Jul 2026· Global Leadership Organizational Research in Management· Vol 4, pp. 41-68· 0 citations· 44 references
TL;DR
This study recommends strengthening AI governance based on the principles of privacy by design, data minimization, and accountability, supported by the harmonization of national regulations with international standards, by examining regulatory frameworks, data governance, and information security.
Abstract
The use of Artificial Intelligence (AI) in the banking sector enhances operational efficiency, the accuracy of decision-making, and the quality of customer services. However, AI’s reliance on large-scale data processing creates risks to personal data protection and privacy. This study analyses policies governing the implementation of AI in the banking sector by examining regulatory frameworks, data governance, and information security. It employs a qualitative method with a juridical-normative approach through an analysis of laws and regulations, financial-sector policies, and AI implementation practices in banking. The findings reveal a gap between the existing legal framework and its implementation. Although Indonesia has enacted the Personal Data Protection Law and sectoral regulations issued by the Financial Services Authority and Bank Indonesia, transparency, accountability, and AI risk controls have not been adequately implemented. The primary risks include excessive data collection, the use of data beyond its original purpose, algorithmic bias, and violations of data subjects’ rights in automated decision-making systems. Limited human resource capabilities and weak AI governance further increase legal and reputational risks for banking institutions. This study recommends strengthening AI governance based on the principles of privacy by design, data minimization, and accountability, supported by the harmonization of national regulations with international standards. The implementation of AI in the banking sector must balance technological efficiency with the protection of customers’ privacy rights.
It is concluded that strengthening legal policies, harmonizing sectoral regulations, and developing AI-specific governance principles are essential to ensure effective personal data protection while supporting responsible technological innovation in Indonesia.
Muhammad Farhan Abdullah· Jurnal Hukum, Administrasi P...· 0 citations
A context-adapted ethical AI governance model for the Republic of Armenia is proposed, which concludes that Armenia can leverage U.S. and global best practices to develop a transparent, accountable, and citizen-centered AI ecosystem.
Harutyun Aleksanyan· Journal of US-China Public A...· 0 citations
The study demonstrates that AI is gradually being integrated into key public finance functions, including government auditing, financial monitoring, transaction analysis, budget data management, and risk forecasting, and substantiates the feasibility of developing a hybrid AI governance model combining innovation capac...
This paper explores the implications arising out of the growing involvement of artificial intelligence as part of tax administration strategies and identifies several ways forward to deal with some of the resulting complexities.
Jaya Priya S and Dr. Sreeja BG· International Journal of Adv...· 0 citations
This paper proposes a practical, audit-ready approach to governing data risks in the AI era, and introduces the concept of critical data elements (CDEs): data elements whose inaccuracy, unavailability, or misuse can produce material regulatory, financial, or customer-facing impact.
Xin-Fa Tu· Journal of financial complia...· 0 citations
It is recommended that preparers and auditors of bank financial statements leverage AI's error-detection capabilities, irrespective of error size, to improve the accuracy and reliability of financial statements in the banking sector.
Ali H. N. BniLam· International journal of bus...· 0 citations
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