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Exploring risk management in smart banking systems through the circular intuitionistic fuzzy Bonferroni means aggregation operator

algorithms-and-analysis-of-algorithms
artificial-intelligence
data-mining-and-machine-learning
security-and-privacy

Abstract

In the rapidly changing world of the intelligent banking system, it emerged as a revolutionary force in the rapidly growing financial technology world. It is more important than ever to manage risk precisely. However, these innovative systems provide clients with a smooth and customized banking experience using modern technologies like blockchain, big data analytics, and artificial intelligence (AI). There is no denying the advantages of intelligent banking. However, customers and the banking sector are exposed to several emerging risks related to it, such as cybersecurity, hacks, and information leakage due to the interconnection of digital platforms. To achieve client authentication, a protective transaction, and better appreciation of new clients, and minimize fraud, it is important to study the risks associated with intelligent banking. This study suggests a multi-criteria group decision-making model (MCGDM) to evaluate risk in innovative banking systems and address the dynamic and complicated issues in the banking industry based on the modern environment of technological growth. Such developments allow recognizing possible risks and trends in large datasets more accurately and efficiently. This paper puts forward the Circular Intuitionistic Fuzzy Bonferroni mean (CIFBM) as a methodology that can be used to assess risks in the innovative banking system. It is an extension of fuzzy logic, and this methodology can effectively handle ambiguity and vague conditions in the actual world. Moreover, some important theorems and properties, such as the idempotency, monotonicity, and boundedness, have guaranteed its efficiency and reliability in most of its applications. After evaluating the effectiveness and credibility of the suggested methodology, it was applied to determine risk within an intelligent banking system that enhances risk determination and offers a secure, efficient, and flexible banking system capable of supporting the needs of the modern financial environment.
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