Applying neural networks to the extraction of knowledge from accounting reports: A classification study

Abstract

This study develops a new approach to the problem of extracting meaningful information from samples of accounting reports. Neural networks are shown to be capable of building structures similar to financial ratios, which are optimal in the context of the particular problem being dealt with. This approach removes the need for an analyst to search for appropriate ratios before model building can begin.