Fraud Detection Rule Population Engine
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Solution Overview
Problem
Merchants face challenges in efficiently detecting fraudulent transactions, as existing fraud detection systems can be compromised, and managing numerous merchant profiles becomes unwieldy, leading to significant resource expenditure and potential financial losses.
Innovation Solution
A system and method for generating and automatically populating fraud detection rules and merchant profiles with a core set of rules, allowing for efficient management and application across multiple profiles, reducing the need for manual intervention and minimizing transcription errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If merchants manually review each transaction to detect fraud, then fraud detection accuracy improves, but time consumption and resource expenditure increase significantly
Solution Approach 1:
The patent replaces manual mechanical review of transactions with an automated fraud detection system that uses algorithms and rules to evaluate transactions automatically. This substitution maintains fraud detection capability while eliminating the time-consuming manual process, allowing the system to process transactions at machine speed without human intervention for each individual transaction.
Solution Approach 2:
The fraud detection system enables merchants to self-serve by automatically detecting and flagging fraudulent transactions without requiring manual review. The system serves itself by using predefined rules and algorithms to autonomously identify potential fraud, reducing the need for merchant staff to manually examine each transaction while maintaining detection accuracy.
2Adaptability or versatility
If merchants establish numerous merchant profiles to meet business requirements, then adaptability improves, but profile management complexity increases
Solution Approach 1:
The patent implements a universal set of core fraud detection rules that can be applied across multiple merchant profiles simultaneously. Instead of creating and managing separate rule sets for each merchant profile, the system uses a single universal rule set that adapts to different business requirements through configuration options, thereby reducing management complexity while maintaining adaptability.
Solution Approach 2:
The patent merges the management of fraud detection rules by allowing a single core rule set to serve multiple merchant profiles. This consolidation reduces the number of separate profiles and rules that need to be managed individually, simplifying the overall system structure while still accommodating diverse business requirements through the flexible application of the unified rule set.
3Reliability
If fraud detection rules are modified to address compromised systems, then security improves, but the risk of rule errors and misidentification increases
Solution Approach 1:
The patent implements feedback mechanisms that allow the fraud detection system to learn from outcomes and adjust rule applications accordingly. By incorporating feedback loops where transaction outcomes feed back into rule refinement, the system can maintain security while reducing rule errors over time, as the feedback helps identify and correct misidentifications without requiring frequent manual rule modifications.
Solution Approach 2:
The patent applies preliminary actions by establishing core fraud detection rules in advance that are designed to be robust and error-resistant. These pre-configured rules undergo validation and testing before deployment, reducing the likelihood of rule errors and misidentifications while maintaining security. The preliminary setup includes default configurations that have been optimized to minimize false positives and negatives.
Data Source
AI summary
Embodiments of the invention are directed to a fraud detection system that stores fraud detection rules and merchant profiles. The fraud detection system allows a user to designate fraud detection rules as core fraud detection rules, and the fraud detection system can automatically populate new profiles with the user's core fraud detection rules.