FNT-5001

Articles

• This article provides a comprehensive exploration of how AI technologies are transforming financial decision-making processes, highlighting both the opportunities and ethical challenges that arise. It delves into real-world applications of AI in finance, such as fraud detection, risk assessment, and personalized banking services, while addressing critical concerns like data privacy, algorithmic bias, and the need for robust ethical frameworks. The authors advocate for a multidisciplinary approach, emphasizing the importance of collaboration among technologists, ethicists, policymakers, and end-users to ensure that AI is developed and deployed in a manner that aligns with societal values and ethical principles. This article is particularly valuable for professionals, researchers, and policymakers who are navigating the complexities of AI integration in finance and seeking to understand its broader implications on market dynamics, regulatory standards, and consumer behavior.

• In this article, the authors provide a comprehensive framework that bridges the gap between academia and the FinTech industry's workforce needs, offering insights into how universities can develop curricula that equip graduates with the necessary skills and knowledge. By exploring the largest FinTech cluster—digital payments—the article highlights the critical areas of competency and provides a roadmap for educational institutions to prepare students for successful careers in this dynamic field. Reading this article is crucial for educators, policymakers, and industry professionals aiming to foster talent that meets the current and future demands of the FinTech industry.

• This article is essential reading for anyone interested in the intersection of FinTech and artificial intelligence (AI), particularly in the area of fraud detection. It offers a comprehensive analysis of how advanced AI algorithms, such as deep learning and machine learning, are revolutionizing the way financial institutions identify and prevent fraudulent activities. By examining real-time processing capabilities, automation, and cost-saving benefits, the article provides practical insights into the operational efficiency gained through AI integration. Additionally, it addresses critical challenges, including data privacy, algorithmic bias, and the need for continuous learning, making it a valuable resource for FinTech professionals, researchers, and policymakers committed to enhancing security in digital financial services.

• This article explores how AI-integrated neobanks are revolutionizing the banking industry by enhancing customer satisfaction, trust, and loyalty. Through a mixed-methods study involving 178 individuals, the research highlights the significant impact of AI in delivering personalized banking services, improving fraud detection, and offering efficient customer support. The study emphasizes the competitive advantage that neobanks hold over traditional banks due to their agile, technology-driven operations. It also addresses concerns about data privacy and the need for transparency in AI usage. The article concludes with practical recommendations for traditional banks to adopt AI technologies and strategies to remain competitive in the evolving financial landscape.

• This article provides a comprehensive overview of the evolution and impact of blockchain on various financial sectors, highlighting its potential to create more secure, efficient, and accessible banking systems. The article discusses the challenges and opportunities that arise from integrating blockchain into FinTech, such as the creation of decentralized finance (DeFi), the rise of cryptocurrencies, and the development of smart contracts and non-fungible tokens (NFTs). By exploring these cutting-edge technologies, the article offers valuable insights into the future of finance, making it a crucial resource for professionals and academics alike who want to stay ahead in the rapidly evolving FinTech landscape.