The Human Factor in Intelligent Banking: Merging Behavioral Finance with Artificial Intelligence

Abstract

Artificial Intelligence (AI) has quickly penetrated the banking and financial services industry and transformed the decision-making process and risk assessment, as well as customer interaction. Despite the fact that the systems created on the basis of AI may become more efficient, more accurate, and predictable, financial outcomes are mostly based on human behavior, the cognitive prejudices, and the emotional responses. This paper discusses the necessity of convergence of behavioural finance and artificial intelligence in intelligent banking systems with the historical existence of human aspect in the technology-oriented financial systems. The paper deals with the interplay of psychological biases such as overconfidence, loss avoidance, herding and perception of trust and AI-enhanced financial applications to change investment decisions, credit decisions and strategy banking. Taking a conceptual and analytical research methodology, the paper will combine the information on behavioral finance theory, human-computer interactive, and financial technology to assess the efficiency of human-AI cooperation in banking activities. There is a specific focus on the questions of trust in the algorithmic systems, transparency, explainability of AI models, and the balance between automation and human judgment. The results are that, although AI can increase the precision and speed of the analytical process, over-reliance on automated systems without behavioral controls can increase systemic risks and decrease the accountability of decision-making. On the other hand, incorporating behavioral knowledge in the design and governance systems of AI enhance the quality of decisions, customer trust, and organizational flexibility. The research reaches the conclusion that intelligent banking systems are most effective in case technological competencies are complemented with the human intuition, moral thinking, and contextual knowledge. This study proposes a hybrid decision-making model and, therefore, it can be seen as contributing to the emerging discussion on responsible AI implementation in the finance industry and has strategic implications on how banks can build a sustainable innovation, better risk management, and customer confidence in the digital age.