Financial Data Structures for Efficient Portfolio Transaction Processing
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Solution Overview
Problem
Current computerized financial transaction systems face inefficiencies in data transfer and processing due to the lack of structured data formats, leading to inaccuracies and increased computational resources needed for data extraction and transmission.
Innovation Solution
Implementing data structures that organize financial data into predefined formats, allowing for efficient transfer and processing across computer networks, including retrieval of portfolio states, market data, predictions, and user preferences to determine and execute transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If unstructured data formats are used for financial data transfer, then system flexibility and ease of data creation are improved, but data transfer speed and processing accuracy deteriorate
Solution Approach 1:
The patent applies parameter changes by transforming financial data from unstructured formats into structured formats with specific parameters and fields. This standardization enables faster processing and transfer while maintaining the ability to represent diverse financial instruments and transactions through defined data structures.
2Ease of manufacture
If unstructured data formats are used for financial data storage, then ease of data entry is improved, but computational resources required for data extraction and processing increase
Solution Approach 1:
The patent implements preliminary action by pre-defining data structures, schemas, and validation rules before data entry. This allows data to be entered into predetermined formats with built-in validation, reducing the need for complex post-processing and extraction operations, thereby lowering computational resource requirements.
3Adaptability or versatility
If unstructured data formats are used for financial transactions, then system adaptability to different transaction types is improved, but data transfer accuracy and reliability deteriorate
Solution Approach 1:
The patent applies universality by creating a standardized data structure framework that can accommodate multiple transaction types and financial instruments through a common set of fields and parameters. This universal structure ensures consistent data representation and validation across different transaction types, improving reliability while maintaining adaptability.
Data Source
AI summary
An example computer-implemented method includes retrieving, by at least one processor, one or more first data structures pertaining to a current state of a financial portfolio of a first user, one or more second data structures pertaining to one or more historical and/or current states of a financial market, one or more third data structures pertaining to one or more predictions regarding one or more financial assets of the financial market, and one or more fourth data structures pertaining to the first user's preferences with respect to the financial portfolio. The method also includes determining, by the at least one processor, one or more transactions to be conducted on the financial market based on the first, second, third, and fourth data structures. The method also includes executing, by the at least one processor, the one or more transactions.