Applied Machine Learning for Spreading Financial Statements

Video description

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.

Table of contents

  1. Applied Machine Learning for Spreading Financial Statements 00:22:18

Product information

  • Title: Applied Machine Learning for Spreading Financial Statements
  • Author(s): Data Science Salon
  • Release date: March 2020
  • Publisher(s): Data Science Salon
  • ISBN: None