Extracting Value from Financial Documents

Most financial organizations today have massive databases of information and little to no efficient way of finding and using the information they need. According to Oracle, only 20% of all generated data is structured data, formatted to be easily understood by machines. The rest is locked away in emails, journals, notes, audio, video, images, analog data, and more.

Natural language processing (NLP) allows machines to use and understand language in similar ways as humans, utilizing written or spoken documents to process information.

Read this use case to learn how to make use of these capabilities to unlock a vast wealth of valuable information in your organization.

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