Title Applied machine learning for spreading financial statements / Data Science Salon

Published [Austin, Texas] : Data Science Salon, 2020

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Description 1 online resource (1 streaming video file (22 min., 18 sec.)) Summary "Presented by Moody Hadi, Group Manager, Financial Engineering at S & P Global Market Intelligence. Counterparty financial statements, particularly for small and medium enterprises can be difficult to handle. Financial analysts need to be able to distill out relevant line items in order to calculate their credit exposure to a counterparty for lending purposes. The solution solves a labor intensive, expert driven inefficient process and frees up the analysts to focus on their high value add operations. This involves combining Optical Character Recognition using pre-trained language neural networks, with context sensitive semantic matching. We will go over the developed ML pipleline and architecture."--Resource description page Notes Title from resource description page (Safari, viewed November 3, 2020) Place of publication from title screen Performer Presenter, Moody Hadi Subject Machine learning. Artificial intelligence -- Data processing. Neural networks (Computer science) Financial statements. Bank loans -- Mathematical models Neural Networks, Computer Artificial intelligence -- Data processing. Bank loans -- Mathematical models. Financial statements. Machine learning. Neural networks (Computer science) Form Streaming video Author Hadi, Moody, on-screen presenter Data Science Salon, publisher

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