Identifier-Based Asset Data Validation for Continuous AI Training
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Solution Overview
Problem
Existing systems lack an efficient and compliant platform for creating and trading digital securities representing real assets, such as real estate, while maintaining transaction privacy and adhering to securities regulations.
Innovation Solution
A computer technology platform with semi-redundant ledgers that synchronize automatically, allowing for the creation and trading of digital tokens representing fractional interests in real assets, while keeping personally identifiable information private and using a dual ledger system to ensure compliance with securities regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized ledger system is used to maintain transaction records, then data consistency and compliance tracking are improved, but system vulnerability to single points of failure and regulatory changes increases
Solution Approach 1:
The patent divides the centralized ledger into multiple distributed ledger nodes across different jurisdictions. Each node maintains a copy of the transaction records, eliminating single points of failure while preserving data consistency through cryptographic verification and consensus mechanisms.
Solution Approach 2:
The system dynamically adjusts ledger parameters such as block size, confirmation requirements, and synchronization intervals based on regulatory changes and system load. This allows the distributed ledger to maintain reliability while adapting to different operational conditions without requiring complete system redesign.
2Loss of information
If detailed transaction data is stored for regulatory compliance, then auditability and compliance monitoring are improved, but data privacy and security risks increase
Solution Approach 1:
The patent extracts personally identifiable information (PII) from transaction records and stores it separately in encrypted form. The main ledger contains only hashed or anonymized identifiers, allowing full auditability of transaction flows while preventing direct identification of parties involved, thus reducing data privacy risks.
Solution Approach 2:
The system introduces cryptographic hash functions and zero-knowledge proofs as intermediaries between transaction data and regulatory oversight. These mathematical constructs enable verification of compliance without exposing underlying sensitive information, maintaining auditability while protecting data privacy.
3Measurement precision
If manual data validation processes are used for asset onboarding, then data accuracy and compliance verification are improved, but processing time and operational costs increase
Solution Approach 1:
The patent implements preliminary automated validation of asset data against predefined compliance criteria before manual review. Documents are scanned, verified for authenticity, and cross-checked with regulatory databases automatically, pre-filtering obvious errors and reducing the burden on manual reviewers, thus maintaining accuracy while reducing processing time.
Solution Approach 2:
The system provides real-time feedback to users during the asset onboarding process, immediately flagging incomplete or non-compliant information. This guided feedback loop prevents errors from propagating through the system and reduces the need for repeated manual corrections, improving both accuracy and efficiency.
4Reliability
If traditional securities trading platforms are used, then regulatory compliance is maintained, but accessibility for retail investors and trading efficiency are limited
Solution Approach 1:
The patent creates a multi-functional platform that serves both traditional institutional investors and retail investors through a unified distributed ledger system. The same infrastructure supports complex institutional trades and simple retail purchases, maintaining regulatory compliance through programmable compliance rules while dramatically improving accessibility and trading efficiency for all user types.
Data Source
AI summary
The present invention extends to methods, systems, and computer program products for data retrieval and validation for asset onboarding and deriving asset characteristics. A first set of data associated with an asset is collected. Identifiers associated with the first set of data are created. A second set of data associated with the asset is collected based on the identifiers. The first set of data set and the second set of data are compared based on the identifiers. The first set of data is validated based on the comparison. An artificial intelligence module is trained as part of a continuous training cycle in view of validation findings. Concurrently with artificial intelligence module training, one or more characteristics of the asset are derived from the first set of data.