GENERATIVE ARTIFICIAL INTELLIGENCE, THREAT OR CHALLENGE FOR THE MODERN BANKING SYSTEM
GENERATIVE ARTIFICIAL INTELLIGENCE, THREAT OR CHALLENGE FOR THE MODERN BANKING SYSTEM

Summary/Abstract: In recent years, generative artificial intelligence has emerged as one of the most transformative technologies across various industries, reshaping operations, enhancing customer experiences, and driving innovation. The banking sector, a cornerstone of the global economy, stands at a unique crossroads as it navigates the implications of integrating generative artificial intelligence into its processes. The fast progress of generative artificial intelligence presents both unprecedented opportunities and formidable challenges for the modern banking system. The allure of generative artificial intelligence lays in its ability to process vast amounts of data, produce coherent and contextually relevant content, and even simulate complex human interactions - all of which are valuable in refining banking services in an increasingly competitive landscape. This paper explores the dual nature of generative artificial intelligence in the banking sector by evaluating its potential to enhance operational efficiency, improve customer service, and drive financial innovation. It can significantly streamline banking operations and enhance decision-making processes by automating routine tasks, generating personalized banking experiences, and developing advanced predictive models. However, generative artificial intelligence integration into the banking business process also poses significant threats concerning cybersecurity risks, data privacy concerns, and the potential for algorithmic bias, which could undermine trust in financial institutions. Furthermore, it can create deepfakes and misinformation emphasizing the critical need for robust regulatory frameworks and ethical guidelines to safeguard the integrity of banking systems. Nowadays, as banks increasingly rely on advanced algorithms to automate decision-making, generate personalized financial products, and improve customer interactions, they must confront the duality of generative artificial intelligence, as both a powerful enabler and a potential disruptor. To grasp the research goal, the paper will address the following research questions: Is there a difference between traditional and generative artificial intelligence? What is the impact of generative artificial intelligence on the banking sector and financial service business? What are the benefits and disadvantages of generative artificial intelligence applications in the banking processes? What strategy bank executives should apply to successfully embed artificial intelligence in banking? To derive conclusions and achieve the objectives of the research paper, the research questions will be answered with secondary data and by using the deduction method, SWOT analyses as well as descriptive statistics. The paper's results set the stage for further comprehensive analysis on how generative artificial intelligence can both transform and challenge the banking landscape, ultimately advocating for a balanced approach that harnesses its benefits while mitigating financial risks. In conclusion, recommendations are offered for banks’ leaders to implement a successful strategic roadmap for a next-generation artificial intelligence scale-up in the banking sector.

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