Introduction to Data-Driven Supervision

Introduction to Data-Driven Supervision

Number of replies: 22

Data-driven supervision is imperative to conducting supervisory activities in the twenty-first century. Converging trends show that becoming a data-driven supervisor is now obligatory. These converging trends were clearly articulated by Jo Ann Barefoot in her vision of “Regulation 2.0” a few years back, which continues to be highly relevant.

Barefoot made six broad points:

  1. There is a need for resilience and adaptability in regulatory and supervisory frameworks. Consider COVID-19, which had far-reaching implications for all economic activities, including DFS. These types of exogenous shocks will occur, and supervisors will need to quickly adapt.

  2. Technology is constantly evolving and advancing, and supervisors must keep up. DFS, by its nature, shifts and changes as technology does. It is therefore critical that supervisory authorities increase their technological readiness and modernise their data systems. An example of this is the adoption of cloud computing.

  3. A range of stakeholders recognise and acknowledge that current regulatory and supervisory models are outdated and require urgent improvement, modernisation, and adaptation. Supervisory authorities are compelled to set themselves up to regularly evolve and keep pace with changes in the industry.

  4. Generational turnover is resulting, and will continue to result, in a greater willingness to overhaul established practices that outgoing supervisors may have been reluctant to change.

  5. Generative AI can lower the barriers to adoption with references to data-driven approaches to supervision. With correct modelling and appropriate, responsible use, it can be a powerful tool for supervisors moving towards data-driven supervision.

  6. Globally, there is a shift in political influences and how these converge with technology, AI, and tech users. Supervisory authorities are now, more than ever, working to maintain independence and technical excellence in order to avoid political interference.

In short, DFS is a fast-evolving field that leverages new data types, as well as innovative approaches to analytics and digitally native business models. DFS supervisors need a foundational set of knowledge and tools to keep pace with these evolving changes. These innovations introduce unique risks, necessitating a shift toward data-driven supervision.

Becoming data-driven requires changing how one views data. Supervisory data needs to be of the highest quality, relevant to what is required, and accessible. Only then can supervisors begin to adopt modern Supervisory Technology (SupTech) tools to generate actionable insights.

However, it is not enough for supervisory authorities to simply use more data. The shift to becoming data-driven must be managed appropriately within the organisation.

Often, technology itself is not the main issue or the biggest obstacle; the human element is frequently overlooked. Implementing significant changes in systems, infrastructure, and work processes to support supervisors in becoming technology-savvy and data-driven can feel uncomfortable for people working in these roles. This change must be managed carefully because, without proper management and consideration, these shifts tend to fail in achieving the desired results.

This module will delve deeper into the journey to becoming a data-driven supervisor. It will cover issues such as approaches to supervisory data, how to improve data quality, and how to use technology, including AI-powered SupTech tools. It will also highlight the importance of understanding and mitigating the risks associated with the increasing use of technology for supervisory purposes.

Let’s begin with a video that outlines the steps supervisors can take to become data-driven.

 

 

If you have trouble playing this video, you can access an alternative player here.

Click to view the transcript.

Additional Reading:

To further your understanding of supervisory tools for risk-based supervision, we recommend you read the following:

  1. Cook, N., Alliance for Innovative Regulation, 2024, From Legacy Systems to Cutting Edge Tech: A Financial Regulator’s Odyssey.
  2. Cook, N. and Narayan, S., Alliance for Innovative Regulation, 2025, Beyond Pilots and Sandboxes: Regulatory Innovation through SupTech Case studies and Leading Practices.
  3. CGAP, 2026, Digital Innovation.
  4. Dias, D., CGAP, 2026, CGAP upcoming publication.

Reflection Questions for Discussion

Remember that one of the aims of this course is for you to apply what you learn to your own context. As in Modules 1 and 2, we will continue to provide you with questions for reflection. These questions are specifically designed to get you to reflect on your country and context. 

We encourage you to respond to these questions using the forum functionality, sharing your reflections and insights with your fellow students. In this way, we hope to encourage collaboration and the building of a community of supervisors. 

Here are the first reflection questions for this module: 

  1. Is your organisation considering or preparing any type of internal reform project that would help you become a data-driven DFS supervisor?
  2. Does the project only deal with increasing the quantity and frequency of data, or does it cover other aspects, such as organisational and capacity-related, that are needed for a transformative change? 
In reply to First post

Re: Introduction to Data-Driven Supervision

by zelalem Adugna Dessie - Group 2
Our authority is undertaking internal reforms to transition toward a data-driven supervisory model. This includes leveraging trading and transaction-level data to enhance risk-based supervision, establishing centralized data infrastructure, adopting SupTech tools, and building internal data analytics capacity. These reforms aim to improve early risk detection, strengthen investor protection, and ensure financial stability in an increasingly digital financial ecosystem
In reply to First post

Re: Introduction to Data-Driven Supervision

by Lucy Kihembo - Group 4
1. Yes, the Bank has implemented a Suptech project to improve efficiency in the prudential processes by leveraging technology. Some routine reporting will be automated, supervisors can collect, process and analyse data to identify patters, potential fraud and patterns, assess risks among other uses.
2. The project covers other aspects as mentioned. This has been structured in such a way that governance includes a specific Board committee to handle this as a priority area with the related reporting frequency. Operationally, this has been incorporated in the Strategic priorities being handled by the Strategy and Innovation department. In terms of capacity building, different teams are being trained in areas such as programming, data analysis, machine learning, among others. Also the Project team is comprised of several departments that include data users, research, governance, IT staff, etc. This project also includes stakeholder engagement at each stage to ensure the financial institutions are also aligned and investing in their technology infrastructure to be project ready.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Rehan Masood - Group 5
Yes, we are actively considering internal reforms to strengthen our transition toward becoming a more data-driven supervisor for digital financial services. As the DFS ecosystem expands in Pakistan, including new licensing categories and increasingly complex business models, we recognise that traditional supervisory approaches must evolve to incorporate stronger data capabilities across the supervisory lifecycle.

Importantly, the reform is not limited to increasing the volume or frequency of data collection. While enhancing data availability is necessary, the initiative also focuses on broader organisational and capability dimensions to enable a genuinely transformative shift. This includes improving data governance frameworks, investing in analytical tools and supervisory technology, and strengthening staff capacity in areas such as data analytics, risk modelling, and technology risk.

In addition, we are working toward integrating data more directly into supervisory decision-making processes, so insights can inform risk assessments, supervisory planning, and policy development in a more systematic way. Aligning processes, skills, and technology in this manner is essential for ensuring that data does not simply accumulate, but is translated into actionable supervisory intelligence.

Overall, the objective is to build a sustainable supervisory model that leverages data to enhance risk detection, improve resource allocation, and support innovation while safeguarding stability and consumer protection in Pakistan’s evolving DFS landscape.
In reply to First post

Re: Introduction to Data-Driven Supervision

by LEILAH ABDALAH MUBEYA - Group 6
1.Our organisation is considering and implementing internal reforms to strengthen data-driven supervision of Digital Financial Services by improving data collection, integration, and analysis.
2. These reforms go beyond increasing data quantity and frequency to include organisational and capacity-building measures such as staff skills development, system upgrades, and process improvements, all aimed at achieving a transformative and sustainable data-driven supervisory approach.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Mariam Nansubuga - Group 4
1. Yes, Bank of Uganda is undertaking an E-Supervision (SupTech) Project directly aimed at transforming it into a data-driven supervisor.

2. The project uses automation, data standardization, and advanced analytics to allow for quick, preventive, and informed oversight, with the goal of improving compliance, trust, and stability in Uganda's financial system. It is a transformational step toward smarter, faster and more transparent regulation.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Erah, Dominic Ose Erah - Group 1
1. The Central Bank of Nigeria uses SupTech tools for off-site a d onsite supervision, including data driven tools for integrity checks, ML/TF monitoring and supervisory automation. In the same vein, the CBN is actively preparing and implementing an internal reform project aimed at becoming a technology enabled, data driven supervisor.
2. The project clearly goes beyond increasing data quantity or reporting frequency. It involves integration of advanced analytics and data science into supervisory processes, strengthening organizational capacity for technology driven oversight, enhancing CBN's supervisory capabilities for payments and remittances and supporting long standing structural reforms in regulatory technology
In reply to First post

Re: Introduction to Data-Driven Supervision

by AISHA UMARU HADEJIA - Group 1
The Central Bank of Nigeria is considering broader reforms that go beyond just collecting more data. Under The Governor’s 10 point agenda, the Bank is working to strengthen governance, enhance Nigeria’s payment systems, expand financial inclusion, and adopt new regulatory frameworks that support innovation. These efforts align with global trends toward data driven supervision (suptech), where regulators use technology not only to increase the quantity and frequency of data but also to improve analytical capacity, organizational processes, and risk monitoring. In practice, the Bank is looking at reforms that combine stronger data infrastructure with institutional and capacity building changes so supervision becomes more proactive, adaptive, and supportive of digital financial services growth.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Sarah Davinah Namata - Group 4
1. Uganda has launched a SupTech project aimed at facilitating data driven DFS supervision. It is a transformational step toward faster and more transparent regulation that can improve compliance, build trust, and strengthen stability in Uganda’s financial system.
2. No, SupTech in Uganda is not only about increasing the quantity and frequency of data. It goes well beyond data collection and touches organisational structure, skills, processes, and supervisory culture.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Basil Paul Buyondo - Group 4
Bank of Uganda is implementing SupTech solutions that use automated reporting, data analytics, and real-time monitoring tools to enhance risk-based supervision, financial stability oversight, and consumer protection in the digital financial sector.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Sheena Rebecca Nantumbwe - Group 4
Uganda has launched a SupTech project to enable data-driven supervision of digital financial services and improve efficiency in prudential processes. The initiative will automate reporting and strengthen supervisors’ ability to analyse data, detect risks and fraud, and support faster, more transparent regulation.

SupTech in Uganda goes beyond data collection to include governance, organisational structures, skills, processes, and supervisory culture. It is overseen by a dedicated Board committee, embedded in strategic priorities, supported by staff capacity building and a multidisciplinary team, with ongoing stakeholder engagement to ensure industry readiness.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Benedict Muhiire Hamenya - Group 4
Yes, my organization is currently undergoing a SupTech project to enhance supervision of commercial banks, non-bank financial institutions, payment service providers, payment system operators, EMIs and other licensed institutions by leveraging on the possibility of real-time transaction monitoring among many other supervision techniques.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Faith Fxentirimam Envuladu - Group 1
The Central Bank of Nigeria (CBN) is actively implementing internal reforms that strengthen its capacity to supervise digital financial services (DFS) using data‑driven and technology enabled approaches. In January 2025, the CBN launched:
The Document Flow (DocFlow) System — digitizing internal document management and workflows and
MDAs Naira Payment Solution — automating government payments and improving transparency These efforts are part of the CBN’s Digital First transformation.

The CBN’s reforms extends beyond simply increasing data volume or reporting frequency. Some of the Bank's initiatives show that the Bank is undertaking organizational, structural, capacity‑building, governance, and technological transformation measures that collectively support a shift toward a modern, data‑driven supervisory model including for DFS (digital financial services).
In reply to First post

Re: Introduction to Data-Driven Supervision

by Michael Sserwanga Sserwanga - Group 4
Yes, my organisation is currently implementing a Supervision technology project, aimed at strengthening data driven supervision across banks and other financial institutions and Digital Financial Service providers. The project is designed to enhance offsite surveillance, automate reporting processes, and improve our ability to identify emerging risks in a timely manner.

The project goes beyond merely increasing the quantity and frequency of data. Becoming data driven requires improving data quality, prioritising appropriate supervisory tools as well as upskilling staff. In our context, this includes reviewing data infrastructure and reporting templates, strengthening analytics capacity, through the various trainings being offered to staff on data governance and infrastructure. The objective is not simply to increase the quantity and frequency of data collection, but to transform how our supervisory decisions are informed and executed.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Usman Bayero - Group 1
The CBN us currently executing a multi-faced reform agenda, most notably through the 2026 Fintech Strategy and the Smart Licensing & Supervisory Gateway (SLSG). This project shifts the Bank away from manual processes toward a technological execution layer that embeds SupTech for realtime oversight and proactive risk management. Far from just increasing data frequency, the reform is a transformative overhal that intergrates organisational restructuring with intensive capacity builing in data analytics and risk based methodologies.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Jemimah Precious Kuteesa - Group 4
Yes, the Bank has implemented an e-supervision project designed to enhance operational efficiency and supervisory decision making. The project is expected to strengthen staff analytical capacity, support data-driven policy development, and facilitate the availability of consistent, reliable, and granular supervisory data.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Aboo Badhasa Aboma - Group 2
1. The ECMA is actively implementing a modern reform project through its newly launched Supervisory Technology (SupTech) framework and automated reporting guidelines. This transition is further supported by the Regulatory Sandbox, which allows the authority to gather real-time data on innovative DFS business models and emerging digital risks. By digitizing reporting templates for market participants, the authority is shifting away from manual oversight toward a proactive, data-driven supervisory stance.

2. The reform project is a holistic transformation that integrates organizational restructuring and specialized capacity building to ensure staff can analyze complex digital datasets. It also addresses inter-agency coordination, aiming to build a shared data ecosystem with telecommunications and AI authorities to monitor systemic risks like cyber threats and fraud. This approach ensures that the "organizational brain" of the ECMA evolves alongside the increasing quantity of data to facilitate effective, risk-based decision-making.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Elsabet Getachew Mulugeta - Group 2
1. ECMA is a new regulator and the market is nacet but our leadership is very much interested to modernize and use technology driven systems such as AI and Sup Tech for any possible supervisory or regulatory work. even our government is more focused on technology for the last seven years and digital Ethiopia is being implemented in every possible aspect. Therefore, there is the interest to implement but we need to do more market activities and hold data fist.
2. ECMA is ambitious and we want to do all possible and that is why we want to be enrolled and build the capacity even in this early stage of our market. The leadership is interested to design ECMA and the market future from the start.
In reply to First post

Re: Introduction to Data-Driven Supervision

by KABIRU MUDASHIRU - Group 1
1. The Central Bank of Nigeria has been using suptech for the collection and analysis of data from regulated entities. Despite this, the bank is investing more in suptech to improve current processes, especially amid the rise of fintech-led institutions and the adoption of regtech solutions by these institutions, and the pace of transactions, coupled with their infrastructure investment to better meet customers' needs.

2. The current exercise is not only about investment in the suptech tool, but it's also a whole culture change for the bank. The tone has been set by management, and the path is being followed by all.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Aliyu Mohammed - Group 1
Currently we are at the verge of revamping our complaints management solution to a more robust, AI driven suptech.
The project goes beyond increasing quantity or frequency of data. It volves the use of AI and ML to ensure that exluded segments could easily submit complaints via IVR and the solution will use natural language processing to extract texts and open a complaint ticket. It is going to be transformational.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Sarim Ali - Group 5
At the State Bank of Pakistan, there is growing recognition that becoming more data-driven is essential for effective DFS supervision, especially given the rapid growth in digital payments and EMIs. Ongoing reforms are not only focused on increasing the frequency and granularity of reporting, but also on strengthening data analytics capacity and investing in SupTech tools.

However, true transformation goes beyond data collection. It also requires upskilling supervisory staff, improving data infrastructure, and fostering a culture that supports innovation and data-driven decision-making.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Ahmed Jibrel Yeha - Group 2
Of course, my organization is considering as well as preparing itself to implement risk-based supervision by the help of technology and the powers of data.
This initiation includes enhancing capacity and supported by technology to make data available, to be capable of retrieving meanings from it and to use for decision making including for market supervision function.
In reply to First post

Re: Introduction to Data-Driven Supervision

by Agaba Albert Busingye Agaba - Group 4
In Uganda, the Bank of Uganda is implementing a Supervision Technology system (Sup Tech) to facilitate real time collection of data through reports and returns and guide supervisors to assess accurate information of digital financial services providers, financial institutions to improve identification and mitigations of risks.

Bank of Uganda is also developing a data collection unit known as the Central Data Hub for collecting information of institutions and individuals borrowing to support Financial Inclusions of all services providers and improve the risk assessments made in relation to the old and emerging Digital Financial providers and financial institutions.

The Sup Tech project also covers the organizational and capacity-related developments and team buildings of supervisors and business continuity of the supervision processes.