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Financial Stability Institute FSI Insights on policy implementation No 29 From data reporting to data-sharing: how far can suptech and other innovations challenge the status quo of regulatory reporting? By Juan Carlos Crisanto, Katharina Kienecker, Jermy Prenio and Eileen Tan December 2020 JEL classification: G20, G28, O31, O32 Keywords: Suptech, data collection, regulatory reporting, data standardisation, regulatory data, data transmissionFSI Insights are written by members of the Financial Stability Institute (FSI) of the Bank for International Settlements (BIS), often in collaboration with staff from supervisory agencies and central banks. The papers aim to contribute to international discussions on a range of contemporary regulatory and supervisory policy issues and implementation challenges faced by financial sector authorities. The views expressed in them are solely those of the authors and do not necessarily reflect those of the BIS or the Basel-based committees. Authorised by the Chairman of the FSI, Fernando Restoy. This publication is available on the BIS website (bis). To contact the BIS Media and Public Relations team, please email pressbis. You can sign up for email alerts at bis/emailalerts.htm. Bank for International Settlements 2020. All rights reserved. Brief excerpts may be reproduced or translated provided the source is stated. ISSN 2522-2481 (print) ISBN 978-92-9259-443-5 (print) ISSN 2522-249X (online) ISBN 978-92-9259-444-2 (online)From data reporting to data-sharing: how far can suptech and other innovations challenge the status quo of regulatory reporting? iii Contents Executive summary . 1 Section 1 Introduction . 3 Section 2 Innovations in regulatory reporting . 6 Section 3 Regulatory reporting initiatives . 9 Data transmission. 11 Data standardisation and transformation rules . 12 Granularity of required reporting data . 16 Data access . 17 Section 4 Issues and challenges . 18 Issues and challenges specific to certain regulatory reporting approaches . 19 How are financial authorities addressing some of these challenges? . 20 Section 5 Conclusions . 23 References . 25From data reporting to data-sharing: how far can suptech and other innovations challenge the status quo of regulatory reporting? 1 From data reporting to data-sharing: how far can suptech and other innovations challenge the status quo of regulatory reporting? 1 Executive summary Regulatory data are the backbone of effective financial sector supervision but regulatory reporting is a complex and costly process and bogged down by several obstacles. Financial authorities need access to timely and good-quality data in order to exercise their regulatory and supervisory functions. The current pandemic, through its limitations to on-site supervisory reviews, has reinforced the importance of robust and flexible regulatory data frameworks in crisis situations. However, multiple factors complicate the regulatory reporting process. These include heterogeneity in how internal data are defined across financial institutions, the complexity of regulations and inclusion of reporting instructions across different regulations. These complicating factors introduce not only a degree of uncertainty about the accuracy and completeness of regulatory reports but also complexity in the process of transforming internal data into reported data. This complexity necessitates significant investment from financial institutions in running their regulatory reporting systems. Innovations in regulatory reporting are aimed at mitigating the complexity and addressing the obstacles that exist at the different points in the regulatory reporting process. Innovations have taken place at the level of either operational data (ie data from business operations) or “input data” (ie data elements needed to populate regulatory reports) by way of standardisation across the industry (eg through the use of data dictionaries). They have also taken place in the way transformation rules (ie description of the steps for generating regulatory reports) or reporting instructions are defined/written. The format and granularity of the required reporting data have also evolved over time. Moreover, the technology used for transmitting data has obviously been progressing over recent years. Lastly, there are initial experiences and experimentations aimed at enabling financial authorities to actively access data from financial institutions. This paper covers regulatory reporting initiatives at 10 financial authorities that are implementing or have implemented innovations in their data collection frameworks. Most authorities are implementing innovations in terms of data standardisation and granularity of required reporting data. Around half are implementing innovations in the means of data transmission and transformation rules. Only a few authorities, however, are implementing innovations in the format of required reporting data or actively accessing data from financial institutions. As data standardisation provides a foundation for improvements in the regulatory reporting process, innovations in transformation rules always occur alongside data standardisation and almost all of the authorities aiming at granular reporting are also implementing data standardisation. Innovations are enhancing the quality of regulatory data and setting the basis for achieving the ultimate objective of moving towards the concept of “data-sharing”. Authorities initiatives are 1 Juan Carlos Crisanto (juan-carlos.crisantobis) and Jermy Prenio (jermy.preniobis), Bank for International Settlements, Katharina Kienecker (katharina.kieneckeroenb.at), Central Bank of the Republic of Austria, and Eileen Tan (eileen_cm_tanmas.gov.sg), Monetary Authority of Singapore. The views expressed in this paper are those of the authors and not necessarily those of the BIS, the Basel-based committees, the Central Bank of the Republic of Austria or the Monetary Authority of Singapore. The authors are grateful to the representatives from the authorities and institutions interviewed, and to Patrick Armstrong, Rodrigo Coelho, Puneet Pancholy, Jos Mara Serena, Ken Taniguchi and Joy Wann for helpful comments. We are also grateful to Dung Tran for valuable support with this paper.2 From data reporting to data-sharing: how far can suptech and other innovations challenge the status quo of regulatory reporting? enhancing regulatory data quality by either ensuring consistency in data through standardisation or embedding data validation rules in the data transmission solutions. Other common benefits expected from these initiatives include straight through data processing, more timely reports and reports that can be used flexibly for different types of analyses. More advanced regulatory reporting initiatives are expected to result in automatic generation of reports and enabling authorities to shift away from the concept of regulatory data reporting to that of “data-sharing”. This refers to the ability of financial authorities to extract the information they need directly from financial institutions databases. “Data-sharing” can therefore help realise on-demand monitoring of financial institutions condition and allow authorities to act swiftly if the situation calls for it, thus contributing to greater financial stability. However, authorities face a number of issues and challenges in the implementation of their regulatory reporting initiatives, key among which are reconciling the different interests of various stakeholders and addressing legacy systems. Shepherding the different views, practices, resources and cultures of different stakeholders is the challenge most cited by financial authorities. In particular, the relative burden facing smaller financial institutions in terms of financial and technical resources could make the implementation of ambitious initiatives more challenging. Financial authorities are addressing these constraints by either tailoring the new reporting approaches to different types of financial institutions or providing financial grants or technical support to assist with implementation. In terms of technology, the complicated process of disentangling closely intertwined legacy systems causes a strong preference for the status quo, which in turn makes it challenging to get buy-in. Based on the experience of authorities covered in this paper, there may be certain preconditions for a regulatory reporting initiative to succeed. These include: a. Strong commitment and support from top management at both financial authorities and financial institutions; b. Alignment of vision by engaging transparently, collaboratively and openly with key stakeholders; c. A culture of innovation that relies on data-driven decision-making, openness to experimentation and questioning “legacy thinking” within financial authorities; d. A well defined centralised data strategy and data governance framework within financial authorities; and e. Effective management of the transition to new regulatory reporting processes, particularly by taking a step-wise approach. Looking ahead, while a shift to a “data-sharing” concept may take time, the trend towards more granular and integrated reporting is very likely to continue. For the “data-sharing” concept to become a reality, the right technology and data standardisation are critical. But the technology to implement this concept is still being developed, and while data standardisation is certainly attractive since it can significantly simplify the regulatory reporting process, implementing it particularly on a wider scale raises financial, practical and competition issues. So a widespread shift to the “data-sharing” concept is unlikely to happen in the near term. That said, many authorities have already started their journey towards more granular and integrated reporting and more will possibly follow. But implementation may take different forms. Smaller financial institutions will likely generate required granular reports in a more traditional way but aided by a more modern format of reports and means of data transmission. Larger financial institutions are expected to be subject to more data standardisation, especially for reporting areas with cross-border elements in which data interoperability is important (eg in the area of derivatives reporting). Several initiatives towards data standardisation are already under way at the regional (particularly in Europe) and international level. FSB (2020), which calls for potential international collaboration in evaluating the scope for common data standards for relevant regulatory areas, provides a boost to these important initiatives.From data reporting to data-sharing: how far can suptech and other innovations challenge the status quo of regulatory reporting? 3 Section 1 Introduction 1. Financial authorities rely on good and timely information to fulfil their monetary, financial stability and other mandates. Statistical and regulatory data constitute the largest category of information that authorities collect from financial institutions. This information allows authorities to obtain an accurate picture of the economy, the financial system and individual financial institutions. Statistical data include balance sheet information, the main objective of which is to support authorities monetary and macroprudential mandates. Regulatory data refer to prudential concepts such as capital positions and liquidity resources as well as credit, market, operational and other risk exposures. Regulatory data are primarily used to support authorities micro- and macroprudential supervisory tasks as well as their crisis management responsibilities. The Bank of England estimates that 90% of the reporting forms in a typical bank correspond to regulatory reporting requirements. 2 2. Regulatory data are the backbone of effective financial sector supervision and hence authorities invest considerable resources in data collection and assessment. Authorities rely on regulatory data to have a comprehensive understanding of the risk profile of a financial institution. This information is a critical input for authorities deployment of their risk-based supervisory approach, including determining the frequency, scope and depth of on-site reviews. This type of data is also used to identify emerging risks; support policymaking; and facilitate supervisory exercises such as thematic reviews or stress tests. Regulatory data are typically captured through a number of specific reporting requirements, using detailed templates that follow a variety of reporting frequencies and relying on different collection systems. The specific nature of the reporting requirements and templates used have made it challenging to repurpose regulatory data for other uses. This, in turn, has led to redundant reports and substantial investment in IT and staff to collect, store, process and assess regulatory data. 3. Collecting and reporting regulatory data is a complex and costly exercise for both financial authorities and financial institutions. For financial authorities, there may be a lack of a central data governance function resulting in different users determining their own data needs. This leads to an exponential growth in regulatory reports, which have limited uses apart from the intended analysis by the users, and potential data duplication. Data collection solutions may also not facilitate straight through data processing (ie automated processing of data from collection to validation and all the way to analytics and visualisation). For financial institutions, complying with regulatory reporting requirements is complex due to multiple factors, including the fact that reporting instructions are found in different regulations and their wording might be unclear or subject to different interpretations. Importantly, regulatory data do not fully align with data used for internal reporting purposes, which themselves vary across financial institutions. This results in financial institutions having to transform information from their business operations into regulatory data based on their understanding of the reporting instructions. This transformation process typically requires input across units within the financial institution and expert judgment. As such, it introduces not only a degree of uncertainty about the accuracy and completeness of the reported data but also the possibility that the same data could be treated differently across financial institutions. The size of a financial institution, its business model and the resources allocated to deal with regulatory reporting can also make the regulatory reporting process more complex. 3 This complexity requires significant investment from financial institutions in running their regulatory reporting frameworks. 2 BoE (2020). 3 For instance, a large cross-border bank must meet reporting requirements in several jurisdictions and hence repeat th
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