The Application of Predictive Learning in Islamic Finance: A Review

Abstract

Incorporation of Predictive Learning in Islamic Finance is catching up as Islamic Finance has the potential and scope to improve decision making and risk management capabilities. This involves the application of Predictive Learning which is a field in Machine Learning that focuses on harnessing historical information to provide forecasts of the future changes ups and downside of the Islamic financial systems. Thus, this study aims to investigate the use of predictive learning in enhancing the Islamic finance and especially focuses on asset management, risk management, and ensuring compliance with Shariah principles. The paper reviews the role of such predictive models to forecast the behaviour of the market, enhance the portfolio returns and the risk of violating any of the Islamic finance regulations such as riba (interest) and gharar (in excess of uncertainties). The main idea is to explore the use of Predictive Learning Algorithm within Islamic Finance through relevant case studies and current research, the main advantage, and therefore present the advantages, disadvantages, and ethical implications. According to the results, it is found that the enhancement of the Islamic finance practices can be promising with the use of the predictive learning technology, however, more studies are needed to deal with data integrity, model explainability, and compatibility with Islamic ethical principles. In the end, this article that adds to the existing literature on technology and Islamic finance, engenders prospects for technology enhancement in Islamic finance.