AI in the Financial Sector: The Line between Innovation, Regulation and Ethical Responsibility

This study examines the applications, benefits, challenges, and ethical considerations of artificial intelligence (AI) in the banking and finance sectors. It reviews current AI regulation and governance frameworks to provide insights for stakeholders navigating AI integration. A descriptive analysis based on a literature review of recent research is conducted, exploring AI applications, benefits, challenges, regulations, and relevant theories. This study identifies key trends and suggests future research directions. The major findings include an overview of AI applications, benefits, challenges, and ethical issues in the banking and finance industries. Recommendations are provided to address these challenges and ethical issues, along with examples of existing regulations and strategies for implementing AI governance frameworks within organizations. This paper highlights innovation, regulation, and ethical issues in relation to AI within the banking and finance sectors. Analyzes the previous literature, and suggests strategies for AI governance framework implementation and future research directions. Innovation in the applications of AI integrates with fintech, such as preventing financial crimes, credit risk assessment, customer service, and investment management. These applications improve decision making and enhance the customer experience, particularly in banks. Existing AI regulations and guidelines include those from Hong Kong SAR, the United States, China, the United Kingdom, the European Union, and Singapore. Challenges include data privacy and security, bias and fairness, accountability and transparency, and the skill gap. Therefore, implementing an AI governance framework requires rules and guidelines to address these issues. This paper makes recommendations for policymakers and suggests practical implications in reference to the ASEAN guidelines for AI development at the national and regional levels. Future research directions, a combination of extended UTAUT, change theory, and institutional theory, as well as the critical success factor, can fill the theoretical gap through mixed-method research. In terms of the population gap can be addressed by research undertaken in a nation where fintech services are projected to be less accepted, such as a developing or Islamic country. In summary, this study presents a novel approach using descriptive analysis, offering four main contributions that make this research novel: (1) the applications of AI in the banking and finance industries, (2) the benefits and challenges of AI adoption in these industries, (3) the current AI regulations and governance, and (4) the types of theories relevant for further research. The research findings are expected to contribute to policy and offer practical implications for fintech development in a country.