The Next Wave of Suptech Innovation - Suptech Solutions for Market Conduct Supervision - World Bank Documents
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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 NOTEFinance, 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
iii 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 33ACKNOWLEDGMENTS
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.
iiiACRONYMS 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
ivEXECUTIVE 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.
12 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, extractingThe 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 InfrastructureThe 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 platform10 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 algorithmsThe 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
