Abstract
Abstract: This study analyzes the level of compliance with corporate governance practices related to risk management and financial performance, using Machine Learning techniques in Chilean companies. The methodology used covers the phases of the knowledge discovery process in a database. As a result, models based on Unsupervised and Supervised Learning were obtained, which allowed characterizing and then predicting with a high level of accuracy, the degree of compliance with practices. Also, a grouping of companies with different characteristics in terms of the level of compliance and financial performance is determined.
Key words: Data Science, Companies, Risk Management, Machine Learning