Managing emotions and algorithms: the delicate equilibrium between artificial intelligence and behavioral finance.

Abstract

Abstract

The paper takes a novel tack by suggesting artificial intelligence (AI) as a way to lessen behavioral biases in the process of making financial decisions. The paper explores how AI might assist avoid behavioral biases among financial planners and provide more effective investment recommendations, based on theoretical research that identifies these flaws. The expanding efficacy of AI is examined in order to overcome confirmation and hindsight biases, particularly via supervised and unsupervised learning. By developing a conceptual framework, outlining potential outcomes, and theoretically examining the relationships between behavioral finance and AI, the technique takes a theoretical approach. The theoretical technique highlights the necessity for conceptual exploration in the developing area of artificial intelligence in finance, which supports this approach even if it has limits due to the lack of empirical evidence.

Keywords: Confirmation bias; Artificial intelligence; Behavioral finance; Investment recommendations; Financial decisions.