule's accuracy falls below the threshold you set here, we'll turn it off automatically.

Heuristic rule settings

These settings will tell SEON to automatically enable any heuristic rules that meet the set criteria in your account.

Click the toggle and specify the transaction data fields that should be included in rules that turn on automatically. Finally, set an accuracy threshold, and we'll do the rest.

Email clustering settings

You can determine how often you want email clusters to refresh in the dropdown below.

 

 

Learn more

Read more about how SEON harnesses the power, speed, and accuracy of machine learning and what you can do to get the best results.

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