Arif Perdana, Saru Arifin, Novi Quadrianto
Algorithm-driven financial systems significantly influence monetary stability and payment transactions. While these systems bring opportunities like automation and predictive analytics, they also raise ethical concerns, particularly biases embedded in historical data. Recognizing the critical role of governance, ethics, legal considerations, and social implications (GELSI), this study introduces a framework tailored for algorithmic systems in financial services, focusing on Indonesia's evolving regulatory environment. Using the Multiple Streams Approach (MSA) as our theoretical lens, we offer a framework that augments existing quantitative methodologies. Our study provides a nuanced, qualitative perspective on algorithmic trust and regulation. We proffer actionable strategies for the Central Bank of Indonesia (BI), emphasizing stringent data governance, system resilience, and cross-sector collaboration. Our findings highlight the critical importance of ethical guidelines and robust governmental policies in mitigating algorithmic risks. We combine theory and practical advice to show how to align problems, policies, and politics to create practical opportunities for algorithmic governance. This study contributes to the evolving discourse on responsible financial technology. Our study recommends a balanced way to manage the challenges of innovation, regulation, and ethics in the age of algorithms. © 2025
Monash University, Indonesia; Universitas Negeri Semarang, Indonesia; University of Sussex, United Kingdom
