A variation of the genetic algorithm of Holland to support analysis of balance sheet and Income Statement for the Fiscal Year

Accounting is a science that, by studying the financial statements, search to provide information of great importance for decision-making, becoming a crucial tool for the managers of an organization. One of the existing difficulties is in the transparency and understanding of accounting data by managers. The studies in this area show the use of subjectivity on the part of financial analysts while in analysis of financial statements. This is due to the fact that the analysis involves deterministic and nondeterministic factors, such as influence of the branch of business, the company´s operating cycle, seasons, political influence, etc. Therefore, this article proposes the creation of a evolutionary application to be used as a tool to support the analysis of accounting indicators, providing a more accurate view of the result by reducing the subjectivity inherent to the analyst. The application of this tool used data extracted from the Balance Sheets (BS) and Income Statement for the Fiscal Year (SFY) of publicly traded corporations Arcelor Mittal Brazil S/A and Romi Industries S.A. for analysis of indicators.