Unpacking the Organizational Factors Influencing Predictive Analytics Adoption for FX Exposure Management in SMEs: A Non-Empirical Appraisal

Abstract

Predominant enterprises use predictive analytics as their main instrument to control monetary perils starting from foreign exchange (FX) exposure. Small and medium-sized enterprises (SMEs) encounter substantial obstacles when it comes to implementing data-driven approaches although large corporations have already accepted this methodology. The evaluation analyzes how organizational aspects contribute to the implementation of predictive analytics for FX exposure management within SMEs along with major adoption hindrances and assistance elements. The potential of predictive analytics for risk management in SMEs depends strongly on factors which include their technological capabilities and financial resources and data access limitations and workforce expertise alongside regulatory demands. Predictive analytics solutions for SMEs need dedicated development to match their needs while training programs and policy changes will help increase wide-spread implementation. Future studies need to concentrate on building both economical and easy-to-use technology models while investigating the behavioral aspects which determine acceptance rates. SMEs who successfully overcome obstacles in adopting predictive analytics technology will build better financial stability while keeping their market competitiveness strong.