AI-driven financial advisory and behavioral tax planning: A conceptual framework for intelligent FinTech ecosystems
Keywords:
Artificial Intelligence, Financial Advisory, Behavioral Tax Planning, Robo-Advisors, FinTech, Explainable AI, Investor Behavior, Digital FinanceAbstract
Artificial Intelligence (AI) is rapidly transforming financial advisory and taxation systems through intelligent automation, predictive analytics, and personalized financial decision-making. Simultaneously, behavioral finance has highlighted how cognitive biases and irrational investor behavior influence financial planning and tax-related decisions. Despite growing adoption of AI-enabled financial technologies, limited research has integrated behavioral tax planning with AI-driven financial advisory within a unified conceptual framework. This study explores the opportunities and challenges associated with AI-driven financial advisory and behavioral tax planning in the evolving FinTech ecosystem. The paper adopts a conceptual research design based on secondary literature from the domains of artificial intelligence, behavioral finance, taxation, and digital financial services. The study examines the role of AI in portfolio optimization, behavioral bias reduction, tax planning efficiency, fraud detection, and financial inclusion. It further analyzes critical challenges relating to algorithmic bias, explainability, cybersecurity, ethical governance, privacy concerns, and regulatory uncertainty. Drawing upon Behavioral Finance Theory, Technology Acceptance Model (TAM), and Explainable Artificial Intelligence (XAI), the study proposes a conceptual framework explaining the relationship between AI capabilities, investor behavior, trust, and financial decision quality. The paper contributes to the emerging literature on intelligent financial ecosystems by integrating technological, behavioral, and governance perspectives.
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