Sample Case Study

Automated Financial Data Identification and Extraction


Partner: A provider of data entry and aggregation solutions for the private equity market, that performs a thorough review and manual entry of all data points and documents including Statement of Investments, Partners Capital Statements, Capital Calls, and Distributions.

This data is difficult for analysts to capture and organize compared to public markets, as data is coming from private sources with bespoke formats and no central regulators. Manual entry and turn-around times were very long and subject to persistent quality issues due to human error.

Uneven and skewed reporting timeframes led to highly volatile periods of activity and volume, making managing operations within cost and timelines very difficult.


Automated document retrieval system from private web portals, email inboxes, and File Transfer Protocols (FTPs).

Applied intelligent table parsing solutions to find, extract, and parse the relevant data tables within the documents.

Built customized data standardization, formulas, dates, entity mapping, automated QA and data delivery to conform to necessary standards.

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Document Automation

End-to-end automation of over 90% of documents, despite irregular and non-standard formats.

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Turn Around Time

Turn around times reduced to less than 24 hours, including all human-in-the-loop steps.

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Team Size Reduction

Team size reduced by 75% to only handle exceptions from automated alerts and QA.

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Eliminated Errors

Typos and data entry errors reduced by over 90% after implementing automation.

Service Highlights

Tools and techniques for extracting and organizing data from all types of document varieties.

Incorporates a robust and tested generic extraction technology with client-specific, custom logic to provide a truly end-to-end automated solution.

Ability to handle OCR, watermarks, automated page rotation, multiple page table continuity, missing and multi-layered headers, text wrapped onto multiple rows, inconsistent structures, irrelevant text, contextual table values such as dates, units and currencies, and more.

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