Regulating Bank Liability in Artificial Intelligence-Based Credit Decision-Making in Indonesia

Figure Ilustration AI

FORMOSA NEWS - Jakarta - Indonesian Banks face Legal Uncertainty over Automated Credit Approvals, Legal Expert Affandi Warns. Indonesian commercial banks are increasingly deploying artificial intelligence (AI) to automate credit decision-making, yet the country lacks specific legal provisions to address bank liability when algorithms make mistakes. Legal scholar Affandi from AMR Law Firm (Konsultan Hukum AMR) published a normative legal study in 2026 examining how Indonesian banking regulations manage automated credit scoring risks. The study highlights that while AI models accelerate loan processing and reduce human error, they operate without explicit statutory safeguards regarding algorithmic accountability. This regulatory gap creates legal uncertainty for financial institutions and borrowers when automated systems deny credit or miscalculate risk.

The Technological Shift in Indonesian Banking

The rapid digital transformation of Indonesia’s financial sector has led banks to adopt automated credit scoring tools. Encouraged by regulatory frameworks like Law No. 4 of 2023 on Financial Sector Development and Strengthening and Law No. 27 of 2022 on Personal Data Protection, financial institutions rely heavily on behavioral data and machine learning to analyze creditworthiness. However, international organizations like the Bank for International Settlements and the European Banking Authority warn that complex algorithms create model risks, potential data bias, and operational vulnerabilities. Unlike traditional banking, where human officers make and explain credit decisions, AI-driven credit scoring often functions as an opaque "black box" system.

How the Study Analyzed Indonesian Financial Law
To evaluate liability structures, Affandi conducted a normative legal study using statutory and conceptual approaches. The research evaluated primary legal materials, including:

• Law No. 10 of 1998 (Banking Law): Establishes mandatory prudential principles and risk management obligations for commercial banks.
  
• Financial Services Authority Regulations: Examined POJK No. 11/POJK.03/2022 on Information Technology Implementation and POJK No. 22/POJK.03/2023 on Consumer Protection.
  
• Data and Transaction Statutes: Assessed Law No. 27 of 2022 (Personal Data Protection) and Electronic Information and Transactions legislation.
  
• Global Regulatory Benchmarks: Analyzed the European Union Artificial Intelligence Act (2024) and OECD AI Policy Framework for comparative insight.
  

Key Findings on Bank Liability and Legal Gaps

The analysis demonstrates that under current Indonesian law, legal liability remains fully with the banking institution. Indonesian law treats artificial intelligence strictly as an internal operational tool rather than an independent legal entity.

• No Liability Shift: Indonesian law contains no mechanism to transfer legal responsibility from banks to third-party AI developers or software vendors. Banks remain solely accountable for errors, biases, or wrong credit decisions.
  
• Regulatory Fragmenting: Existing laws mandate general prudence and IT risk management, but do not explicitly cover algorithmic credit scoring, decision explainability, or automated bias.
  
• Opacity and Lack of Audits: Indonesian banks frequently deploy predictive AI models without providing transparent explanations to rejected applicants. Furthermore, standard audit mechanisms for AI models are currently lacking across the domestic industry.
  
• Global Divergence: While international frameworks like the European Union AI Act explicitly classify credit scoring as a high-risk application requiring strict human oversight, Indonesian regulations rely on broader, non-specific IT rules.
  

Real-World Impact and Industry Implications

The study’s findings directly affect banking regulators, financial technology developers, commercial banks, and loan applicants. For policymakers at the Financial Services Authority (OJK), the research provides a clear roadmap to create sector-specific rules governing AI transparency, human oversight, and mandatory algorithm audits. For commercial banks, establishing robust AI governance mitigates reputational damage and legal liability caused by hidden algorithmic bias. Clear regulatory frameworks ensure that Indonesian consumers gain equitable access to credit without losing their right to understand automated financial decisions.

Author Profile

Affandi, S.H., is a legal consultant at Konsultan Hukum AMR in Indonesia. He holds a Bachelor of Laws (Sarjana Hukum) degree and specializes in banking law, artificial intelligence governance, information technology regulation, and financial sector liability.

Source
Affandi. Regulating Bank Liability in Artificial Intelligence-Based Credit Decision-Making in Indonesia. International Journal of Law Analytics (IJLA). Vol. 4, No. 3, Hal. 491-502
DOI : https://doi.org/10.59890/ijla.v4i3.286
URL : https://journal.multitechpublisher.com/index.php/ijla/index