Automated analysis and evaluation of SEC documents

Abstract

This paper presents an intelligent corporate governance analysis and rating system, called AAE System, capable of retrieving SEC required documents of public companies and performing analysis and rating in terms of recommended corporate governance practices. With Machine Learning, local knowledge bases, databases, and semantic networks, the AAE system is able to automatically evaluate the strengths, deficiencies, and risks of a company's corporate governance practices and board of directors based on the documents stored in the SEC EDGAR database[1]. The produced score reduces a complex corporate governance process and related policies into a single number which enables concerned government agencies, investors and legislators to assess the governance characteristics of individual companies.

A Literature Review on Corporate Governance Mechanisms: Past, Present, and Future*

“…The shareholder resolutions cluster around the following seven themes: emission and energy, accountability, product management, politics, board, governance, and regulation. Zheng et al (2014) apply text mining, semantic networks, and ML to assess the extent to which US firms comply with governance practices. They retrieve 8-K, 10-K, and proxy statement information from EDGAR and connect the text to a series of 200 questions from the Corporate Governance Handbook 2005 Developments in Best Practices, Compliance, and Legal Standards.…”

“…Zheng et al (2014) apply text mining, semantic networks, and ML to assess the extent to which US firms comply with governance practices. They retrieve 8‐K, 10‐K, and proxy statement information from EDGAR and connect the text to a series of 200 questions from the Corporate Governance Handbook 2005 Developments in Best Practices , Compliance , and Legal Standards .…”