AI and Hidden Riba: The Ethical Dilemma of Targeted Marketing in Islamic Finance

Abstrak

The rapid growth of artificial intelligence (AI) and big data has reshaped digital marketing, including in the Islamic financial industry, which increasingly relies on algorithmic personalization to reach customers. While AI-driven targeted marketing offers efficiency and precision, it may harbor forms of hidden riba that remain underexplored in Islamic marketing scholarship, particularly when algorithms encourage debt-based consumption, exploit information asymmetry, or obscure elements of gharar and maysir. This study therefore aims to conceptualize "algorithmic hidden riba" as a new category of ethical risk and to propose a preliminary ethical safeguard framework for Islamic financial institutions. Using a qualitative approach based on library research and conceptual analysis, it draws on the literature on fiqh al-mu'amalat and maqasid al-shariah, scholarship on AI ethics and digital marketing, and relevant fatwas, analyzed descriptively and interpretively. The conceptual analysis shows that profiling, behavioral prediction, and automated offer delivery mechanisms intersect with the prohibitions of riba, gharar, and maysir. Algorithmic hidden riba emerges as a distinct risk that is procedural, dynamic, and collective-aggregate in nature, conflicting primarily with hifz al-mal (protection of wealth) and 'adl (justice). These findings suggest that formal contractual compliance is insufficient to ensure substantive Shariah compliance in the era of AI-driven marketing. The study accordingly proposes five adaptive ethical safeguard principles for Islamic financial institutions: algorithmic transparency, Shariah audits of AI systems, restrictions on debt-based profiling, data protection and consent, and mechanisms for objection and accountability. As a conceptual framework, it requires further empirical testing across Islamic financial institutions and customer contexts.