Multi-layered Edge Gatekeeper Architecture for Fraud Mitigation
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Solution Overview
Problem
Digital transactions are susceptible to fraudulent activities, with existing automated systems often detecting fraud with high latency and resource consumption, making it difficult to reverse unauthorized transactions in a timely manner.
Innovation Solution
A multi-layered fraud mitigation system utilizing an N-tiered set of gatekeeper units with edge-computing devices that perform successive validation checks and emit alerts to trigger advanced validation checks, reducing resource usage and enhancing detection efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated systems are used for fraud detection, then detection capability is improved, but system resource consumption increases
Solution Approach 1:
The fraud detection system is divided into multiple gatekeeper units organized in an N-tiered hierarchy. Each gatekeeper unit performs specific validation checks on transaction requests, segmenting the overall detection task into manageable portions that can be processed in parallel, thereby improving detection capability while distributing resource consumption across multiple units.
Solution Approach 2:
The gatekeeper units perform preliminary validation checks on transaction requests before they are fully processed. By conducting initial fraud detection screenings in advance, the system identifies and flags suspicious transactions early in the processing pipeline, reducing the need for resource-intensive deep analysis of all transactions.
2Measurement precision
If comprehensive validation checks are performed, then fraud detection accuracy is improved, but processing latency increases
Solution Approach 1:
Validation checks are segmented into multiple tiers with increasing depth of analysis. Gatekeeper units in lower tiers perform quick, lightweight validation checks that process transactions rapidly, while only suspicious transactions are escalated to higher tiers for more comprehensive validation, thus maintaining accuracy while reducing average latency.
Solution Approach 2:
The system applies partial validation checks to the majority of transactions that appear normal, performing only the necessary minimum validation to process them quickly. Comprehensive validation is applied selectively only to transactions that trigger suspicion flags, achieving high detection accuracy for fraudulent transactions without subjecting all transactions to resource-intensive full validation.
3Reliability
If multiple gatekeeper units are deployed, then detection coverage is improved, but system complexity increases
Solution Approach 1:
Each gatekeeper unit is designed as a universal, multi-functional component that can handle various types of validation checks and transaction types. The gatekeeper units use common protocols and interfaces for communication, allowing them to be deployed in different configurations and numbers without requiring custom integration work, thus improving detection coverage while managing complexity through standardization.
Data Source
AI summary
Aspects of the disclosure relate to edge-computing (“EC”)-based systems and methods for fraud mitigation. The systems and methods may utilize a multi-layer architecture. The architecture may include a set of N gatekeeper units, and each gatekeeper unit may be associated with an EC device. When a transaction request is received, the request may be processed at a first gatekeeper unit, and, if validated, successively processed by the set of N gatekeeper units. If any gatekeeper unit flags the request as suspicious, the unit may emit an audible alert that may be sensed by the associated EC device. The EC device may transmit a signal to one or more of the other gatekeeper units to perform additional processing for the request. When the request reaches the Nth gatekeeper unit and achieves validation, the transaction may be executed via a central server connected to a transaction network.