Automated Link Analysis for Scalable Data Transfer Fraud Detection
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Solution Overview
Problem
Current link analysis methods for fraud prevention in data transfers, such as online account opening, rely on manual visual representation review, which is error-prone and not scalable.
Innovation Solution
An automated process that creates link presence indicators between data records without a visual representation, using an algorithm to assign labels based on variable values, and performs analytics on these links to identify potential fraud.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual visual representation review is used for link analysis, then investigation accuracy can be maintained through human judgment, but productivity and scalability are severely limited
Solution Approach 1:
The patent replaces the manual mechanical review process with an automated computer-based system that uses algorithms to analyze link representations. The system automatically generates link presence indicators, performs analytics, and identifies suspicious activities without requiring human investigators to manually examine visual representations, thereby maintaining accuracy while dramatically increasing productivity.
Solution Approach 2:
The system enables self-service automated analysis where the computer automatically performs link analysis, generates indicators, and identifies fraud patterns without human intervention. The automated process serves itself by taking input data, processing it through analytical algorithms, and producing fraud detection results independently, freeing human investigators from manual review tasks.
2Productivity
If automated link analysis is implemented, then productivity and scalability are improved, but complexity of the system increases
Solution Approach 1:
The patent segments the link analysis process into distinct automated components: data reception modules that collect input data, link presence indicator generation modules that create linkage indicators, analytics modules that perform analysis, and fraud identification modules that detect suspicious activities. This segmentation allows each component to be independently developed, tested, and optimized, managing system complexity while maintaining high productivity.
Solution Approach 2:
The system manages complexity by changing parameters from manual visual inspection to automated algorithmic analysis. The computer-based system uses configurable parameters and algorithms that can be adjusted without requiring complex manual processes, enabling scalable automation where complexity is managed through parameter configuration rather than procedural complexity.
3Device complexity
If manual review processes are used, then system complexity remains low, but error rates increase due to human factors
Solution Approach 1:
The patent replaces manual human review with automated computer-based analysis to eliminate human errors such as fatigue, bias, and inconsistency. The automated system consistently applies analytical algorithms to all data without variation, significantly reducing error rates while the modular architecture keeps system complexity manageable through standardized processing components.
Data Source
AI summary
Computing platforms, methods, and storage media for processing instructions associated with one or more data transfers are disclosed. Exemplary implementations may: obtain, by the apparatus, input data associated with a set of data transfer requests, the input data including a plurality of records; generate, by the apparatus and based on the input data and in the absence of a visual representation of the plurality of records, link presence indicators for the input data by automatically creating indications of presence of links between the plurality of records based on one or more of the plurality of variables; and create, by the apparatus and for storage in a memory, a set of linked data based on the input data and the generated linking relationships. Exemplary implementations focus on whether, rather than how, items are linked together, in an automated and scalable approach, and may perform analytics on the links and entities.