Abstract: Digital banking fraud poses a threat to the global economy and fintech applications. Sustainable models are essential to address this issue and minimize its economic impact. Hybrid methods have been developed to assess strategies for preventing digital banking fraud, aiding global stakeholders in making well-informed judgments. However, many of these models concentrate on the numerical features of digital banking ratios while overlooking crucial financial fraud protection qualities. This paper introduces a computational method for discovering and measuring the influence of digital banking fraud prevention strategies on sustainable fraud prevention. This innovative approach combines intuitionistic fuzzy set theory and the analytical network process for decision-making. Initially, an intuitionistic fuzzy expert system prioritizes crucial indices based on the preferences of financial decision-makers. This technique is then compared to alternative decision-making models across multiple variables. Empirical data demonstrate the superiority of the intuitionistic fuzzy-based decision-making system, outperforming other models and facilitating the recognition of financial statement fraud in global banking networks. Consequently, it offers a sustainable fintech solution. The findings of this study are pertinent to fintech scholars and practitioners engaged in the global battle against digital banking fraud.

Bandar Ali M. Al-Rami Al-Ghamdi, “Selection of a Trustworthy Technique for Fraud Prevention in the Digital Banking Sector” International Journal of Advanced Computer Science and Applications(IJACSA), 14(11), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0141124

@article{Al-Ghamdi2023,
title = {Selection of a Trustworthy Technique for Fraud Prevention in the Digital Banking Sector},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0141124},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0141124},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {11},
author = {Bandar Ali M. Al-Rami Al-Ghamdi}
}