The Next Wave of Suptech Innovation - Suptech Solutions for Market Conduct Supervision - World Bank Documents
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized MARCH 2021 Suptech Solutions for Market Conduct Supervision Suptech Innovation The Next Wave of TECHNICAL NOTE
Finance, Competitiveness & Innovation Global Practice © 2021 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of the World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. RIGHTS AND PERMISSIONS The material in this work is subject to copyright. Because the World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Any queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Pub- lisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2422; e-mail: pubrights@ worldbank.org.
CONTENTS Acknowledgments iii Acronyms and Abbreviations iv EXECUTIVE SUMMARY 1 1. INTRODUCTION 4 2. CATEGORIES OF SUPTECH SOLUTIONS FOR MARKET CONDUCT SUPERVISION 7 3. SUPTECH SOLUTIONS FOR MARKET CONDUCT SUPERVISION 10 3.1. Regulatory Reporting 10 3.1.1. Supervision Information Systems 10 3.1.2. Automated Data Submission via API 13 3.1.3. Web Portal Data Upload with Central Database 14 3.2. Collection and Processing of Complaints Data 15 3.2.1. Complaints Management System 15 3.2.2. Analysis of Unstructured Complaints Data 16 3.3. Non-traditional Market Monitoring 17 3.3.1. Web Scraping 17 3.3.2. Social Media Monitoring 18 3.3.3. Consumer Sentiment Analysis 19 3.3.4. Reputational Analysis 19 3.3.5. Dark Web Monitoring 20 3.4. Document and Business Analysis 20 3.4.1. Document Analysis for Regulatory Compliance 20 3.4.2. Document Analysis for Examination of FSPs 21 3.4.3. Document Analysis for Peer Group Comparison 22 3.4.4. Validation of Terms and Conditions 22 3.4.5. Automated Review of New Provider Registrations 23 3.4.6. Predictive Modeling of Financial Statements 23 3.4.7. Business Intelligence and Geospatial Analysis 24 3.4.8. Managed Data Platform 24 i
ii The Next Wave of Suptech Innovation 4. PEOPLE, PROCESS, AND IT INFRASTRUCTURE: THREE KEY ENABLERS 25 FOR SUPTECH IMPLEMENTATION 4.1. People: Culture and Skillsets 25 4.2. Process: Internal Champions and Strong Governance 26 4.3. Underlying IT Infrastructure 27 5. IMPLEMENTATION CONSIDERATIONS 28 5.1. Key Decisions in Suptech Implementation 28 5.2. Initiatives to Accelerate Suptech Implementation 31 5.3. Additional Challenges Encountered by Regulators 33 6. LOOKING FORWARD 34 REFERENCES 35 FIGURES 1. Suptech Solutions for Market Conduct Supervision and Key Enablers for Implementation 3 2. Suptech Solutions for Market Conduct Supervision and Key Enablers for Implementation 6 3. A Function-Based Suptech Taxonomy with Suptech Use Cases 7 4. Results Framework for Market Conduct Suptech Solutions 9 5. Overview of Suptech Solutions for Market Conduct Supervision 11 6. Dataflow Diagram of SIS Solutions 13 7. CMS Case Workflow and Data Architecture 15 8. Dataflow Diagram for Social Media Monitoring 18 9. Example of Dataflow Diagram in Document Analysis Solutions 21 10. Considerations for In-House Development Versus Using a Third-Party Vendor 29 CASE STUDIES 1. How BNR Designed Its SIS Solution 12 2. How NBR Develops Suptech Solutions 14 3. How Researchers at Princeton University and FSD Kenya Worked with the Central Bank of Kenya 17 to Analyze Complaints Data 4. The FCA’s Development of Sleuth, Its NLP Platform 21 5. How AFM Prioritized People within Its Transformation to Data-Driven Supervisors 25 6. How ASIC’s Innovation Office Collaborates with Industry Stakeholders 32 BOX 1. FinCoNet: SupTech Tools for Market Conduct Supervisors 33
ACKNOWLEDGMENTS This technical note is a product of the Financial Inclusion and Consumer Protection Team in the World Bank Group’s Finance, Competitiveness and Innovation Global Practice. This note was prepared by Ligia Lopes (former Senior Financial Sector Specialist, World Bank), Jennifer Chien (Senior Financial Sector Specialist, World Bank), Mackenzie Wallace (Market Con- duct Supervision Consultant), and Edoardo Totolo (Operations Officer, International Finance Corporation). Mahesh Uttamchandani (Practice Manager, World Bank) provided overall guid- ance. The team is grateful for the substantive feedback received from peer reviewers Douglas Randall (Financial Sector Specialist, World Bank) and Matei Dohotaru (Senior Financial Sector Specialist, World Bank), and from the International Financial Consumer Protection Organisation (FinCoNet). Editorial inputs were provided by Charles Hagner and design and layout assistance was provided by Debra Naylor of Naylor Design, Inc. The team also gratefully acknowledges the generous contributions of time and expertise by financial authorities at the Australian Securities and Investments Commission, the Authority for the Financial Markets (Netherlands), Autorité des Marchés Financiers (Québec, Canada), Banco de Portugal, Bank of England, Bangko Sentral ng Pilipinas (Philippines), the Central Bank of Ireland, the European Insurance and Occupational Pensions Authority, the Financial Conduct Authority (United Kingdom), the National Bank of Rwanda, and Nepal Rastra Bank. Finally, the team gratefully acknowledges the generous financial support of the Ministry of Foreign Affairs of the Kingdom of the Netherlands and the Bill & Melinda Gates Foundation under the Financial Inclusion Support Framework (FISF) program, without which preparation of this paper would not have been possible. iii
ACRONYMS AND ABBREVIATIONS ADF automated dataflow AFM Authority for the Financial Markets (Netherlands) AMF Autorité des Marchés Financiers (Québec, Canada) API application programming interface ASIC Australian Securities and Investments Commission BdP Banco de Portugal BI business intelligence BNR National Bank of Rwanda BOE Bank of England BOL Bank of Lithuania BSP Bangko Sentral ng Pilipinas (Philippines) CBI Central Bank of Ireland CFPB Consumer Financial Protection Bureau (United States) CMS complaints management system CRM customer relationship management EDW Electronic Data Warehouse EIOPA European Insurance and Occupational Pensions Authority EU European Union FCA Financial Conduct Authority (United Kingdom) FSP financial service provider MVP minimum viable product NLP natural language processing NRB Nepal Rastra Bank SIS supervisory information system USD United States dollar iv
EXECUTIVE SUMMARY Around the world, financial sector supervisors are Four key insights for market conduct authorities can experiencing a profound shift to data-driven supervi- be drawn from this note: sion enabled by the next wave of technology and data solutions.1 While technology and data are not new to INSIGHT 1: Increasing operational efficiency and enhanc- financial oversight, their specific application to financial ing supervisory effectiveness are two of the primary consumer protection and market conduct supervision is a motivations for adopting suptech solutions for market newer and welcome trend. conduct. In implementing suptech, financial authorities are often Supervisory technology, or suptech, refers to the use of driven by two different motivations: (1) increasing oper- technology to facilitate and enhance supervisory pro- ational efficiency and (2) improving hypothesis-driven cesses from the perspective of supervisory authorities. supervision. The former often involves automating busi- As highlighted in the World Bank’s 2018 discussion note ness processes by replacing elements of the supervision on suptech for market conduct supervision (World Bank decision framework with data and algorithms, bringing sig- 2018), examples of suptech for market conduct supervi- nificant efficiencies to the process, while the latter involves sion were initially limited. In recent years, the application helping supervisors to test and prove hypotheses using of suptech for market conduct supervisory purposes has new sources of analyses or data. become more widespread and sophisticated. Recent advancements, particularly in the realm of unstructured Given limited capacity at many financial authorities, and text analysis, present opportunities for market con- implementation of suptech for market conduct often duct supervision where a greater reliance on qualitative focuses on solutions to increase operational efficiency. assessments is required. The rationale is to make existing staff more productive and to enable them to focus on higher-value activities. This technical note draws from a wide set of regulatory Repetitive or time-consuming tasks such as data cleaning experiences to showcase new suptech solutions spe- or document, data, or complaints intake and process- cific to market conduct supervision. The main objective ing are prime candidates for suptech automation. From of this note is to assist market conduct authorities, partic- an initial focus of operational efficiency, some market ularly those in low- and middle-income countries, to build conduct supervisors have since expanded their overall and enhance supervisory capacity and efficiency by pro- approach to include enhancing the effectiveness of their viding concrete examples where supervisory technology supervisory program. can be leveraged. 1. Solution is used in this note to refer to an implementation of people, processes, information, and technology that supports a set of business or technical capabilities that solve one or more business problems. 1
2 The Next Wave of Suptech Innovation INSIGHT 2: Suptech solutions for market conduct super- insights in seconds where previously it would have vision can be grouped into four categories. taken supervisors weeks (if even possible at all). Given the more qualitative nature of market conduct super- This technical note explores 18 suptech solutions for vision, advancements in the analysis of text present a market conduct, grouped into the following four cate- potentially significant breakthrough. gories. These categories generally align with their respec- tive supervisory activity, rather than groupings based on In each of the above categories, the suptech solutions technological functionality (which is another approach for described span the data life cycle of a specific supervi- categorizing suptech solutions). sory activity. The solutions within each category present a collection of tools that enable supervisors to collect new 1. S olutions for regulatory reporting by supervised forms of data or introduce new, more efficient methods for institutions: A primary method for regulators to iden- collecting such data. Suptech solutions can also be used tify market conduct risks and issues is to collect infor- to conduct richer analyses on an exponentially increasing mation directly from supervised institutions, but doing amount of information with limited analytical resources. this can be time consuming and labor intensive. Web These collections of suptech solutions therefore provide portals, application programming interfaces (APIs), market conduct supervisors with both gains in efficiency automated dataflows (ADFs), and comprehensive and the ability to extract new insights to allow for data- supervision information systems (SISs) allow for auto- driven decision making. mated and standardized regulatory reporting that col- lects, validates, transforms, and stores data in real time. INSIGHT 3: Suptech implementation is about more than just the technology. 2. S olutions for collection and processing of com- plaints data: Complaints data is one of the most val- Embedding modern technology and data into the ued data sources for market conduct supervisors. A supervisory process is often an ongoing effort. Imple- complaints management system (CMS) is key to the menting suptech solutions requires more than just the efficient processing of these complaints and capturing solution. It requires making investments in three key and managing data to maximize its accuracy and value enablers: people, process, and IT infrastructure. The for supervisory purposes. The application of advanced culmination of broader efforts to implement suptech analytics to complaints data, particularly to unstruc- solutions and underlying enablers is organizational trans- tured text, represents the next step for market conduct formation into a data-driven supervisor. supervisors to deduce new insights in a more efficient • People refers to the talent, mindset, and skills of manner from complaints data. employees and the larger organizational culture toward data and technology. 3. S olutions for non-traditional market monitoring: The internet provides the opportunity to utilize a • Process refers to how suptech ideas are supported range of new, non-traditional methods for monitoring from ideation to implementation, including how supt- the market, another core activity for market conduct ech is championed and governed. supervision. Monitoring social media, online news, • IT Infrastructure refers to the underlying IT infrastruc- websites, and so on can provide early warning signals ture and capabilities needed to develop and operate of emerging consumer risks. Foundational to these suptech solutions internally. types of solutions is web scraping, which provides the mechanism for collecting and gathering online text for INSIGHT 4: Various strategies can be used to help accel- analysis. Such text can be used for social media mon- erate the development and implementation of suptech itoring, reputational analysis in the news, consumer solutions. sentiment scoring, and dark web monitoring. Non-tra- ditional market monitoring provides supervisors a use- Some financial authorities have benefited from the ful complement to traditional market monitoring. creation of formal, multiyear suptech or data strate- gies. Innovation offices can also be leveraged to provide 4. S olutions for document and business analysis: a central place to encourage internal suptech ideation Advances in analytics have been most profound in and learning, as well as improving dialogue with such the realm of unstructured text data. For example, nat- external parties as fintechs or potential suptech solution ural language processing (NLP) solutions can ingest providers. and analyze large quantities of documents, extracting
The Next Wave of Suptech Innovation 3 FIGURE 1. Suptech Solutions for Market Conduct Supervision and Key Enablers for Implementation CATEGORIES Collection and Non-traditional Document Regulatory OF SUPTECH Processing of Market and Business Reporting SOLUTIONS Complaints Data Monitoring Analysis • Supervision • Complaints • Web scraping • Document analysis for information systems management • Social media regulatory compliance EXAMPLES • Automated data system monitoring • Document analysis for OF SUPTECH submission via API • Analysis of examination of FSPs SOLUTIONS • Consumer • Web portal data unstructured sentiment • Document analysis for upload with central complaints data analysis peer group comparison database • Reputational • Validation of terms and analysis conditions • Dark web • Automated review of new monitoring provider registrations • Predictive modeling of financial statements • Business intelligence & geo-spatial analysis • Managed data platform People KEY ENABLERS FOR Process IMPLEMENTATION IT Infrastructure In some instances, it is more appropriate to begin The expansion of digital activity prompted by the with an incremental, targeted approach, rather than a COVID-19 pandemic reemphasizes the necessity and broader institutional strategy. Supervisors in low- and value of suptech for financial authorities. This is true for middle-income countries will inevitably face challenges all categories of suptech solutions for market conduct. during implementation. Common challenges include The direct and automated collection of granular regula- underdeveloped supervisory risk frameworks, staffing and tory data from supervised institutions is critical to replac- resource constraints, and technology constraints among ing on-site examinations, as is the ability of supervisors to financial service providers (FSPs). However, successful engage directly with consumers and manage their com- implementation of suptech solutions in these contexts plaints with providers digitally. Meanwhile, both non-tradi- can provide more meaningful gains to efficiency and tional market monitoring and advanced text analysis allow effectiveness in low-capacity countries. These constraints supervisors to monitor fast-moving sentiment remotely favor a targeted approach to suptech implementation and emerging risks to consumers on a more rapid basis. that focuses scarce time, attention, and resources. Such tools that enable supervisors to oversee the Utilizing experimentation and iteration in the financial sector with increased effectiveness and effi- technology-development process can be beneficial. ciency will only become more critical as digital trans- In place of traditional approaches such as “waterfall,”2 formation continues. The initial successes experienced authorities now increasingly use design or tech sprints, by the authorities referenced in this technical note offer a proofs of concept, prototypes, pilots, “minimum via- glimpse of this future—one in which data and technology ble products,” and agile approaches. Such approaches become core to the operations, identity, and culture of all engage and validate capabilities with end users, both supervisors. Such tools hold the promise to help empower ensuring the utility of the solution when delivered and financial authorities to meet the market conduct supervi- condensing the implementation timeline. sory challenges of the next decade. 2. Waterfall software development methodology refers to a linear, sequential approach whereby customer and business requirements are gathered at the beginning of the project and the technology solution is developed following a sequential project plan to accommodate those requirements.
1. INTRODUCTION Financial sector authorities around the world are expe- A new generation of more advanced suptech solutions riencing a profound shift to data-driven supervision is currently emerging, driven by the latest technological enabled by robust technology and data solutions. While innovations in big data architecture, machine learning technology is obviously not new to financial authorities, (especially NLP), and automated data collection and man- this new wave of digital solutions holds the promise to agement. In this note, the term suptech refers to the use increase the efficiency and effectiveness of supervision in of technology to facilitate and enhance supervisory pro- order to meet key regulatory objectives, including finan- cesses from the perspective of supervisory authorities. cial stability, financial integrity, and, increasingly, financial consumer protection. This technical note showcases new While technology solutions are not new to financial supervisory technology, or suptech, solutions specific to oversight, their specific application to market conduct market conduct supervision that can assist financial sector is a newer and welcome trend. Historically, technol- authorities—including in low- and middle-income coun- ogy solutions for quantitative analysis have been more tries—to enhance and strengthen financial consumer pro- advanced than qualitative ones, with greater application tection and market conduct supervision. for prudential supervision. Recent advancements in data and technology, such as NLP and other machine-learning While regulators have always leveraged data and tech- applications, present new opportunities for market con- nology for supervisory purposes, a marked increase in duct supervisors by enabling greater qualitative analyses. new and ambitious initiatives has occurred in recent As highlighted in the World Bank’s previous discussion years. Examples include the introduction of “TechSprints” note on suptech for market conduct supervision (World at the Financial Conduct Authority (FCA) in the United Bank 2018), examples of suptech for market conduct Kingdom, development of the Electronic Data Ware- supervision were initially limited to complaints data collec- house (EDW) at the National Bank of Rwanda (BNR), and tion and analyses. In the past few years, the application of the launch of “Step 1” technology transformation at the suptech for purposes of market conduct supervision has Authority for the Financial Markets (AFM) in the Nether- become more widespread and sophisticated, as explored lands,3 among many other technological developments at in this note. financial authorities worldwide. Suptech solutions are increasingly critical given the This latest wave of new suptech solutions builds on digital transformation of the financial services industry earlier generations of technology solutions. Most in recent years. Supervisors have often lagged behind in supervisory technology to date has focused primarily on their capacity to monitor these growing and increasingly data-management workflows and descriptive analytics. complex markets. However, supervisors can leverage the However, many of these solutions involve a certain degree technological advances behind digital transformation to of manual processing or had other limitations (BIS 2019). overcome resource constraints and make processes and 3. AFM (Netherlands) developed a multiyear, three-phase suptech transformation program: Build, Pilot, and Transform. The “Build” phase began with an assessment of AFM’s own data and analytics capacity. 4
The Next Wave of Suptech Innovation 5 procedures more effective and efficient. In the face of lim- for market conduct supervision, and (2) practical consid- ited capacity and resources, a particular concern in low- erations for successful implementation of a data-driven er-income economies, suptech can be used to leverage supervision program, such as investments and organiza- data and technology to supervise financial services more tional changes required to support implementation. efficiently and effectively for market conduct. The main audience for this note is market conduct While adoption has been most pronounced in high- authorities and other stakeholders in low- and mid- income countries, suptech solutions are relevant and dle-income countries. Considering that the potential for translatable to lower-capacity countries. The uneven gains in supervisory efficiency and effectiveness is high global uptake of suptech solutions can be partly attributed in lower-capacity countries, this note highlights solutions to the additional logistical barriers that supervisors in low- that can be adapted to these contexts and practical con- and middle-income countries often face. However, the siderations in doing so. In addition, the note should bene- broadening landscape of suptech solutions presents such fit development practitioners assisting financial authorities authorities with the opportunity to learn from technology by informing the development and design of technology examples in other countries. Many of these examples of support programs. technology and data solutions can still be translated and adapted to countries with lower capacity, where their Information Sources potential for positive impacts on supervisory efficiency and effectiveness may be even more powerful. This note draws from a wide set of regulatory expe- riences and is the result of primary and secondary research with 14 financial authorities. These financial Research Objectives and Key Audience authorities represent a diverse cross-section with var- The main objective of this note is to assist market con- ied levels of financial market development and internal duct authorities in their efforts to build and enhance capacity. Each authority was selected on account of its supervisory capacity and efficiency by providing con- successful track record in developing suptech solutions for crete examples of situations in which supervisory tech- market conduct supervision. Research methods included nology can be leveraged. An efficient market conduct interviews, demonstrations, questionnaires, and reviews supervision framework requires the collection of a wide of internal materials, external publications, and public-fac- range of data from disparate sources; doing this is chal- ing websites. lenging in many jurisdictions. Market conduct supervi- sors must also undertake complex qualitative analyses to The following financial authorities contributed critical determine compliance with legislation or regulation that is inputs to this note: often principles-based or composed of judgement-based • Australian Securities and Investments Commission rules. These challenges are compounded when supervi- • Authority for the Financial Markets (Netherlands) sors have under their jurisdiction a large diverse range of • Autorité des Marchés Financiers (Québec, Canada) FSPs with unique or unfamiliar risk profiles. Consequently, • Banco de Portugal market conduct supervision continues to be manual and • Bangko Sentral ng Pilipinas (Philippines) labor-intensive in many countries. Suptech presents the • Bank of England opportunity to enhance both supervisory capacity and • Bank of Lithuania efficiency to tackle these inherent operational challenges, • Central Bank of Brazil particularly important in light of growing and rapidly digi- • Central Bank of Ireland tizing financial markets. • Consumer Financial Protection Bureau (United States) • European Insurance and Occupational Pensions While collective knowledge on suptech has grown in Authority recent years,4 the literature specific to market conduct • Financial Conduct Authority (United Kingdom) supervision is limited. This note seeks to address this • National Bank of Rwanda gap by providing financial authorities with (1) an array of • Nepal Rastra Bank5 concrete examples of suptech solutions that can be used 4. Since the World Bank published its note on suptech for market conduct supervision (World Bank 2018), organizations such as the Bank of Inter- national Settlements, International Financial Consumer Protection Organization, Toronto Center, Milken Institute, R2A, Consultative Group to Assist the Poor, Columbia University, and others have published on suptech. 5. The Central Bank of Brazil, Bank of Lithuania, and Consumer Financial Protection Bureau (United States) contributed to the 2018 World Bank discussion note on suptech (World Bank 2018).
6 The Next Wave of Suptech Innovation Structure of Technical Note CHAPTER 4: People, Process, and IT Infrastructure: Three Key Enablers for Suptech Implementation. The technical note is structured into the following Successful implementation of a suptech solution goes chapters: beyond the technology itself. Three suptech enablers are critical for implementation: (1) people, (2) process, and (3) CHAPTER 2: Categories of Suptech Solutions for Mar- underlying IT infrastructure. ket Conduct Supervision. Four main categories of supt- ech solutions are introduced: (1) solutions for regulatory CHAPTER 5: Implementation Considerations. Common reporting by supervised institutions, (2) solutions for col- considerations when implementing suptech solutions lection and processing of complaints data, (3) solutions emerged across country examples. Authorities often for non-traditional market monitoring, and (4) solutions face key decisions related to prioritization, determining for document and business analysis, especially of unstruc- whether to build a solution in-house or to buy from a ven- tured data. dor, and deciding how to organize data and technology staff. It is also useful to consider whether to undertake CHAPTER 3: Suptech Solutions for Market Conduct efforts to accelerate suptech adoption through formal Supervision. Individual suptech solutions for market con- suptech or data strategies, adaptive technology develop- duct are identified for each of the four main categories ment, and internal innovation offices to liaise with external noted above, and a total of 18 solutions are presented. stakeholders. For each solution, there is a description of how the solu- tion works, its benefits, and considerations for implemen- CHAPTER 6: Looking Forward. This section includes brief tation, drawing from country experience and including final thoughts on the value of suptech solutions for market detailed case studies. conduct supervisors operating in an increasingly complex environment. FIGURE 2. Suptech Solutions for Market Conduct Supervision and Key Enablers for Implementation CATEGORIES Collection and Non-traditional Document Regulatory OF SUPTECH Processing of Market and Business Reporting SOLUTIONS Complaints Data Monitoring Analysis • Supervision • Complaints • Web scraping • Document analysis for information systems management • Social media regulatory compliance EXAMPLES • Automated data system monitoring • Document analysis for OF SUPTECH submission via API • Analysis of examination of FSPs SOLUTIONS • Consumer • Web portal data unstructured sentiment • Document analysis for upload with central complaints data analysis peer group comparison database • Reputational • Validation of terms and analysis conditions • Dark web • Automated review of new monitoring provider registrations • Predictive modeling of financial statements • Business intelligence & geo-spatial analysis • Managed data platform People KEY ENABLERS FOR Process IMPLEMENTATION IT Infrastructure
The Next Wave of Suptech Innovation 7 2. C ATEGORIES OF SUPTECH The four main categories of suptech solutions for mar- ket conduct supervision are as follows: SOLUTIONS FOR MARKET CONDUCT SUPERVISION 1. Solutions for regulatory reporting by supervised insti- tutions No taxonomy of suptech solutions is widely accepted 2. Solutions for the collection and processing of com- globally. To date, most existing taxonomies have taken a plaints data function-based approach toward describing suptech eco- systems (see Figure 3). Existing suptech taxonomies tend 3. Solutions for non-traditional market monitoring to categorize suptech solutions based on the flow of data 4. Solutions for document and business analysis from collection to validation, consolidation, and analysis. This technical note takes a slightly different approach, 1. Solutions for regulatory reporting by supervised categorizing suptech solutions for market conduct institutions supervision by supervisory activity. Unlike the other tax- A primary method for regulators to identify market con- onomies of suptech solutions, the categories employed duct risks and issues is to collect information directly from in this note extend beyond dataflow to include engaging supervised institutions. Historically, such submissions have with supervised institutions and consumers as well as new been collected manually through reporting templates types of non-traditional data collection and analysis. This submitted by mail, email, or fax, resulting in a slower, inef- categorization is not meant to be exhaustive for all possi- ficient, and more error-prone process. ble suptech solutions for market conduct but reflective of the solutions described in this note. FIGURE 3. A Function-Based Suptech Taxonomy with Suptech Use Cases Mac ro-p n rud sio ervi en tia p su Detection of Early warning l su FT networks indicators pe /C Stress testing L rv AM isi Risk scoring Network Forecasting on Big Data analysis AI/ML Market NLP surveillance AML NLP compliance Policy assessment Big Data GIS evaluations DATA Credit risk Big Data Text Electronic mining record AI/ML keeping Liquidity risk NLP NLP Dynamic Electronic Governance risk visualization document on management Centralized isi Cyber risk repositories v er Li up ce Automated data ns ls Case management tia reporting ing en prud o- Micr Supervision phases Use cases Technologies Source: World Bank (2020).
8 The Next Wave of Suptech Innovation Today, web portals, APIs, ADFs, and comprehensive 3. Solutions for non-traditional market monitoring SIS allow for automated and standardized regulatory The internet provides the opportunity to utilize a range of reporting that collects, validates, transforms, and stores new, non-traditional methods for conducting market mon- data in real time. The most sophisticated solutions rely itoring, another core activity for market conduct supervi- on machine-readable taxonomies, customer relationship sion. Monitoring social media, online news, websites, and management (CRM) systems, and data warehousing with so on can provide early warning signals of emerging con- permission-based datamarts. However, a solution need sumer and reputational risks. By keeping a pulse on con- not be overly complex to deliver immense regulatory ben- sumer sentiment in social media and web forums, these efits for market conduct supervisors, including enhanced solutions provide the potential for more uninhibited, real- efficiency and increased analytical capability. Further, time access to the “voice of the consumer” and consum- applying automated data analytics allows market con- ers’ experiences with FSPs. Overall, these web monitoring duct supervisors to support their supervisory framework solutions provide a useful, low-cost complement to tra- and prioritize scarce supervisory resources toward areas ditional market monitoring to gather regulatory insights. of greatest risk. Solutions for non-traditional market monitoring include Suptech solutions for regulatory reporting include the fol- the following: lowing: • Web scraping • SIS6 • Social media monitoring • Automated data submission via API • Consumer sentiment analysis • Web portal data upload with central database • Reputational analysis • Dark web monitoring 2. S olutions for the collection and processing of complaints data 4. Solutions for document and business analysis Complaints data is one of the most valued data sources for market conduct supervisors. Suptech solutions in Advances in analytics have been most profound in the complaints handling alleviate the operational burden realm of unstructured text data. For example, NLP solu- through greater automation. Such solutions can also tions can ingest and analyze large quantities of docu- introduce new front-end digital channels to engage with ments, extracting insights in seconds where previously it consumers regarding their complaints and inquiries, would have taken supervisors weeks (if even possible at such as via websites, mobile apps, text messaging, and all). Given the more qualitative nature of market conduct chatbots. After initial setup, digital channels tend to be supervision, advancements in the analysis of text present lower in cost to operate, expanding regulators’ reach a potentially significant breakthrough. beyond urban areas. In addition, such solutions enhance the quality of the information collected about consumer Suptech solutions for analysis also leverage automation complaints. Advancements in database management and combine data sets together to produce a more holis- and analysis allow for supervisors to extract more under- tic view. Some suptech tools also bring in new types of standing and insight from consumer-submitted com- external data sets that were traditionally difficult to com- plaints via CMSs, providing a critical resource for market bine for analysis, such as geospatial data. Solutions for conduct supervision. advanced analytics provide market conduct supervisors with both significant gains in efficiency and the ability to Solutions for the collection and processing of consumer extract new insights from data to allow for data-driven data include the following: decision making. • CMS7 • Analysis of unstructured complaints data 6. Solutions for regulatory reporting also include machine-readable taxonomies, data validation systems, and ad hoc transmission systems. 7. These solutions often include both case management interfaces for supervisory staff and digital user interfaces for consumers.
The Next Wave of Suptech Innovation 9 FIGURE 4: Results Framework for Market Conduct Suptech Solutions Potential Suptech use cases Automated data Advanced data validation, Platform and Data management collection processes analysis, visualization database integration and storage (use of data-pull or (cleaning and analysis (examiner dashboards, (use of cloud computing data-input systems; of unstructured data; workflow tools, merging to store big data) machine readable and identification of spikes disparate data sets) executable regulation) and trends) Potential Suptech supervisor-level outcomes Improved scope, Enabling/enhancing More efficient use More efficient information accuracy, consistency, risk-based supervision of resources flows between providers and timeliness of (better identification and (reallocation of staff away and supervisors, between collected information measurement of risk) from manual tasks) consumers and supervisors, and across supervisors Potential Suptech impacts Larger share of financial Improved consumer Improved conduct Better value for limited sector under outcomes (better of providers government resources supervision protection, increased confidence in market) Solutions for document and business analysis include the The four main categories of suptech solutions for mar- following: ket conduct supervision represent an update from the • Document analysis for regulatory compliance Suptech Conceptual Framework first introduced in the 2018 World Bank discussion note (World Bank 2018). • Document analysis for examination of FSPs As noted above, these suptech solutions drive both effi- • Document analysis for peer group comparison ciency and effectiveness at the supervisor level and ulti- • Validation of terms and conditions mately lead to potential beneficial impacts in the broader • Automated review of new provider registrations market, such as via improved consumer outcomes. • Predictive modeling of financial statements • Business intelligence and geospatial analysis • Managed data platform
10 The Next Wave of Suptech Innovation 3. SUPTECH SOLUTIONS FOR to analyze text and speech data. This includes the ability to infer topics in text, classify and categorize documents, MARKET CONDUCT SUPERVISION and measure other text characteristics, such as sentiment. Common types of NLP algorithms found within suptech Within the four main categories of suptech solutions solutions include topic modeling, sentiment analysis, and for market conduct supervision, 18 individual solutions text summarization. NLP has the advantage of being rep- are described in this chapter. These suptech solutions licable, systematic, and more transparent, but challenges are currently operational, in pilot, or were expected to be remain. NLP requires continuous fine-tuning and interpre- operational in 2020. For each solution, information is pro- tation for its outputs to be accurate and regularly usable. vided on what the solution is, the benefits it provides, and considerations for implementing the solution. Solutions are accompanied by country examples and select case studies. 3.1. Regulatory Reporting Data and reports submitted by supervised institutions are It is worth noting that suptech solutions need not among the sources of information used most widely by always be particularly “high-tech” or the most complex market conduct supervisors to inform supervisory activi- to have real, significant supervisory benefits. The com- ties. In addition to market conduct, financial authorities plexity of suptech solutions varies within each category. regularly use technology solutions for regulatory report- What this means practically for financial authorities, espe- ing to support prudential, financial inclusion, or other cially in low- or middle-income countries, is that authorities goals. Solutions for regulatory reporting vary in their level have options. Financial authorities can focus on the solu- of complexity and are presented here beginning from the tion(s) that best matches their needs, available resources, most complex (3.1.1 “Supervision Information Systems”) and existing capabilities. Figure 5 summarizes the level of to less complex (3.1.2 “Automated Data Submission via implementation complexity across solutions. Supervisors API”) to least complex (3.1.3 “Web Portal Data Upload in lower-capacity countries evaluating potential solutions with Central Database”). from this list should first consider adding capabilities in a category(s) for which the authority does not currently 3.1.1 Supervision Information Systems have a solution. Once the authority has baseline capabil- SIS represent a comprehensive IT upgrade to the collec- ities within a category, authorities can opportunistically tion, validation, and analytics of reported information from enhance their capabilities by implementing more sophisti- supervised institutions. While the exact technical deploy- cated solutions, depending on supervisory need and avail- ment can vary among authorities, SIS solutions share the able resources. As with any investment, authorities should following technical elements: ADFs to retrieve data from evaluate the solution’s business case in context of supervi- supervised institutions; a central data warehouse with a sory goals and available resources. CRM system to store, manage, and secure documents and data; “datamarts” to facilitate permission-based access to Solutions within each category are interrelated and different teams and departments within the authority; and complementary. When viewed together, suptech solu- business intelligence (BI) tools that equip supervisory staff tions within each category span the data life cycle related to analyze and monitor data for trends and risks. to the specified supervisory activity. Individual solutions may allow authorities to collect new forms of data, intro- The solution’s high complexity requires a significant duce new methods for its collection, or conduct new or investment of organizational time and resources. This richer analyses of this information. This is particularly true often includes external consultants and software vendors, as it relates to new types of analytics, whose functionality in addition to in-house technology staff. Involvement of is common across all four categories of suptech solutions supervisory staff is also crucial to ensure the solution is but can be employed to serve specific supervisory use designed appropriately to support an authority’s specific cases requiring domain expertise. supervisory framework. This includes considering defini- tions of standards and reporting guidelines to supervised In particular, the latest wave of advanced analytical entities and the solution’s data validations. solutions in multiple categories is enabled by NLP. NLP refers broadly to the ability of computers and algorithms
The Next Wave of Suptech Innovation 11 FIGURE 5: Overview of Suptech Solutions for Market Conduct Supervision SUPERVISOR IMPLEMENTATION CATEGORY SOLUTION DESCRIPTION EXAMPLES COMPLEXITY & COST8 3.1 Regulatory 3.1.1 Supervision information Comprehensive IT upgrade to the BNR, AMF Most sophisticated Reporting systems (SIS) collection, submission, and analytics of FSP reported data 3.1.2 Automated data submission FSPs prepare database extracts and share BSP Moderate sophistication via API data via consolidated API transmission 3.1.3 Web portal data upload with Low-complexity data sharing solution to NRB Foundational capability, central database replace manual data sharing over email, inexpensive fax, or not at all. 3.2 Collection & 3.2.1 Complaints management Automates complaints handling BOL, CFPB, Moderate sophistication Processing of systems (CMS) processes, improves data quality, BSP Complaints and introduces digital interfaces for Data consumers and case workers 3.2.2 Analysis of unstructured Identifies topic, sentiment, and thematic FSD Kenya Inexpensive, but requires complaints data patterns in consumer complaint text analytics staff 3.3 Non-traditional 3.3.1 Web scraping Gathers text data from online sources FCA, AMF, Foundational capability, Market (e.g., FSP website, social media, web CBI inexpensive Monitoring forms, blogs, news) 3.3.2 Social media monitoring Topical analysis of consumer posts on FCA, AMF, Inexpensive, but requires social media related to FSPs or financial CBI, EIOPA analytics staff products 3.3.3 Consumer sentiment analysis Analysis of consumers’ tone and emotions BOE, AMF, Inexpensive, but requires in their interactions with FSPs online CBI analytics staff 3.3.4 Reputational analysis Analysis of news media’s view of specified AMF Inexpensive, but requires FSPs analytics staff 3.3.5 Dark web monitoring Identify fraud, scam, etc. risks on the BOE Moderate dark web sophistication 3.4 Document 3.4.1 Document analysis for Inspects FSP-provided documents to FCA Inexpensive, but requires and Business regulatory compliance determine compliance with specified analytics staff Analysis regulations 3.4.2 Document analysis for Topical analysis of FSP-provided AMF Inexpensive, but requires examination of FSPs documents to scope and support analytics staff supervisory examinations 3.4.3 Document analysis for peer Analysis of FSP-provided documents to BOE Inexpensive, but requires group comparison spot risks and trends across a peer group analytics staff 3.4.4 Validation of terms and Automation of the review of product BdP Inexpensive, but requires conditions terms and conditions to identify analytics staff compliance risks 3.4.5 Automated review of new Evaluates and identifies new provider or AFM Inexpensive, but requires provider registrations product registrations that are higher-risk analytics staff 3.4.6 Predictive modeling of Evaluates financial statements for AFM Inexpensive, but requires financial statements misstatement or other risks analytics staff 3.4.7 Business intelligence (BI) & Supports analysis and interpretation AMF, BOE, Ranges from low to high geo-spatial analysis of data, often a complement to other FCA, NRB, complexity suptech solutions AFM 3.4.8 Managed data platform Standardizes, centralizes, and makes AFM Most sophisticated accessible internal data from a multitude of sources 8. Implementation costs are from the authors’ interpretation of anecdotal information.
12 The Next Wave of Suptech Innovation The solution’s benefits can be substantial. BNR designed a direct connection to the IT systems of supervised insti- its solution, called the Electronic Data Warehouse (EDW), tutions or, more commonly, through “middleware” that to centralize data from across the authority into a single serves as an intermediary between the SIS and the IT internal data store for comprehensive analysis, including systems of supervised institutions. An advantage of mid- data from the national payments system, credit refer- dleware is its interoperability with the various types of ence bureaus, and the statistics department. Autorité des databases used by supervised institutions (for example, Marchés Financiers (AMF) in Québec, Canada designed Oracle, SQL, MySQL, and so on). This interoperability its solution to serve as an Offsite Supervision System allows supervised institutions to continue to use their which streamlines many of the operational, cybersecurity, same provider and connect via the middleware using sim- and data integrity challenges associated with collecting ple data-transfer protocols. The middleware also adapts granular data from supervised institutions. Such granu- data from different types of databases into a common lar data is typically contained in requests for supervisory readable format for the SIS. Finally, the middleware also information. Like BNR, AMF’s solution also centralizes and provides supervised institutions with a buffer, as the SIS compiles data sets from across the authority to create a accesses only data that the supervised institution inten- richer, more holistic view to generate insights for data- tionally makes accessible. In this way, SIS solutions using driven decision making. The supervisory infrastructure to middleware do not require access to the full database or conduct off-site examinations has become increasingly core banking systems of supervised institutions. important in 2020, as the logistics of on-site examinations are made more complex (or infeasible) due to the COVID- Data analytics and reporting through datamarts 19 pandemic. While central warehouses and CRM systems store, man- age, and protect the data retrieved from supervised insti- Pulling data directly from supervised institutions tutions, datamarts are used by supervisory staff to access An innovation of SIS solutions, ADFs allow supervisors to and analyze the data. Datamarts are typically user-permis- “pull” data directly from supervised institutions, rather sioned and facilitate access to the subsets of data within than having supervised institutions “push” data to the the central repository deemed appropriate based on job authority. This data pull can be facilitated either through role, function, department, or other distinction of the user CASE STUDY 1 How BNR Designed Its SIS Solution BNR’s EDW is an end-to-end regulatory reporting data plat- system, credit reference bureaus, and the statistics department, form with both prudential and market conduct applications. among others. It was the culmination of a three-year IT effort from proof of The EDW imposed relatively little additional burden on FSPs. concept to deployment and cost approximately USD 1M to This is a result of its technical design for software interoperabil- implement. It overhauled previous data-management sys- ity. FSPs can continue using the same database provider (for tems, requiring investments not only in hardware and software example, Oracle, SQL, MySQL, and so on) and connect to the at BNR but also (and more importantly) in upgrading staff skills EDW using simple data-transfer protocols. Further, manage- and coordination among the more than 600 institutions that ment at BNR reports that frequent engagement with FSPs, par- it supervises. ticularly relating to providers’ concerns about the level, nature, The EDW solution introduced three new dimensions to and frequency of supervisor’s access to their data, was key to its BNR’s regulatory reporting infrastructure: (i) data-pull tech- ultimate widespread adoption. nology that allows supervisors to connect directly to the Throughout the three-year initiative, management at BNR databases of FSPs and collect data from the source, rather indicated the importance of managing change within the finan- than sharing data via Excel spreadsheets; (ii) the collection of cial authority. Supervisory staff accustomed to BNR’s data-man- account-level data that provides more granular data, provided agement processes initially met the changes introduced by the daily, rather than aggregated by institution on a monthly or EDW with skepticism. Staff who performed manual data-cleaning quarterly basis; and (iii) data analytics and reporting that are or data-consolidation processes had to learn new skills to interact now automated and linked to interactive dashboards. Within with the more sophisticated system. Many also were retrained to BNR, the EDW was also designed to break down internal data perform business analysis, focusing on the analysis and interpre- siloes. As a central data warehouse, it integrates with other tation of the data (with greater value-add) rather than on such internal data sources, such as data from the national payments mechanical processes as consolidation and cleaning.
The Next Wave of Suptech Innovation 13 FIGURE 6. Data Flow Diagram of SIS Solutions Data Collection & Validation Data Storage & Management Data Analysis & Reporting Sandbox Environment Supervised Institutions share data via automated data flows (ADFs), APIs, System performs Data consumer or other secured data validations and Enterprise Data Supervisors, risk transmission transformations Warehouse experts, and other The validated data is regulatory staff use archived and stored in the data and insights a central data warehouse Analysis Tools for oversight Additional datasets are Datamarts Dashboards, alerts, merged and test data is Datamarts manage statistical tables and available in the Sandbox permission-based graphs are created Environment access of data to to understand specific departments trends and risks or teams within the data Source: Figure adapted from materials provided by the Autorité des Marchés Financiers (Québec, Canada) requesting access. Datamart interfaces can also help users by institutions. Further, this data can be validated in real to link data sets together and produce automated reports. time, as upward of thousands of validation rules are run in parallel. Together, the process typically averages 10 In designing a SIS solution, supervisors should consider seconds per submission in the Philippines—a substantial the nature of their supervisory framework. How the data is improvement from the 30 minutes or more a submission collected and maintained over time will partly depend on via web portal upload might take for a supervisor to pro- whether the authority takes a risk-based or institution-type cess and validate (di Castri, Grasser, and Kulenkampff focus to oversight. 2020b). For supervisors, the solution reduces staff time spent on processing and managing data. This is especially 3.1.2 Automated Data Submission via API true of the time spent on cross-validations, which grows An API acts as a software intermediary that enables two or as the number of items requiring reconciliation grows with more systems to talk to each other. For regulatory report- every new report. ing, supervised institutions can prepare database extracts and share their data with supervisors via API transmission. This solution provides benefits for supervised institutions These data and report transmissions are most valuable in as well, reducing reporting burden and compliance costs. a machine-readable format to minimize the operational In the case of Bangko Sentral ng Pilipinas (BSP) in collabo- burden on supervisory authorities associated with manual ration with the RegTech for Regulators Accelerator (R2A),9 processing, data cleaning, and validation and making the the number of reporting fields required of FSPs was cut data readily available for market conduct analysis. in half, from 107,000 to 50,000, as duplicated or calcu- lation fields were eliminated. Further, this consolidation Direct machine-to-machine transmission via API has sev- allowed for the retirement of older reporting templates in eral benefits. The raw data extracted from supervised the move to automated database extracts (in XSD format). institutions’ core banking systems is converted into a single encrypted XML file that is pushed directly to the The desirability and feasibility of this solution is likely to vary supervisor. This single unified reporting scheme can among market conduct supervisors in low- and middle-in- replace dozens of previous reports submitted separately come economies. Countries with larger digital finance 9. The RegTech for Regulators Accelerator, launched with support from the Bill and Melinda Gates Foundation, the Omidyar Network, and USAID, partners with financial sector authorities and technology firms to accelerate innovation in financial sector supervision, regulation, and policy analysis. See https://www.r2accelerator.org/about.
You can also read