Asset Data Normalization and Validation for Transaction Processing
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Solution Overview
Problem
Existing systems face challenges in effectively and accurately processing, validating, and communicating data between different sources or parties due to varying data formats and configurations, leading to increased costs, time, and resource consumption, particularly in electronic asset transaction processes like mortgage note clearing and settlement.
Innovation Solution
A data management system that receives, normalizes, and validates data against a standard reference database, automatically extracts and compares data elements, and ensures data accuracy and integrity, acting as a central counterparty to facilitate transactions by translating and standardizing data formats and formats, and managing asset transfers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is processed in various different formats and configurations from multiple sources, then data coverage and source compatibility are improved, but processing complexity and time increase
Solution Approach 1:
The patent introduces a central data management system that acts as an intermediary between multiple data sources with different formats and configurations. This system receives data in various formats, automatically normalizes it to a standard format, and then distributes it to recipients. The intermediary handles the complexity of format conversion and validation centrally, preventing this complexity from propagating to each individual data source or recipient system.
Solution Approach 2:
The system dynamically changes data parameters including format, structure, and configuration to match the requirements of different sources and recipients. It automatically detects the incoming data format and transforms it into the required standard format through parameter adjustment, enabling seamless interoperability between systems with different data specifications without requiring manual configuration or complex processing logic at each endpoint.
2Reliability
If additional data processing is performed to ensure accuracy and validation, then data quality and integrity are improved, but processing time and resource consumption increase
Solution Approach 1:
The system performs preliminary data validation, normalization, and format standardization automatically as data enters the management system, before the data is distributed to recipients. By conducting these validation actions in advance, the system ensures data accuracy and quality are established early in the process, preventing the need for repeated validation and processing at subsequent stages, thereby reducing overall processing time despite the initial validation overhead.
3Measurement precision
If data is manually processed and validated between parties with different configurations, then data accuracy can be ensured, but costs and resource consumption increase
Solution Approach 1:
The data management system automatically performs validation, normalization, and format conversion without requiring manual intervention from data sources or recipients. The system self-manages the entire data processing workflow including detecting data formats, applying appropriate transformation rules, validating data against schemas, and routing data to the correct recipients. This automation eliminates the need for manual processing resources while maintaining high validation accuracy through systematic rule-based processing.
Data Source
AI summary
Systems and methods for data management via a data management system are provided. The data management system can receive data relating to one or more assets, the data in one or more formats, convert the asset data to a uniform format, extract data elements, compare and normalize the data elements against a standard reference database, and automatically validate the one or more data elements. The validation can be performed by comparing data elements to requirements set by the data management system or other party, and confirming that the data elements match the requirements. The validation can operate to initiate an asset transaction.