Synthetic Identity Network for Attribute-Based Credit Fraud Detection
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Solution Overview
Problem
Existing systems fail to effectively track and identify synthetic identities and attributes, allowing fraudulent individuals to assemble and use fictitious information to obtain credit, which goes unnoticed by credit bureaus and poses a risk to financial institutions.
Innovation Solution
A synthetic identity network utilizing a user identity server and identity database to detect and flag potentially synthetic identities and attributes by comparing user attributes with stored profiles, and broadcasting alerts to financial servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If credit bureaus only record approved credit applications, then storage space is conserved and processing is simplified, but fraudulent synthetic identities go undetected and can be used repeatedly
Solution Approach 1:
The system performs preliminary actions by creating placeholder credit records for synthetic identities before actual credit approval occurs. When attributes are assembled during credit applications, the system proactively creates a credit record and assigns a synthetic identifier, enabling future detection of fraudulent activities involving these identities before they can cause significant harm.
Solution Approach 2:
The patent introduces an intermediary synthetic identifier system that mediates between credit bureaus and financial institutions. This intermediary layer allows credit bureaus to track synthetic identities without requiring direct integration between all financial institutions and credit tracking systems, simplifying the overall architecture while enabling fraud detection.
2Reliability
If credit records are created for all assembled identities, then fraud detection improves, but storage requirements and processing overhead increase significantly
Solution Approach 1:
The system applies local quality by creating detailed credit records only for synthetic identities detected through attribute assembly, rather than creating records for all identities. Normal legitimate identities continue to use traditional credit reporting methods, while only suspicious synthetic identities receive the enhanced tracking treatment, optimizing resource allocation.
Solution Approach 2:
The patent uses copying by creating simplified placeholder credit records for synthetic identities that contain essential tracking information (synthetic identifier, status flags) rather than full credit histories. This reduces storage requirements while maintaining the ability to detect and track fraudulent activities.
3Measurement precision
If the system compares user attributes against all stored identities, then identification accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system segments the identity verification process into two stages: first, a rapid filtering stage that checks for obvious synthetic identity indicators using hashed attribute comparisons; second, a detailed verification stage for flagged cases. This segmentation allows most legitimate applications to be processed quickly while maintaining high accuracy for detecting synthetic identities.
Solution Approach 2:
The patent applies partial action by performing attribute comparison only on critical fields (name, address, social security number) rather than all possible attributes. This partial comparison approach provides sufficient accuracy for detecting synthetic identities while significantly reducing processing time and computational resources required.
Data Source
AI summary
A synthetic identity network for detecting synthetic identities may receive a first request for credit including one or more user attributes, compare the one or more user attributes to one or more stored user identities, create a new user identity, flag the new user identity as a potentially synthetic identity based on comparing the one or more user attributes to the one or more stored user identities, receive a second request for credit including or more second user attributes, compare the one or more second user attributes to the one or more user attributes associated with the potentially synthetic identity, prepare a notice including the potentially synthetic identity and a credit request identifier, and transmit the notice to one or more servers.