A finance firm responsible for conducting legal and financial reviews of corporate filings faced significant challenges extracting critical information from complex financial statements. The manual process of reviewing large volumes of structured and unstructured financial data was time-consuming, resource-intensive, and prone to human error.
The firm needed a faster and more reliable way to access, organize, and analyze financial information to support legal reviews, risk assessments, and decision-making.
Infognana implemented its Cognitive Data Extractor (rannsCDE), an AI-powered document processing solution designed to automate the extraction and analysis of financial data from corporate filings.
Using advanced AI models, hybrid table-text parsing, value classification, and document summarization capabilities, rannsCDE automatically extracted key financial information, including revenue figures, expenses, balance sheet data, and supporting footnotes. The solution accurately processed both structured tables and unstructured narrative content, providing legal teams with a complete and organized view of financial records.
This enabled faster access to critical information while reducing the complexity of financial statement reviews.
The implementation delivered 93% field-level AI accuracy and reduced financial review cycles by 80%, significantly improving the efficiency of legal and financial analysis workflows.
By automating the extraction and organization of financial statement data, the finance firm accelerated legal review processes, improved decision-making, and enabled teams to focus on higher-value financial analysis rather than manual document review.
Share this case study
Infognana is an AI solutions and digital services company with 25+ years of expertise in empowering enterprises through intelligent platforms, scalable digital solutions, and innovation-driven growth.
© 2026 – Infognana Solutions. All Rights Reserved.
