{"id":11247,"date":"2021-04-30T16:42:07","date_gmt":"2021-04-30T15:42:07","guid":{"rendered":"https:\/\/www.imprima.com\/?post_type=whitepapers&p=8721"},"modified":"2022-06-13T09:24:13","modified_gmt":"2022-06-13T09:24:13","slug":"finding-information-in-documents","status":"publish","type":"whitepapers","link":"https:\/\/www.imprima.com\/whitepapers\/finding-information-in-documents","title":{"rendered":"Finding Information: What Does it Cost, What Does it Take?"},"content":{"rendered":"\n

According to McKinsey<\/strong><\/a>, employees spend 1.8 hours every day \u2013 9.3 hours per week, on average \u2013 searching and gathering information\u2019.<\/p>\n\n\n\n

This is even more true in M&A Due Diligence<\/strong><\/a> where one of the main objectives is to find information, which can be challenging. The time pressure is especially high during the due diligence stage which increases the likelihood of missing certain information.<\/p>\n\n\n\n

That is where Machine Learning (ML) comes in. This whitepaper explains why NLP approaches to unstructured data (documents) are so effective.<\/p>\n\n\n\n

Points of discussion include:<\/p>\n\n\n\n