Unlocking the Potential of Predictive Analytics in Financial Decision-Making

Abstract

Systems for decision-making assistance are gradually using analytical and computational methods to aid in management as well as decisions regarding strategy. In order to use these kinds of technologies to reliably predict economic information, researchers need to understand how to use them. Consequently, this chapter presents a method-based literature assessment with a focus on the subject of predictive analytics. The study covers the time series simulations, association, regression analysis, grouping, and categorization in great detail. It introduces machine learning into the realm of mathematical explanatory modeling. The approaches examined enable future prediction through the analysis of longitudinal and financial time series data collected, preserved, and handled in computer systems. The outcomes of these models aid in improving outcomes for risk administration specialists and financial executives. This review unifies several financial forecast analytic methodologies into a single domain.