Regtech and suptech in central banks: 2024 survey

These technologies enable the identification and swift resolution of emerging issues, as well as preventative action

In an increasingly complex financial landscape, valuable insights from more granular and real-time regulatory data can only be harnessed with the right tools. Regtech aids regulatory reporting compliance and suptech processes the data to generate insights. Regtech and suptech allow for the “quicker detection of anomalies and risks in financial markets, as well as facilitating interventions to ensure timely responses to emerging issues”, an official told Central Banking. Predictive modelling enables preventative interventions, which has “revolutionised the supervisory process”.

There is work to be done with regard to data sharing among central banks and the supervisory authorities themselves. One official explained that a challenge to implementing regtech and suptech was approaching other financial authorities known as “developers of suptech and regtech strategies” to be able to “exchange experiences and gather advice and recommendations based on best practices”. This survey bridges that gap and delves deeper into regtech and suptech adoption at financial authorities and its transformative potential.

Does your institution use regtech or suptech?

Of the 15 respondents, just over half, eight (53%), said they used regtech or suptech, six (40%) responded no and one (7%) said it was currently implementing the technology.

Whether a central bank or supervisory authority uses regtech or suptech appears to correlate with jurisdiction income classification. Of the respondents that said they use the technology, four are in high-income countries, three in upper-middle and one is in a lower-middle income jurisdiction.

The average number of staff among central banks with the technology was around 1,500, a stark contrast to 500 among those that do not use regtech or suptech.

Number of regtech and suptech initiatives

It is common for central banks to have a number of regtech and suptech initiatives once they have implemented the technology. Central Banking asked whether institutions had 1, 2–5 or 6 or more regtech and suptech solutions. Of the eight using the technology,  half said they had 2–5 regtech or suptech initiatives in their institution and three had more than six.  One institution did not provide a response.

How the technology was developed

Among regtech and suptech users, financial authorities were most likely to develop their regtech and suptech collaboratively. Three respondents said they developed their regtech and suptech solutions in-house and four developed them both in-house and using a private provider. Just one respondent said they depended on an outside technology firm completely.

Considering using the technology

Of the six respondents that do not use regtech or suptech, three said they were considering using it, two said they were not, and one did not provide an answer.

How regtech and suptech have improved regulation and supervision

The central banks and regulatory authorities that are currently using regtech and suptech provided insights on how regtech and suptech help them fulfil their mandates.

An official from a high-income European central bank said suptech and regtech had created more efficient information flows between supervised parties and supervisors, and improved the accuracy, consistency and timeliness of the information collected. An official from a high-income central bank in the Middle East said streamlining processes led to better resource allocation and “reduced the time and effort spent on analysis”.

An official from a financial authority in the Americas said analysis has been enhanced by data visualisation control panels that facilitate decision-making. This includes a “sentiment index created with artificial intelligence [AI]” to analyse topics associated with financial stability. Internal uses include financial, accounting and operational indicators.

At an upper-middle income central bank in the Americas, “suptech has revolutionised the supervisory process”, allowing for quicker detection of anomalies and risks in financial markets, as well as facilitating interventions to ensure timely responses to emerging issues.

At a third central bank in the Americas, with the use of automation and improved data management, “new preventative supervisory approaches have been implemented, which make it possible to anticipate possible non-compliances”. The technology also allows for the timely analysis of the information provided by financial intermediaries on policy issues related to client due diligence, validation of official sanctions lists, unusual operation monitoring systems and risk assessments within payment systems. Additionally, the central bank is researching and looking to develop new and more efficient regtech and suptech solutions. “The central bank is convinced that the use of such tools will increase in the near future.”

Challenges to implementing the technology

The timing of implementing new solutions needs to be carefully managed, while meeting ongoing demands. An official from one of the upper-middle income institutions in the Americas said: “The development of a clear and structured institutional strategy in suptech matters has been a continuing challenge as technology advances and the market grows in size and complexity.” They have to balance “selecting successful and cost-efficient projects at the right moment, while being focused on day-by-day issues of supervision and regulation”. Meanwhile the market “is still evolving”, and its participants “heterogeneous” in terms of digitalisation and technology adoption.

Another official said challenges to implementation included the time it takes for the development of new technological solutions to meet the needs of different departments. Furthermore, “scarcity of human and financial resources” is a significant hurdle, another central banker highlighted. Expanding the workforce typically requires “navigating the complex landscape of public sector recruitment”. While public procurement regulations ensure “transparency and fair competition”, they also introduce “significant delays in acquiring the necessary technology and expertise”.

A central banker from a high-income regulatory authority in the Middle East said there needs to be a “mindset change” at the institution. In a “stable” world, tools built based on end-users’ documented work procedures can be the best approach but, when things are moving quickly, “such a process will stifle innovation and improvement”.

“Times of change”, they said, “call for cross-functional collaboration and an experimentative process … requires first-principles thinking, openness, creativity and a new kind of accountability from all parties.”

When working with external partners, because “suptech solutions are often unique from other industries and even other supervisory authorities when the solutions are new to all parties”, it is important to have “a clear agreement in place to set measurable success criteria and objectives for the partnership” and “determine how the generated intellectual property is shared between the parties”.

How do you see the role of regtech or suptech solutions in your supervision process?

Among the nine authorities that are either using or implementing regtech and suptech, all said they are either useful or essential for the reporting entity registration process, data collection and data validation, data analyses, data sharing and on-site supervision. Most considered it essential for data collection and data validation, data analyses and data sharing.

Five respondents not using regtech or suptech gave their views on the technology. Of those, all but one still view it as either useful or essential for the aforementioned use cases.

How often does your institution collect data?

Among central banks that use regtech and suptech, financial data monitoring, prudential supervision data and monitoring data from non-bank financial institutions tend to be collected monthly. Cyber risk supervision and climate/environmental, social and governance (ESG) risk supervision data tends to be collected on an ad hoc basis. Respondents were split on when they collect anti-money laundering (AML)/combatting the financing of terrorism (CFT) data as either daily or ad hoc. Some respondents did not provide answers for all sections of the question.

Among those institutions that do not use regtech or suptech, prudential and financial monitoring data also tended to be collected on a monthly basis. Climate/ESG risk supervision data tended to be collected ad hoc.

Just one respondent said it collects real-time data, and this was for AML/CFT supervision only. Once again, some respondents did not provide answers for all sections of the question. 

Do you rely on standards such as technical data formats or standard methodologies to manage your data collection processes?

All central banks and regulators that use regtech and suptech said they relied on data standards during the data collection process (eight, 53%). However, the standards reported on showed variability between central banks and financial authorities even within similar geographies. The central bank currently implementing the technology did not prove an answer (one, 7%).

Perhaps surprisingly, among those that do not use regtech and suptech, no central banks or regulators said that they rely on technical data formats or standard methodologies to manage their data collection processes. Four (27%) said they plan to, but two (13%) said they have no such intentions.

“It should be noted it has been proven that standard formats and methodologies facilitate massive automation and supervision processes,” an official from an upper-middle central bank that uses the technology said. They added that, with respect to information that is not received via structured regulatory reports, data was collected via a number of different means, such as questionnaires. The department that gathers and processes the information for its own or others’ consumption, then analyses it with the help of tools such as dashboards and statistical tests.

An official from a high-income central bank in the Middle East said it uses a risk-based approach to data collection “based on Basel Committee, International Monetary Fund [IMF] and Financial Action Task Force standards and risk-based supervision methodology used by the World Bank”. It also uses a “specific national risk assessment and sectoral risk assessment methodology designed by a consultant and the IMF”.

Among other institutions that developed their technologies in collaboration with a private provider or in-house, some specifically mentioned collected data through eXtensible Business Reporting Language (XBRL) and Extensible Markup Language (XML) files. XBRL is an extension of XML and is a leading framework for global financial data exchange, with central banks and financial authorities among the standards consortium members.

Do you believe machine learning and AI can help in your regulatory and supervisory mission?

Fourteen (93%) central banks and regulators – all apart from one – said they believe machine learning and AI can help in their regulatory and supervisory missions.

An official from a high-income regulatory authority in the Middle East said: “Machine learning and AI have significant potential in enabling us to process more information and closer to real time than was previously possible”. Benefits include identifying patterns that aren’t easily observable for human experts and “augmenting human intelligence across descriptive, diagnostic, predictive and prescriptive analyses”.

“Machine learning and AI hold immense potential to enhance our regulatory and supervisory mission,” an official from a central bank in the Americas said. The technology can “detect patterns and identify potential risks more efficiently and accurately than traditional methods”.

They added that automating repetitive tasks could free up “valuable human resources to focus on more complex and strategic aspects of regulation and supervision”. Moreover, with AI, supervisors can “develop predictive models that forecast market trends and anticipate emerging risks, allowing for more proactive and preventive regulatory interventions”.

“These tools will shape the future regulatory workforce and how our central bank works,” an official from a high-income central bank in Asia-Pacific agreed.

Does your institution use cloud services?

Cloud services can help meet growing data collection storage needs and provide computing capacity for analysis. Among the 15 central banks and regulators, eight (53%) said they use the cloud, four (27%) said they do not, but plan to, and three (20%) said they do not and do not plan to. The most common deciding factors on a move to the cloud were security, costs and availability.

Of the eight respondents that use regtech and suptech, four use the cloud, three do not, but plan to, one does not and does not plan to. Among the six respondents that do not use the technology, three use the cloud,  two do not and do not plan to, and one does not, but plans to.

Do you share collected data with external users or plan to?

Data sharing can alleviate some of the burden of collection, offering the potential to increase market transparency and generate deeper insights. Fourteen institutions said they shared data with external users (93%). Just one central bank (7%) said it did not share data with external users and does not plan to. Most commonly, data is shared with other governmental agencies (13, 87%), followed by the public (11, 73%) and supervised entities (nine, 60%).

 

Other organisations that central banks and other financial authorities reported sharing data with include the IMF, the World Bank and the International Finance Corporation, UN Trade and Development, the European Bank for Reconstruction and Development, the Inter-American Development Bank, the UN Economic Commission for Latin America and the Caribbean and the Commonwealth Secretariat.

Bloomberg, and credit rating agencies Moody’s and S&P, were also named as data recipients. National AML/CFT organisations and other governmental agencies may also receive information “based on need and request”.

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