XBRL Comparative Reporting System for Financial Benchmarking
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Solution Overview
Problem
Enterprises lack the means to create competitive financial forecasts and identify correlations from large datasets of financial information available from public sources, and there is a lack of software tools to integrate reported financial information of competing enterprises into their financial systems effectively.
Innovation Solution
A comparative reporting system that ingests and processes financial information from multiple sources, using XBRL (eXtensible Business Reporting Language) to extract attributes and metrics, and integrates them with enterprise financial data for analytics, enabling benchmarking and analytics to generate comparisons between the enterprise and competitors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If financial information from multiple public sources is collected and integrated, then the comprehensiveness and accuracy of financial analysis is improved, but the complexity of data processing and integration increases
Solution Approach 1:
The patent employs XBRL (eXtensible Business Reporting Language) as an intermediary standard to bridge multiple public financial data sources. XBRL tags and taxonomies serve as a common language that structures financial information from different sources (SEC EDGAR, exchange filings, company reports) in a standardized format, enabling automated extraction and integration without requiring complex custom parsing logic for each source
Solution Approach 2:
The system implements a universal data integration framework that handles multiple types of financial information (income statements, balance sheets, cash flow statements) from multiple sources through a single standardized process. The XBRL-based architecture provides multi-functional capability to ingest, validate, and normalize diverse financial data formats into a common structure that can be used for various analytical purposes
2Loss of information
If detailed financial data from multiple sources is integrated, then the depth of benchmarking and analytics is improved, but the time and resources required for data processing increase
Solution Approach 1:
The system performs preliminary action by pre-structuring financial data using XBRL tags and taxonomies during the data ingestion phase. Financial statements are pre-validated against XBRL schemas, and key metrics are pre-calculated and tagged during the extraction process. This preliminary processing reduces the computational burden during actual analytical queries, as data is already organized and validated before analysis begins
Solution Approach 2:
The system creates standardized copies of financial data in XBRL format from various source formats (PDF, HTML, XML). Instead of processing the original diverse formats during analysis, the system works with standardized XBRL copies that contain pre-extracted numerical data and contextual information, significantly reducing processing time while maintaining data integrity
3Adaptability or versatility
If financial data from competitors and industry peers is integrated, then the capability for competitive benchmarking is improved, but the difficulty of data integration and normalization increases
Solution Approach 1:
The system applies parameter changes by transforming financial data from various sources into a standardized XBRL parameter structure. Different source formats and accounting methodologies are normalized to common XBRL taxonomies, allowing direct comparison of financial metrics across competitors. The system handles parameter variations in accounting periods, fiscal year endings, and reporting standards through XBRL's contextual definition capabilities
Solution Approach 2:
The patent segments the complex integration task into manageable components: data extraction from individual sources, validation against XBRL schemas, transformation to standardized format, and integration into the benchmarking system. This segmented approach processes each data source independently through standardized stages, reducing the overall integration complexity while enabling comprehensive multi-source benchmarking
Data Source
AI summary
A comparative reporting system provides financial benchmarking and analytics. Integrating public reporting and enterprise software systems, raw financial information from external sources derived from a plurality of reporting sources can be ingested and processed to extract attributes and metrics. The extracted attributes and metrics can be data warehoused together with financial information from the enterprise software system. Analytics can be performed to generate a comparison between the enterprise and the plurality of reporting sources.