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Overview
This North52 rules engine example implements a fraud detection and order management system for Shopify orders. Shopify sends information to Dataverse via a webhook. This triggers a Flow and calls a custom action which is bound to a North52 Formula. The rules are evaluated and if fraud or a problem customer is determined by the rules, North52 connects via the Shopify API to update the order.
Key Features
- Automated fraud prevention based on spending patterns
- Risk-based decision making with different thresholds
- Integration with Shopify using GraphQL APIs
- Historical pattern analysis to identify unusual behavior
- Manual review workflow for suspicious but not clearly fraudulent orders
This system helps prevent fraudulent orders while minimizing false positives by using the customer’s own purchase history as a baseline.
Rules for Shopify integration
| Rule # | Description |
|---|---|
| 1 | Fraud Assessment – Evaluates the current order against the customer’s historical patterns: High Risk (3x Average): If current order > 3× average order value:
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| 2 | Fraud Assessment – Evaluates the current order against the customer’s historical patterns: Medium Risk (1.5x Average): If current order > 1.5× average order value:
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| 3 | Problem Customer Check – Queries the system for previous problem cases:
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