Hashed Identity Document Verification for Synthetic Fraud Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems struggle to effectively detect and mitigate synthetic identity fraud, particularly in customer onboarding processes, where fraudsters create fictitious identities using real social security numbers combined with fictitious data.
Innovation Solution
An adaptive analytics and data platform that compares hashed values of customer-imaged identity documents to historical data, generating risk indicators and alerts for potential fraud, while allowing system users to define alerts and collaborate in preventing fraud.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional identity verification methods are used, then the process is simple and fast, but synthetic identity fraud can still occur undetected
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing hashed versions of identity document images and data in a database before verification occurs. When a new verification request arrives, the system compares hashed values against the pre-stored data to detect synthetic identities, enabling fraud detection before the fraudster completes the onboarding process.
Solution Approach 2:
The patent introduces an intermediary hashing mechanism that transforms identity documents into hashed representations for comparison. This intermediary layer (the hashing function and database) enables the system to detect synthetic identities without directly analyzing the original documents, adding detection capability while maintaining system simplicity.
2Reliability
If comprehensive identity document verification is performed, then fraud detection improves, but processing time increases
Solution Approach 1:
The patent replaces complex mechanical verification processes with cryptographic hashing operations. Instead of manually or computationally intensive analysis of identity documents, the system uses hashing algorithms to create compact representations that can be quickly compared in databases, significantly reducing processing time while maintaining verification accuracy.
Solution Approach 2:
The system changes the verification parameters by working with hashed values rather than original document data. This parameter transformation allows for rapid comparison and detection while reducing the computational burden, enabling comprehensive verification without excessive processing time delays.
3Measurement precision
If hashed value comparison is used for fraud detection, then detection accuracy improves, but data security risks increase
Solution Approach 1:
The patent uses copying by creating hashed versions (copies) of identity documents for storage and comparison. These hashed copies preserve the essential verification information needed for fraud detection while eliminating sensitive original data from the verification process, thereby improving detection precision without compromising security.
Solution Approach 2:
The system extracts only the essential verification information from identity documents by applying hashing functions. This extraction process removes sensitive data elements while retaining the cryptographic fingerprints needed for fraud detection, achieving high detection precision while minimizing data security risks through data minimization.
4Reliability
If collaborative alert system is implemented, then fraud prevention effectiveness improves, but system complexity increases
Solution Approach 1:
The patent implements universality by designing a multi-functional platform that handles document verification, fraud detection, data storage, and collaborative alerting through a single integrated architecture. The same hashing and database infrastructure serves multiple purposes: verifying identities, detecting fraud patterns, storing historical data, and enabling collaborative alerts across organizations, thereby improving effectiveness without proportionally increasing complexity.
Data Source
AI summary
A data analytics system/method operative in conjunction with a data repository storing data regarding each of a multiplicity of frames including images of ID documents, including receiving at least one image generated by an image capturing device such as a camera or scanner; providing document data, derived by a hardware processor from the image capturing device, which characterizes a document depicted in the image; providing person data, derived by a hardware processor from the image, which characterizes a person who may bear the document depicted in the image; and generating inputs for identification of potential fraudulent attempts including analyzing whether the document data exists within the data regarding each of the multiplicity of images of ID documents; and/or analyzing whether the person data exists within the data regarding each of the multiplicity of images of ID documents.