Cross-Service Fraud Detection via Shared Engine Trends
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Solution Overview
Problem
Existing fraud detection systems are not capable of utilizing trends from other services, leading to inefficiencies in detecting fraud and compromising security, as each service has its own independently defined fraud detection engine.
Innovation Solution
A fraud detection system that acquires user feature information and result information from one service and utilizes it to enhance fraud detection in another service, leveraging a different fraud detection engine to improve security by sharing detection trends across services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fraud detection engine is independently defined for each service, then the service can be operated autonomously, but fraud detection accuracy deteriorates due to inability to utilize trends from other services
Solution Approach 1:
The patent implements a shared fraud detection engine that serves multiple services simultaneously. The fraud detection engine is configured to receive user information from different services and perform fraud detection across them, making a single system perform multiple functions. This resolves the contradiction by improving fraud detection accuracy through shared learning while avoiding the complexity of maintaining separate independent engines for each service.
2Reliability
If fraud detection engines are shared across services, then fraud detection accuracy improves by utilizing trends from multiple services, but service autonomy and operational independence deteriorate
Solution Approach 1:
The patent segments the fraud detection system into two independent parts: a shared fraud detection engine that learns from multiple services, and service-specific interfaces that maintain operational independence. Each service can independently interact with the shared engine through standardized protocols, allowing fraud detection trends to be shared while preserving service autonomy and the ability to independently modify or remove services.
3Productivity
If separate fraud detection engines are maintained for each service, then service independence is preserved, but productivity deteriorates due to inability to leverage shared detection trends
Solution Approach 1:
The patent merges multiple service-specific fraud detection engines into a single shared fraud detection engine that processes requests from multiple services. This consolidation reduces the total number of engines from N (one per service) to 1, improving productivity by enabling the engine to learn from and detect fraud patterns across all services simultaneously, while maintaining the ability to serve each service's specific needs.
Data Source
AI summary
A fraud detection system, comprising at least one processor configured to: acquire user feature information relating to a feature of a user in a first service; acquire user identification information with which the user is identifiable; acquire, based on the user identification information, result information relating to a result of fraud detection of the user in a second service which uses a different fraud detection engine for detecting a fraud from a fraud detection engine of the first service, and detect a fraud in the first service based on the user feature information in the first service and the result information in the second service.