Financial Data Object Mapping via Tag-Value Segmentation
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Solution Overview
Problem
Current financial management software struggles to efficiently consolidate and analyze data from disparate sources and formats, requiring frequent model changes and manual verification of 'consolidated' information, especially when dealing with multiple financial institutions and changing tax rules.
Innovation Solution
A computerized method that converts incoming financial data into a flat data structure, allowing for the creation of objects based on user-defined models, resolving conflicts and ambiguities during data processing, and enabling easy querying and modification of data models without the need for migration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If commercial financial software packages are used to manage financial data from multiple sources, then data consolidation is achieved, but the system requires frequent model changes and manual verification when dealing with disparate formats and changing tax rules
Solution Approach 1:
The patent segments financial data into standardized atomic elements (transaction, holding, position, event) with defined schemas. Each data type is broken down into specific fields (e.g., transaction has transaction_id, date, type, amount, currency). This segmentation allows the system to handle disparate formats from different banks and brokers by mapping them to these standardized segments, reducing the need for complex model changes when tax rules or data sources change.
Solution Approach 2:
The patent creates a universal data model that can handle multiple types of financial data (checking accounts, investments, tax information) from various sources (banks, brokers, tax authorities) through a single standardized schema. The holding object universally represents asset positions across different account types and institutions, while the event object universally captures tax-relevant occurrences regardless of source format, eliminating the need for source-specific processing models.
2Ease of operation
If spreadsheet applications are used to organize financial data, then data can be manually organized, but the process requires endless manual verification of consolidated information
Solution Approach 1:
The patent implements self-service through automated data import and validation. The system automatically imports data from multiple sources using standardized schemas, validates consistency against defined rules (e.g., ensuring holding quantities match transaction history), and generates tax reports without requiring manual verification. The computer automatically reconciles data from different sources and identifies inconsistencies, eliminating the endless manual verification process while maintaining ease of operation through automated workflows.
3Adaptability or versatility
If existing financial management applications are used, then basic account management is supported, but they lack functionality for comprehensive investment management and cross-institutional analysis
Solution Approach 1:
The patent merges data from multiple financial institutions and account types into a unified consolidated view. The holding object combines positions from different brokers and banks into a single representation, the transaction object aggregates transactions across all accounts, and the event object consolidates tax-relevant events from multiple sources. This merging enables comprehensive investment management and cross-institutional analysis by presenting all financial data in a unified structure that supports holistic analysis.
Data Source
AI summary
A computerized method for managing data performed in a computer system. The data is stored in a data base including flat lines. Each of the flat lines includes values of the data and tags associated with the values forming tag-value pairs. The flat lines are scanned and an object of a class is created. The class specifies a subset including one or more tags selected from the tags of the flat lines. The flat line points to the object if a portion of the tag-value pairs of the flat line includes all the tags of the subset. When the flat line contains multiple alternative ways, through the subset(s) of tags or through different tag-value pairs, of pointing to the object of the class, then the object as individually identified by the alternative ways is taken to be the same object.