Artificial intelligence (AI) applications in the banking and finance sector have seen significant development and implementation in recent years, offering innovative solutions that enhance both back-end processes and customer experiences. These AI-driven solutions improve decision-making capabilities, providing valuable competitive advantages in a dynamic industry. Artificial Intelligence has undoubtedly transformed the banking industry, a vast and multifaceted environment. This paper presents a comprehensive literature analysis of numerous AI applications in banking, detailing their advantages, drawbacks, and challenges. The methodology employed in this research is a systematic literature review, in which a domain-based approach is followed. The study analyses research papers from four major electronic databases: Emerald Insight, Science Direct, Google Scholar, and ProQuest, covering the period from 2010 to 2023. To maintain consistency with previous systematic reviews, the study excluded editorials, non-referred articles, and proceedings. The researcher began with broad search terms such as “Artificial Intelligence” and “bank,” subsequently refining the search by examining titles, keywords, and abstracts to identify relevant articles. The PRISMA model guided the search strategy. This research explores various dimensions of AI applications in banking services. Key areas of focus include credit score checking, risk management, customer services, cash flow risk assessment, and the detection of fraudulent activities and fraudulent websites. Technologies like chatbots, and mobile banking have significantly enhanced customer service and experience. The review is structured into several sub-themes: AI in banking, applications of AI in banking, benefits of AI in banking, challenges of AI in banking, AI and customer services, applications of AI in risk management, and chatbots in the banking system. AI has transformed traditional banking operations, making them more efficient and customer-centric. Credit scoring models powered by AI can analyses vast amounts of data more accurately and swiftly than traditional methods, leading to more reliable credit assessments. In risk management, AI algorithms can predict potential risks and assess cash flow with higher precision, enabling banks to make informed decisions and mitigate potential financial threats. AI’s role in detecting fraudulent activities is particularly notable, as machine learning models can identify suspicious patterns and behaviors that might go unnoticed by human analysts. Customer service in banking has also been revolutionized by AI. Chatbots and virtual assistants provide immediate responses to customer queries, significantly reducing wait times and enhancing user satisfaction. These AI-driven tools can handle a wide range of customer interactions, from simple queries to complex problem resolution, thereby freeing up human agents to focus on more intricate tasks. This paper also provides directions for future research, emphasizing the need to address the ethical and regulatory challenges associated with AI in banking. Additionally, further studies are recommended to explore the long-term impacts of AI on employment within the banking sector and to develop frameworks for the equitable and responsible use of AI technologies. In conclusion, AI has undeniably improved the banking experience for millions of customers and employees, offering enhanced efficiency, security, and personalized services. As AI continues to evolve, its applications in banking are expected to expand, further transforming the industry.