Open finance holds transformative potential—enabling consumers and businesses to share their financial data securely across providers, and driving competition, innovation, and financial inclusion. As argued in our recent paper, realizing these benefits depends on effective oversight. And while most financial sector authorities (FSAs) in emerging markets are only beginning their open finance journey, it is crucial to start preparing for oversight and supervision now, defining supervisory activities, data returns, tools, and required resources.
Models of effective oversight vary, but technology could play a central role in all of them. This is due to the unique nature of oversight that requires analyzing large volumes of high-frequency, real-time data.
Traditionally, FSAs rely on the analysis of quarterly or monthly reports, which may be adequate when information does not change very quickly or when changes do not have an immediate impact. In open finance, however, a different supervisory posture is needed—one that is better suited to the fast‑moving, interlinked ecosystem. An outage, poorly performing APIs, or slow error resolution within a major ecosystem participant can quickly affect many others, disrupting or deteriorating the quality of the services consumers rely on. If the issues persist, they discourage participation in the ecosystem, reduce the viability of services, and erode public trust. The result—such issues undermine the very policy objectives of open finance, such as inclusion, competition, innovation, and consumer empowerment.
To effectively oversee such a dynamic, interlinked ecosystem, detailed regulatory data needs to be shared in large volumes and at high frequency to give timely intel for early, corrective interventions. Technology is critical as it equips FSAs with the necessary data analytics capabilities.
Technology for prompt corrective interventions
Early, corrective interventions are central to open finance oversight and supervision – particularly in the first years of implementation when customer trust is limited, and contenders are experimenting with novel use cases. To protect customers, open finance ecosystems need to operate at high levels of performance, follow strict data security standards and fraud monitoring and management practices, and ensure a smooth user experience. Early interventions also protect participants against anti-competitive practices, some of which may be difficult to identify without high-frequency data and technology (e.g., slower response times, higher rejection rates, recurring technical issues).
Moreover, instead of relying primarily on formal enforcement actions, which are often slow and resource-intensive, FSAs should focus on understanding the root causes of failure (e.g., weak API resilience, limited API availability) and helping to fix them by engaging with specific participants.
Implementing a tech-driven approach: Brazil & the United Arab Emirates
Brazil’s experience implementing a tech-supported approach illustrates how monitoring of the ecosystem based on high-frequency data allows supervisors to distinguish between temporary growing pains and repeated underperformance or patterns that could signal misconduct or weak controls.
The Central Bank of Brazil (CBB) mandated the country’s open finance implementation body (Associação Open Finance – AOF) to build a monitoring platform. Through the platform, AOF conducts numerous analyses using granular metadata on API calls and handles day-to-day follow-up with participants. It has an automated API Resilience dashboard built on AWS QuickSight that is complemented by other tools developed in-house. The platform produces analytics that feed an overall scoring model that assigns a score from 1 to 10 for each ecosystem participant and to the whole ecosystem, based on regulatory metrics and operational criteria, as shown in the screenshots below.
Beyond API performance monitoring, a Python pipeline (an automated sequence of software steps to manage an AI model) is used to assess aspects such as product monitoring (e.g., integration errors), governance (e.g., data quality), and compliance (e.g., conformance tests with FAPI standards and implementation of Service Level Agreements [SLAs]).
Conclusion
The ability to implement effective open finance oversight and supervision depends on design choices made well before an ecosystem reaches scale. FSAs that do not plan may find themselves with limited options and inadequate oversight capabilities, unable to achieve their goals. Technology plays a critical role, given that effective oversight depends on processing and analyzing large volumes of granular, high-frequency data.
Thus, the key takeaways for FSAs are clear:
- Plan ahead for oversight and supervision to ensure effectiveness and availability of resources, including the right technologies.
- Make robust oversight the foundation of the supervisory model.
- Focus on prompt corrective measures while using enforcement as a credible deterrent.
- Use comprehensive, high-frequency data and leverage technology for their timely analysis that feeds supervisory (and enforcement) decisions.
- Leverage implementation bodies where they exist to support supervision (e.g., by collecting and processing the regulatory data).
For more information about emerging practices in open finance oversight and supervision, read our recent paper, and please share your experience with using technology for open finance oversight and supervision.
This blog was written with contributions from Genaro Lins and Ana Abrão (Open Finance Brasil).
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