Self-Aggregated PII Profile Maps for Faster Loan Verification
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Solution Overview
Problem
The existing process of collecting, validating, and sharing personal identifiable information (PII) for financial transactions and loans is time-consuming, repetitive, and costly, with lenders bearing regulatory liability if data handling is not compliant and secure, while consumers lack control over their data.
Innovation Solution
A computer-based method and system for self-aggregation of PII, creating a user-specific profile map data structure with standardized schemas, allowing iterative data updates, secure storage, and controlled access, enabling users to manage and share their data compliantly and efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional direct verification forms are used for each data point, then data accuracy and validity are ensured, but the process becomes time-intensive and costly
Solution Approach 1:
The patent segments the verification process into automated data collection from multiple electronic resources, classification into standardized categories, and selective validation. This divides the monolithic verification process into manageable components that can be executed efficiently by the logic layer processor, reducing overall verification time while maintaining accuracy through systematic processing.
Solution Approach 2:
The system performs preliminary data aggregation and classification from multiple electronic resources before the actual verification process. By pre-organizing data into standardized categories and identifying required data points in advance, the system reduces the time needed for actual verification while ensuring completeness and accuracy of the collected information.
2Productivity
If comprehensive PII data is collected for loan processing, then lending decisions can be made, but regulatory liability and security risks increase for lenders
Solution Approach 1:
The patent introduces a user-controlled data repository as an intermediary between borrowers and lenders. This repository stores aggregated PII data with user consent and provides controlled access to authorized entities. The intermediary mechanism enables efficient loan processing by making data readily available while reducing lender liability through user-controlled access and consent management, creating a trusted third-party interface.
Solution Approach 2:
The system enables users to self-manage their PII data through the repository, controlling who accesses their information and for what purposes. This self-service approach reduces regulatory liability for lenders by shifting data control and consent management to the users themselves, while maintaining productivity through automated data provision to authorized entities.
3Reliability
If users have control over their PII data, then privacy and security are improved, but data accessibility for legitimate uses may be reduced
Solution Approach 1:
The patent implements dynamic access control where user consent and data sharing permissions can be modified at any time. The system adapts data accessibility based on user preferences, transaction context, and authorized entity credentials. This dynamic mechanism maintains strong security through user control while ensuring ease of operation for legitimate uses by automatically granting access when proper authorization and consent are present.
Solution Approach 2:
The data repository serves multiple functions: storing PII data, managing user consent, controlling access for various entities (lenders, creditors, government agencies), and enabling different types of transactions. This universal platform approach ensures data security through centralized control while maintaining ease of accessibility for legitimate purposes by providing a standardized interface for authorized access across multiple use cases.
4Productivity
If standardized data schemas are implemented, then data processing efficiency is improved, but flexibility in handling diverse data formats is reduced
Solution Approach 1:
The patent employs parameter changes by implementing a standardized data schema with defined categories and data types that the logic layer processor uses to classify and process information. This standardization improves processing speed and efficiency by enabling automated validation and consistent handling. The system maintains flexibility by allowing users to input diverse data formats initially, which are then transformed into the standardized schema for processing, effectively adapting different formats to a common structure.
Data Source
AI summary
A method includes receiving, by a logic layer processor, over a communication network, from a plurality of electronic resources, initial user personal identifiable information (PII) of a user of a plurality of users. The user PII includes a plurality of data elements. The plurality of data elements of the initial PII of the user are classified to populate a profile map data structure having a standardized predefined data schema of a plurality of vector elements so as to form a user-specific profile map data structure of the user. Additional user personal identifiable information (PII) of the user is iteratively received from the plurality of electronic resources. The additional user PII of the user is iteratively classified to update the user-specific profile map data structure of the user. A plurality of user-specific data management software functions is enabled based on the user-specific profile map data structure.