American Journal of Business and Operations Research AJBOR 2692-2967 2770-0216 10.54216/AJBOR https://www.americaspg.com/journals/show/2303 2018 2018 Faculty of Economics and Administrative Sciences, Adana, Turkey Serkan Yilmaz Kandir Faculty of economics and administrative sciences, Cukurova University, Adana, Turkey Murat Ismet Haseki effective risk management is an indispensable requirement for improving the flow of transactions in dynamic financial markets. To this end, this study presents an applied predictive analytics methodology, that integrate gradient boosting algorithm to model the risk behavior in dynamic markets. This study, based on predictive analytics in monetary and financial systems, faces an urgent need for robust models that can overcome the uncertainties inherent in dynamic markets. Holistic experimentations on public case study of U.S retail data demonstrate the predictive power of the proposed approach of the state-of-the-art techniques across different performance metrics. This in turn highlights the nuanced interaction between variables and delivering intuitions into crucial risk determining factor. 2024 2024 54 61 10.54216/AJBOR.110106 https://www.americaspg.com/articleinfo/1/show/2303