– Case Study –
Data Extraction for Mergers & Acquisitions Analytics
Leading financial intelligence company requires automation to provide hourly updates on deals
A leading financial intelligence company offers a comprehensive database of information on M&A, IPO, private equity, and venture capital. They collect structured and unstructured data comprised of 84 fields of interest within news items from 5 sources. Because manually processing the unstructured data is both resource- and time-intensive, they sought an elegant solution to automate this process.
Innodata’s Data Transformation API provides seamless access to a machine learning model trained by in-house subject matter experts that facilitates an automated approach to extracting and structuring relevant information. To ensure speed, quality, and agility this project was set up in two phases. Phase 1: Develop & train 10-20 data points ML model with 4,000+ deal records. Phase 2: Offer continuous training and automation for 500+ deal records per day.
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