Fraud Rule System with Shadow Mode Testing
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Solution Overview
Problem
The financial industry faces challenges in rapidly updating fraud rules to counter evolving fraudulent patterns in financial transactions, leading to a dynamic 'whack-a-mole' game where fraudsters can gain an upper hand if developers are hindered in quickly deploying new or improved rules.
Innovation Solution
A system and method for defining and deploying fraud rules that include fraud criteria and responses, with activation criteria, allowing for quick inclusion in financial transaction product flows, facilitated by a fraud module that enables rule creation, testing, and activation, including a shadow mode for testing without impacting live transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fraud rules are updated frequently to counter evolving fraudulent patterns, then fraud detection effectiveness is improved, but the complexity and time required for rule development and deployment increases
Solution Approach 1:
The fraud rule system is segmented into modular components including rule templates, fraud scenarios, and configurable parameters. This allows individual rules to be developed, tested, and deployed independently without affecting the entire system, reducing deployment complexity while maintaining detection effectiveness.
Solution Approach 2:
Fraud rules are pre-configured with templates and default parameters based on common fraud scenarios. This preliminary setup reduces the time and complexity required for rule development, as developers only need to customize specific parameters rather than building rules from scratch, enabling faster response to evolving fraud patterns.
2Reliability
If fraud rules are updated frequently to counter evolving fraudulent patterns, then fraud detection effectiveness is improved, but the time required for rule activation increases
Solution Approach 1:
Fraud rules are pre-configured with templates and default parameters based on common fraud scenarios. This preliminary setup reduces the time and complexity required for rule development, as developers only need to customize specific parameters rather than building rules from scratch, enabling faster response to evolving fraud patterns.
Solution Approach 2:
The system includes automated testing and validation mechanisms that self-verify rule correctness before deployment. This self-service capability reduces manual review time and accelerates rule activation, allowing rapid response to emerging fraud threats without sacrificing quality control.
3Reliability
If comprehensive testing is performed before deploying fraud rules, then rule reliability is improved, but the productivity of rule deployment decreases
Solution Approach 1:
Testing is segmented into multiple independent stages including unit testing of individual rules, integration testing of rule interactions, and validation against historical fraud data. This staged approach allows comprehensive testing without requiring all tests to complete before any rule deployment, improving overall deployment productivity while maintaining reliability.
Solution Approach 2:
The system implements confidence-based deployment where rules with high confidence scores (based on template maturity and initial testing results) can be deployed with reduced testing requirements. This partial action approach allows productive deployment of high-confidence rules while maintaining thorough testing for less certain rules, balancing reliability and productivity.
Data Source
AI summary
A method of employing fraud rules associated with identification of fraud in connection with financial transactions may include receiving information associated with a fraud scenario and defining a fraud rule based on the information. The fraud rule may include fraud criteria used to analyze financial transaction data to detect the fraud scenario and may also include a fraud response. The method may further include defining activation criteria for the fraud rule and enabling activation of the fraud rule for inclusion in product flows associated with the financial transactions in response to the activation criteria being met.


