Financial authorities’ use of supervisory technology (SupTech) tools has accelerated and proved ‘indispensable’ during the Covid-19 pandemic but ‘formidable’ implementation challenges mean barriers remain to broader adoption and acceptance.
That is the verdict of a newly published paper from the Financial Stability Institute (FSI), a Bank for International Settlements (BIS)-housed body that exists to help supervisors to improve their financial systems.
‘Suptech tools for prudential supervision and their use during the pandemic’ sets out how travel restrictions and social distancing protocols ‘severely curtailed’ on-site inspections and prompted financial authorities to use more SupTech tools for their day-to-day oversight of companies. At the same time, supervisory authorities recognised the need to develop new data analytics tools for prudential purposes.
Twenty authorities that took part in the research reported using, developing or experimenting with 71 different prudential supervisory tools, up from just 12 tools in 2019. In total, authorities that responded to the survey reported 130 SupTech ‘use cases’.
But ‘limited’ data science skills within supervisory authorities, data quality issues that underpin SupTech models and ‘settling on an appropriate calibration of SupTech parameters’ are all hampering broader adoption of SupTech tools, according to the paper.
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SupTech, a strategic priority for a growing number of financial authorities, is among six priorities in the BIS Innovation Hub’s work programme for 2021-2022 alongside its sister discipline RegTech (the application of technology to improve regulatory compliance).
Global Government Fintech reported in January that the European Central Bank (ECB) had kicked off its first ‘SupTech’-specific procurement with an ‘estimated total value’ is €227.5m (about £193m).
The ECB’s move came three months after the Financial Stability Board (FSB) published a report on the use of SupTech and RegTech by FSB members and regulated institutions that described technology and innovation as ‘transforming’ the global financial landscape, presenting opportunities, risks and challenges for regulated institutions and authorities. Opportunities offered by SupTech, as well as RegTech, have been created by growing availability and granularity of data, and infrastructure such as cloud computing and application programming interfaces (APIs), the 76-page publication noted.
More than half the 71 SupTech tools captured in the FSI paper assessed mainly qualitative data, ‘underscoring the importance of analysing textual information in prudential supervision’, the paper notes. The remaining tools were split between those that analyse mainly quantitative data and others that scrutinise both quantitative and qualitative data. ‘Despite these variations, all tools aim to extract deeper supervisory insights or to improve supervisory efficiency,’ the researchers state.
A previous Financial Stability Institute (FSI) publication found that most SupTech tools were used for reporting and misconduct analysis, with relatively few deployed for prudential supervision. The Financial Stability Board found similar results in 2020, though it did observe a rise in SupTech use cases for prudential purposes.
‘SupTech tools proved indispensable’
‘As more [SupTech] tools become operational, a critical consideration is to ensure that the tools’ outputs support, rather than replace, supervisory judgment,’ the 26-page paper states. ‘In this context, a comprehensive SupTech strategy – that addresses many of these challenges – becomes indispensable, particularly as more supervisory activities migrate to a virtual setting.’
The findings were based on responses to a survey of what the FSI refers to as its ‘Informal Suptech Network’, combined with follow-up interviews with some jurisdictions. Authorities that responded included the Australian Prudential Regulatory Authority (APRA), Central Bank of Brazil, the ECB, Deutsche Bundesbank, Central Bank of Malaysia, Qatar Financial Centre Regulatory Authority, Swiss Financial Market Authority and US Federal Reserve System.
‘The migration of on-site activities to off-site work, in conjunction with various ad hoc reports requested during the pandemic, added to the mounting stack of existing structured and unstructured data that required review. In the virtual environment, SupTech tools proved indispensable,’ the paper states.
Data management platforms, file exchange protocols, collaboration software and communication tools enabled the shift to virtual supervision, partly offsetting limited on-site inspections. Meanwhile, growth of ‘non-traditional’ data sources that can have a bearing on a company’s risk profile and new analytical tools to help process and analyse data – such as artificial intelligence (AI) and machine learning (ML) – provided authorities with opportunities to deploy a range of SupTech tools for prudential supervision, the paper explains.
Risk of ‘supervisory blind spots’
The paper states that, overall, SupTech tools are automating ‘lower-value, labour-intensive’ tasks and supporting ‘higher-value, judgment-based’ functions – trends that are accelerating.
But, in this vein, it goes on to issue a warning that supervisors ‘could rely less on their own judgment and depend more on the SupTech output to identify key supervisory issues’. This ‘may lead to supervisory blind spots and a broader loss of institutional knowledge based on the art of judgment-based supervision,’ it states.
‘While authorities have emphasised that SupTech tools support, rather than replace, supervisory judgment, explicit policies that acknowledge the tensions between, and outline the respective roles of, supervisory judgment and SupTech tool outputs, could help,’ the paper suggests.
The paper’s annex details 11 SupTech use cases. For example, the Bank of Thailand and Banca d’Italia (Bank of Italy) each use AI/ML to analyse board meeting minutes of financial institutions, ‘with some interesting similarities and differences in their respective approaches’; and the FRS has operationalised a natural language processing (NLP) tool called Language Extraction (LEX) that applies AI/ML techniques to analyse documents from multiple places.
The BIS Innovation Hub is currently engaged in ‘Project Ellipse’, a proof-of-concept project investigating the feasibility of an integrated regulatory data and analytics platform for SupTech purposes. This project – which, more specifically, is exploring cross-border digital regulatory reporting using a machine-executable data model – is being led, in its first phase, by the BIS Innovation Hub’s Singapore centre, working alongside the Monetary Authority of Singapore, as well as other authorities and partners.
FURTHER READING
‘CBDCs and SupTech among priorities as BIS Innovation Hub maps out 2021 agenda’ – our news story (23 January 2021) on the BIS Innovation Hub’s 2021-2022 work programme
‘ECB eyes “cutting-edge” tech as it launches first SupTech procurement’ – Global Government Fintech news story (18 January 2021) on the Frankfurt-based authority’s first ‘SupTech’-specific procurement
