FINANCIAL RATIO ANALYSIS IN CONSTRUCTION INDUSTRY: AN INVESTIGATION USING MACHINE LEARNING

Abstract

Financial Ratio Analysis is considered one of the most fundamental ways of evaluating performance in companies. Analysis of major financial ratios of a company can help decision-makers take early business decisions/actions that could prevent, or at least alleviate, the potential hardships in the future. This paper reviews the literature and shows that various financial models have been developed in the past to evaluate an organization’s financial performance. The paper further proposes to upgrade and extend the resources used for financial performance evaluation through employing advanced artificial intelligence (AI) techniques, with application onto Egyptian construction companies. Research methodology included the gathering of a large number of financial reports/data items from relevant companies. Six major financial ratios were determined over a number of years, based on the consolidated financial accounts and income statements. These ratios include Current Ratio, Quick Ratio, Return on Equity, and others. The use of Machine Learning (ML) techniques is then investigated to analyze those ratios and to develop a financial performance evaluation model. K-means, as an un-supervised ML technique, was utilized to cluster the collected data set into three major groups. Each group has its own unique financial characteristics. Finally, future study measures are discussed where case studies will be used to verify and explain the findings.