A Systematic Review of the Literature on Financial Applications of Predictive Analytics

Abstract

To assist the management and support the strategic decisions, statistical and computational methodologies are being progressively incorporated into decision support systems. To accurately anticipate the financial data, researchers must properly comprehend its utilization. Therefore, a method-based literature evaluation with an emphasis on the predictive analytics field is proposed in this chapter. Regression, clustering, association, and time series models are thoroughly covered in this research. It extends current statistical explanatory modelling into the field of computational modelling. These model results help financial managers and risk management experts get better results. The numerous financial predictive analytic techniques are brought together in this review under one area. This is regarded as a solid foundation since it shows that when more than 40 papers have been identified as eligible, systematic reviews can be employed at the domain level. This search was conducted by the SPAR-4-SLR (scientific procedures and rationales for systematic literature reviews) protocol.