Regulatory Challenges of AI-Driven Credit Scoring in Indonesian Banking: Between Algorithmic Bias and Consumer Protection

Abstract

Artificial Intelligence (AI) based credit scoring systems have rapidly transformed lending practices in Indonesian banking. AI enables automated assessment using non-traditional variables, including digital footprints, e-commerce behavior, and mobile device metadata. While this innovation enhances efficiency and financial inclusion, it also creates significant legal and ethical challenges. Existing regulations, Bank Indonesia regulations, OJK regulations on risk management, and the Personal Data Protection Law have not yet provided a comprehensive and specific framework for algorithmic transparency, fairness, and liability in automated decision-making. This article examines the regulatory gaps in Indonesian laws related to AI-driven credit scoring, evaluates the risks of algorithmic bias, and formulates a normative model for consumer protection. Using a normative juridical method, this paper compares Indonesia’s regulatory landscape with global frameworks such as the EU Artificial Intelligence Act, OECD AI Principles, and U.S. fair lending rules. The study finds that the Indonesian financial regulatory regime lacks clear provisions on explainability, auditability, and accountability for AI decisions. It concludes that regulatory reform is required to mitigate discrimination risks and strengthen legal certainty for consumers and financial institutions.