INVESTIGATING THE ETHICAL TRADE-OFFS IN HYPERPERSONALIZED FINANCIAL PRODUCT RECOMMENDATIONS USING AI MODELS
Keywords:
Hyperpersonalization, AI Ethics, Financial Services, Algorithmic Bias, Data Privacy, Fairness, ConsentSynopsis
The growing integration of artificial intelligence (AI) into financial services has led to the emergence of hyperpersonalized recommendation systems. These systems tailor products such as credit cards, insurance plans, and investment portfolios to individual user profiles. While this enhances customer experience and operational efficiency, it introduces significant ethical dilemmas including algorithmic bias, surveillance, manipulation, and lack of informed consent. This paper investigates the ethical implications of AI-powered hyperpersonalization in financial contexts, drawing from scholarly literature and industry data. It presents analytical visualizations and outlines emerging frameworks to balance innovation with ethical responsibility.
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