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RAGE AI Processes Untagged Data in XBRL Documents

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rfby Angela Guess

A recent release out of the company reports, “RAGE Frameworks, a provider of AI for the Enterprise, today announced the availability of new features and capabilities for its LiveSpread™ Intelligent Machine, a contextual, traceable machine learning solution for the automated ingestion and processing of financial statements and other documents. With this release, LiveSpread™ will process untagged data from XBRL documents, in addition to tagged data, financial statements, bank statements and ITRs received in any form [paper, pdf, picture, excel, etc.] or format.”

The release goes on, “Financial statements are at the heart of numerous business processes ranging from lending, mergers and acquisitions to audits and investments. The significant degree of nonstandard account labels across private and public, domestic and international companies, and natural variation in format (electronic files, spreadsheets, PDFs, and within fax statements) of accounting standards across companies makes the process of gathering, extracting and normalizing financial data in a form amenable for decision making highly complex and cumbersome. XBRL provides a framework for the interchange of financial statements between organizations and systems, but does not address this variability or standardization problem.”

It continues, “RAGE’s LiveSpread™ Intelligent Machine also has the ability to process statements across multiple languages and GAAP conventions, normalizing them to a single desired view. It has been deployed in several leading global financial institutions with higher quality results, reduced costs and faster turnaround times. With this release, LiveSpread™ will now also process all data in XBRL documents, both tagged and untagged.”

Read more at Marketwired.

Photo credit: RAGE Frameworks

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