The use of predictive analytics in finance

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Statistical and computational methods are being increasingly integrated into Decision Support Systems to aid management and help with strategic decisions. Researchers need to fully understand the use of such techniques in order to make predictions when using financial data. This paper therefore presents a method based literature review focused on the predictive analytics domain. The study comprehensively covers classification, regression, clustering, association and time series models. It expands existing explanatory statistical modelling into the realm of computational modelling. The methods explored enable the prediction of the future through the analysis of financial time series and cross-sectional data that is collected, stored and processed in Information Systems. The output of such models allow financial managers and risk oversight professionals to achieve better outcomes. This review brings the various predictive analytic methods in finance together under one domain.
Original languageEnglish
Article numberNovember 2022
Pages (from-to)145-161
Number of pages17
JournalThe Journal of Finance and Data Science
Early online date20 May 2022
Publication statusPublished online - 20 May 2022

Bibliographical note

Publisher Copyright:
© 2022 The Authors


  • Fintech
  • predictive analytics
  • Finance
  • Regtech
  • Risk
  • Statistics
  • Machine learning
  • Decision support systems
  • information systems
  • Predictive analytics
  • Information systems


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