Data Governance For Artificial Intelligence Implementation In The Financial Sector: An Indonesian Perspective

The fast-evolving landscape of Artificial Intelligence (AI) is transforming industries worldwide, including Indonesia’s financial sector. While AI presents immense opportunities for innovation and efficiency, it also poses complex challenges in data governance. This paper explores the need for Indonesia to establish a comprehensive and forward-thinking data governance framework tailored to AI implementation in the financial sector. Using a literature review method and drawing on global and local regulatory developments, the paper outlines key principles for AI-related data governance, including transparency, accountability, specificity, enforceability, and adaptability. By reimagining its approach to data governance, Indonesia can mitigate the risks of data misuse, enhance personal data protection, and foster an environment conducive to responsible AI innovation. The research addresses the foregoing issues by offering a conceptual foundation for policymakers, regulators, and financial institutions in Indonesia to develop better rules and practices for managing AI-related data to strengthen Indonesia’s technological sovereignty, particularly in the financial sector. The study finds that Indonesia’s current data governance framework in the financial sector is not yet optimal for supporting AI implementation. Indonesia’s data governance framework requires adjustments in key areas, namely specificity, enforceability, and adaptability, while also promoting stronger cooperation among stakeholders.