Case Study: a leading financial intelligence company achieves hourly deal updates with Innodata's AI-powered data extraction

a leading financial intelligence company achieves 90% accuracy in 12 weeks with Innodata

A leading financial intelligence company required an automated solution to process unstructured data from news items for its M&A, IPO, private equity, and venture capital database. Manually extracting 84 fields of interest was too resource- and time-intensive. They partnered with Innodata to develop a machine learning solution to automate this process.

Innodata built a proprietary machine learning model, trained by subject matter experts, to automate the extraction of over 20 relevant entities. The solution, deployed in two phases, achieved 90% accuracy within 12 weeks and now processes over 500 deal records daily. This allowed the customer to provide hourly updates on deals, significantly improving turnaround time, reducing costs, and enhancing the scalability of their world-class financial product.