WORKING PAPER

Supply-Side GenderDisaggregated Data
for Advancing
Financial Inclusion
Insights and Areas for Further Research
February 2024 • Tatiana Alonso, Diana Dezso

Acknowledgments

Rights and Permissions

Special thanks go to Yasmin Bin Humam, Juan Carlos
Izaguirre, Denise Dias, Simrin Makhija, Aveesha Singh,
and Olga Tomilova (all CGAP). Thanks go to Luis
Treviño Garza (Alliance for Financial Inclusion) and
Kelsey Ross (Data 2X) for their thorough comments
and contributions to enhance the quality of the paper.
Our deepest gratitude also goes to the reviewersof CGAP’s supply-side gender-disaggregated data
project’s strategy and knowledge products for theiralways constructive and collegial feedback: Buddy
Buruku (the World Bank), José Félix Etchegoyen(International Finance Corporation), María Fernandez
Vidal (CGAP), Estelle Lahaye (CGAP), Peter
McConaghy (Office of the United Nations SecretaryGeneral’s Special Advocate for Inclusive Finance forDevelopment), and Stefan Staschen (CGAP). The
authors would also like to thank Sylvie Bossoutrot,
Gerhard Coetzee, and Michael Tarazi (all CGAP) for
their insightful guidance throughout the process.

This work is available under the Creative Commons
Attribution 4.0 International Public License (https://creativecommons.org/licenses/by/4.0/). Under theCreative Commons Attribution license, you are free
to copy, distribute, transmit, and adapt this work,
including for commercial purposes, under the following
conditions:

CGAP
1818 H Street, NW, MSN F3K-306
Washington, DC 20433
Internet: www.cgap.org
Email: cgap@worldbank.org
Telephone: +1 202 473 9594
Cover photo by Beauttah Wandera.
© CGAP/World Bank, 2024.

Attribution—Cite the work as follows: Alonso, Tatiana, andDiana Dezso. 2023. “Supply-Side Gender-Disaggregated
Data for Advancing Financial Inclusion: Insights andAreas for Further Research.” Working Paper. Washington,
D.C.: CGAP. https://www.cgap.org/research/publication/
supply-side-gender-disaggregated-data-for-advancingfinancial-inclusion
Translations—If you create a translation of this work, add
the following disclaimer along with the attribution: Thistranslation was not created by CGAP/World Bank andshould not be considered an official translation. CGAP/World Bank shall not be liable for any content or error inthis translation.
Adaptations—If you create an adaptation of this work,
please add the following disclaimer along with theattribution: This is an adaptation of an original work by
CGAP/World Bank. Views and opinions expressed in
the adaptation are the sole responsibility of the author
or authors of the adaptation and are not endorsed by
CGAP/World Bank.
All queries on rights and licenses should be addressed
to CGAP Publications, 1818 H Street, NW, MSN
F3K-306, Washington, DC 20433 USA; e-mail: cgap@
worldbank.org.

Contents

Executive Summary

3

SECTION 1: Introduction

7

SECTION 2: Gender-Disaggregated Data in the Financial Sector:

Concept Mapping and Building Blocks
SECTION 3: Key Lessons from Supply-Side Gender-Disaggregated Data Initiatives

11
14

3 .1: What drives countries to collect and use S-GDD?

14

3 . 2: How do countries collect S-GDD, and what data do they collect?

16

3 .3: How are countries using the S-GDD they collect, and what challenges

are they encountering?

18

SECTION 4: The Way Forward to Unlock S-GDD Potential

22

APPENDIX: Financial Gender Data Initiatives Reviewed for this Paper

27

References35

Acronyms
ADB

Asian Development Bank

AfDB

African Development Bank Group

AFI

Alliance for Financial Inclusion

BIS

Bank for International Settlements

CMF

Comisión para el Mercado Financiero

D-GDD

Demand-Side Gender-Disaggregated Data

EBRD

European Bank for Reconstruction and Development

ESG

Environmental, Social and Governance

FAS

Financial Access Survey

FAW

Financial Alliance for WomenFI

Financial Inclusion

FSAP

Financial Sector Assessment Program

FSP

Financial Service Provider

FICP

Financial Inclusion and Consumer Protection

FMBBVABBVA Microfinance Foundation

GDD

Gender Disaggregated Data

GPFI

Global Partnership for Financial Inclusion

GPSS

World Bank Global Payment Systems Survey

GSMA

Global System for Mobile Association

IADB

Interamerican Development BankIDAInternational Development Association

IDB

Inter-American Development Bank

IFC

International Finance Corporation

IMF

International Monetary Fund

INFE

International Network on Financial Education

KYC

Know Your Customer

MDB

Multilateral Development BanksMSME

Micro, Small, and Medium Enterprises

NFIS

National Financial Inclusion Strategy

OECD

Organisation for Economic Co-operation and Development

SDD

Sex-Disaggregated Data

SDG

Sustainable Development Goals

S-GDD

Supply-Side Gender-Disaggregated Data

SIGI

Social Institutions and Gender Index

SME

Small and Medium Enterprises

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

1

ToC

Theory of Change

UNCDF

United Nations Capital Development FundUNSGSA

United Nations Secretary-General's Special Advocate for Inclusive Finance for Development

We-Fi

Women Entrepreneurs Finance Initiative

WEE

Women’s Economic Empowerment

WFI

Women’s Financial Inclusion

WFID

Women’s Financial Inclusion Data Partnership

WWB

Women’s World Banking

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

2Executive Summary1T

HE GENDER GAP IN FINANCIAL
inclusion continues to be unacceptably highin most developing countries, highlighting
the need to prioritize policies that promote gender
equity in the financial sector more effectively.
Policies must be informed by high-quality genderdisaggregated data (GDD) generated from both thedemand side and supply side of the market. Genderdata is also essential for financial service providers tounderstand the market opportunity for serving womenand to build strong business cases for designing
products and services tailored to women’s needs.
The financial inclusion community has supported
the gender data agenda since the early 2010s
through several global initiatives and countrylevel efforts.2 These efforts range from raisingawareness about the need for and potential benefitsof gender-disaggregated data in the financial sector,
documenting countries’ experiences in collecting
and using such data, developing gender data toolkits
for regulators, sharing lessons, and advocating forthe collection and use of gender data to promotewomen’s financial inclusion. While these initiatives havecontributed to a notable increase in the availability anduse of gender-disaggregated data, especially on the
demand side, significant gaps continue to exist in thegeneration and, especially, in the use of administrative(supply-side) data.

This paper examines these efforts, focusing on
supply-side gender-disaggregated data (S-GDD)
initiatives. It explores how S-GDD has been collected
and used, mainly by financial sector authorities
but also by providers, and the challenges andopportunities associated with this work. It highlights
lessons to date, identifies existing gaps, and proposes
next steps for future work to unlock S-GDD’s
potential to support women’s financial inclusion andeconomic empowerment.
The first key lesson is that there is no ideal or
standard set of best practices guiding countries
toward collecting and using S-GDD in the financial
sector. The research has revealed significant
differences across countries regarding the departure
point, the motivations and goals, and the approaches
used to collect and use the data.
• The motivations for each country to startcollecting and using S-GDD vary greatly. Several
countries were encouraged to capture S-GDD
by global initiatives targeting financial authorities(such as the International Monetary Fund’s Financial
Access Survey (FAS) and the Alliance for Financial
Inclusion’s Denarau Action Plan). In other cases, astrong culture of data-driven, evidence-based policy
making, as well as strong-willed and committed
gender data champions with influential roles in the1

All terms used in the paper are per the nomenclature of the source. Detailed definitions of terms used throughout the paper are included in
Section 2.

2

This includes key stakeholders such as the World Bank, the International Monetary Fund (IMF), the Alliance for Financial Inclusion (AFI),
Data2X, the Financial Alliance for Women (FAW), the Office of the United Nations Secretary-General’s Special Advocate for Inclusive Financefor Development (UNSGSA), and the Women Entrepreneurs Finance Initiative (We-Fi).

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion

3

financial sector, was critical to launching S-GDD
collection efforts (for example, Rwanda and Zambia).
In some countries, S-GDD efforts were promptedby the desire of policy makers and regulators toaddress financial gender gaps revealed by datafrom demand-side studies (for example, Nigeria and
Rwanda). The development of national strategies
with explicit targets to reduce gender gaps in thefinancial sector has also strongly incentivizedauthorities to start collecting S-GDD (for example,
Pakistan). In a few countries, broader nationallevel gender equality objectives trickled down to
the financial inclusion agendas and prompted thecollection of S-GDD in several sectors, including thefinancial sector (for example, Chile and Mexico).
• The gender variable can be generated byproviders at the onboarding (Know Your Customer(KYC)) stage, using an ID or similar identification
document when these exist, and reported to thesupervisor along with all relevant administrative
data. In many countries, S-GDD is collected byincluding a gender variable in the mandatory
regulatory reports, whether granular, aggregate,
or both. In a few cases, authorities have sought toengage providers to share S-GDD on an ad hoc
or voluntary basis (for example, Honduras and
Kenya). Where available, a national identification
system contributes significantly to the authorities’ability to disaggregate data by gender without
having to update financial reporting templates (forexample, Brazil, Chile, Costa Rica, Egypt, Malaysia,
and Rwanda). Some authorities collect granular
data from the supervisees (customer microdata),
whereas others request aggregate series (forexample, number of deposit accounts by gender).
When published, S-GDD is presented in aggregate
form (system level, by product, by financial service
provider (FSP)). Data collection for businessaccounts is mostly done for sole proprietorships
who run the business in their own names, rather
than including women-owned micro, small, andmedium enterprises (MSMEs).

• Authorities tend to collect S-GDD for retailaccounts, typically credit variables, given its
significant role in financial development andsupervision. S-GDD on credit may include thenumber of borrowers and accounts, the volume
of outstanding balances, and conditions (such as
price or collateral required). S-GDD on savings isoften limited to aggregate indicators of deposit
volume and number of accounts, mainly becauseof concerns regarding compliance with banking
secrecy laws that forbid providers to share individual
data for deposits other than at the account level.
At the global level, the International Monetary
Fund’s FAS has gathered S-GDD indicators from 83
countries, with ongoing efforts to expand country
and series coverage further.

There is no ideal or standard set of bestpractices guiding countries toward
collecting and using S-GDD in thefinancial sector.
• Some authorities use S-GDD to assess thefinancial gender gap, inform gender inclusion
or diversity strategies and policies, and monitor
progress. In countries with more experiencegathering S-GDD (such as Bangladesh, Chile,
Ecuador, India, México, Rwanda, and Zambia),
insights from data have been used to develop
gender-informed policies, guidance, and products(with different degrees of traction) and tounderstand gender gaps in financial inclusion
further. Some regulators have used the data
to produce publicly available data and mainly
reports to raise awareness, build capacity, andpromote collaboration and consultations among
key stakeholders (for example, Bangladesh, Chile,
Ecuador, Ghana, Honduras, Mexico, and Morocco).

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion

4

The second key lesson is that, despite considerable
progress in S-GDD availability, the collection anduse of S-GDD is suboptimal. This is due to low data
quality and suitability, lack of awareness, mandateor capacity, and data privacy concerns. The lack of
relevant public data generates a lack of awareness byboth authorities and providers about S-GDD’s potential.
On the other hand, the lack of awareness about thevalue of S-GDD and guidance to collect and use it
effectively minimizes the incentives or ability to do soin the first place.
• Inconsistencies, errors, and missing information.
There is consensus about the attributes that data,
including S-GDD, should have to be useful andimpactful (such as robustness, reliability, quality,
comparability, cost-effectiveness, and relevance)(World Bank 2021c). In many cases, these
conditions fail to prevail in existing schemes. Issues
mainly arise when:• Different supervisory authorities require S-GDD
using different KYC and standards (for example,
definitions for gender categories and types oftransactions), formats, or timelines.
• The gender field had not been traditionally
requested, and there is no identification system
to help update it.
• Data are gathered and processed manually(either by reporting entities or financial
authorities).
• Data are generated with errors by providers’staff due to issues such as lack of data skills andsiloed internal databases.
• There is a lack of understanding of the data
standards imposed by financial authorities, due
to issues such as a lack of detailed reporting
guidance.
• Data are submitted late or are incomplete.
• The gaps regarding the scope of available
S-GDD also pose serious limitations to providers’and authorities’ use. For example, gender-

disaggregated indicators for account dormancy,
loan delinquency rates, or credit conditions are
generally not requested by regulators. Still, suchinformation, when reported on a timely basis
and with standardized frequency, can help both
regulators and providers to better understand
how well products are used, identify risks andopportunities, and assess whether products areproviding value to customers. Also, the lack ofpublicly available industry or market-level S-GDD,
both at the individual and women-owned small
and medium enterprises (WSME) level, means thatproviders cannot see the full scope of women’s
activity in the financial system, which hampers
their ability to both identify pockets of risk and new
business opportunities in serving women. Finally, theuse of S-GDD by financial supervisors to monitor
and address market (mis)conduct putting at riskboth consumers and the system’s stability is almost
nonexistent despite the high vulnerability of womenand their key role in preserving financial resiliency at
the household level.
The final, and definitive, key lesson is that to unlock
the S-GDD potential to contribute to women’s
financial inclusion (WFI) and women’s economic
empowerment (WEE), a more systematic andcollaborative approach toward effective ways tocollect and use S-GDD is needed, in the form of
guidance. When powered by adequate incentives,
capacity, and collaboration, S-GDD frameworks candeliver the high-quality data required to assess the risks
and opportunities of targeting women and design astrategic response to the findings, be it at the funder,
policy, supervisory, or business levels. While there is noagreed definition of an “ideal” S-GDD framework, somefeatures stand out from the literature. These include
having champions, producing data with sufficientquality, embracing a customer-centric approach todesign and analyze data indicators, promoting data
sharing and collaboration across stakeholders, andseeking proportionality in the data requirements. Other
qualities that merit attention include sustainability andefficiency (the incentives of the different stakeholders
are well aligned, and the system’s resources are used

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion

5

optimally), flexibility (the framework is tailored tothe country’s needs and capabilities), safety (data is
protected and used in safe ways), and effectiveness(data is used in impactful ways). Several useful tools
are already available to guide stakeholders at different
steps along the S-GDD process (see Appendix), butholistic guidance is needed to help authorities design
and implement S-GDD frameworks that can generate,
analyze, and use relevant S-GDD in effective, safe, andimpactful ways.

To unlock the S-GDD potential tocontribute to women’s financial
inclusion and women’s economic
empowerment (WEE), a more systematicand collaborative approach toward
effective ways to collect and use S-GDD
is needed, in the form of guidance.
The new guidance should be flexible and scalable
across countries and must rest on a robust
conceptual framework that seeks to align incentives
through strong use cases, adequate S-GDD
indicators, and effective collaboration mechanisms.
A clear theory of change should articulate howadequate S-GDD can catalyze a positive market
reaction toward serving women in effective, safe,
and impactful ways (Figure 4). For the guidance to beflexible and scalable across countries with different
objectives, settings, and capabilities, it should beoutcomes-oriented and focused on ensuring that the
S-GDD framework delivers results aligned with theintended objectives, rather than prescribing specificmethods, formats, or tools. These good results
include delivering adequate data and using them toachieve the intended objectives, including informing
decisions and monitoring progress. Whether authorities
mandate or incentivize providers to cooperate, it islikely that S-GDD collection and application will be
more sustainable in a collaborative ecosystem that
supports the goals and objectives of all players. Thisshould also include agreements on data sharing
among various government agencies and supervisors.
Finding common ground to align the incentives of all
stakeholders from the outset of an S-GDD initiative will,
therefore, be essential.
Another key area where the new guidance could
bring value is developing gender-sensitive financial
indicators to measure financial inclusion or to help
regulators and supervisors fulfill their mandates for
all individuals, including the most vulnerable ones.
The S-GDD needs to transcend the traditional focus
on data about access and basic usage of accounts (forexample, outstanding amounts, dormant accounts)
and adopt a more customer-centric approach thatmeasures the immediate outcomes of responsible
financial inclusion for women (for example, percentage
of loan rejections by gender, average credit conditions
by product category and gender) and therefore forproviders (for example, default rates or number ofcomplaints), as well as measures of financial health and,ideally, longer-term development outcomes of financial
inclusion. Using advanced (outcomes-based) S-GDD
indicators, providers might decide that reviewing theeligibility criteria for certain products, such as a basic
account, is warranted to facilitate women’s uptake
and participation. They might also want to review
some decision processes for credit allocation or the
protocols for complaints handling to ensure thatwomen are not discriminated against by men. With thesame indicators, supervisors might decide whether
to take corrective action if it is found that women arebeing discriminated against by a particular provider oracross the board. And might even decide to adopt (orrecommend adoption of) new or revised measures toprevent discrimination practices, including by setting
inclusion targets, generating public awareness about
the situation through public data or reports, providing
financial education to women, or incentivizing
providers or women to participate in the market byadopting risk-sharing schemes.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion

6

SECTION 1

Introduction3

W

OMEN COMPRISE HALF THE
world’s population and are integral toeconomic growth and stability. Women’s
financial inclusion is key to women’s economic
empowerment (Bull 2021) and, therefore, key tosupporting several Sustainable Development Goals(SDGs), especially Goal 5 on gender equality.4 Equal
access to financial services would contribute to (1)reducing poverty and inequality, (2) developing more
employment opportunities, and (3) building inclusive
societies (AFI 2017a; IMF 2022). Greater inclusion of
women as users, providers, and regulators of financial
services has been found to foster greater stability inthe banking system (IMF 2023b). More broadly, theInternational Monetary Fund (IMF) considers thatgender gaps in financial inclusion are among the key
channels through which gender disparities can become
macro-critical, affecting both macroeconomic andfinancial outcomes at the system level, and therefore,
these gaps need to be urgently addressed. Yet,despite significant developments in financial services
and technology, a substantial gender gap in financial
inclusion persists in many countries (Chen et al. 2021;
Global Findex 2021; IMF 2023b).
Digital financial services are key drivers for financial
inclusion in many low-income countries and havecontributed to reducing both income and ruralurban divides, but, contrary to initial expectations,they do not seem to be helping to close the gender
gap significantly (Chen et al. 2021; IMF 2022).
According to Global Findex, the gender gap in
account ownership in developing countries exceeded
5 percentage points in 2021, and it is significantly
larger in parts of South Asia, the Middle East, andAfrica, with gaps ranging from 13 to 20 percentage
points (Global Findex 2021). In developing economies,
the gender gap affects not just account access but
also the use of accounts and associated funds. Whenit comes to saving and storing money in a financial
account, requesting formal credit, and making
payments, the gender gaps in developing economies
are between 5–9 percentage points. The same istrue for digital providers and even more so for mobile
money services, where the gap is 8 percentage
points. Moreover, women-owned businesses––whorepresent 28 percent of all micro, small, and medium
enterprises (MSME) globally, account for an outsizedshare of the global financing gap––with 38 percentof the total microenterprise finance gap ($1.7 trillion)(IFC 2017).
These persistent gender gaps highlight the needfor policy makers to prioritize policies that support
women’s financial inclusion. To inform these, genderdisaggregated data are crucial, as recognized by key
financial inclusion and development global advocates.
In 2020, H.M. Queen Maxima stated, “To close the3

All terms used in this paper are per the nomenclature of the source. Detailed definitions of terms used throughout this paper are included in
Section 2.

4

SDG Goal 5: Gender Equality––Achieve gender equality and empower all women and girls.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿7gender gap in financial inclusion, we need policies
based on evidence and data on women’s financial
inclusion. Getting high-quality gender-disaggregateddata can truly help policymakers make this happen.”5
The World Bank recognizes that gender-disaggregateddata (GDD) helps inform investment decisions inpolicies and interventions that are evidence-based andmore effective at closing the gender gap (World Bank2022). For example, collecting and using GDD can help
“dispel myths about women (being) less than viable
customers and allowing regulators as well as financial
institutions to adapt their strategies to market needs”(World Bank 2022).
Additionally, the 2020 G20 Presidency issued a reporton Advancing Women’s Digital Financial Inclusion,
which, among its 10 policy proposals, recommends
that authorities “work towards financial institutions
providing anonymized sex-disaggregated data as partof reporting requirements, make these data available
publicly and use these data to address the needs ofwomen in product design and/or marketing” (WorldBank 2020b). In keeping with this, the new G20 Data
Gaps Initiative (IMF 2022) recognizes the importanceof having financial inclusion indicators (particularly for
digital finance) for different income groups, women,
and possibly their intersections (use of digital financial
services by women in the low-income segment).
Similarly, in its most recent three-year action plan,
the Global Partnership for Financial Inclusion (GPFI)
identifies the “promotion of data availability––also
on a gender-disaggregated basis––for monitoring
financial inclusion, and supporting evidence-based
policymaking,” as a priority action (GPFI 2023). The
World Bank (in reference to analysis done by theUnited Nations Capital Development Fund (UNCDF)
Policy Accelerator) recognizes that “regulators are(increasingly) becoming aware of the value of andrequiring that providers collect gender-disaggregateddata to shed light on the extent of the gender gap, and5also to monitor progress against initiatives to reduce
this gap” (World Bank 2020b).
While significant progress has been made on
the availability and use of demand-side genderdisaggregated data, the biggest gaps in the generation
and use of national-level data on women’s financial
inclusion lie within supply-side data (Data2X and FAW
2022a). Therefore, this paper examines key initiatives
that have contributed to the increase in the availability
and use of gender-disaggregated data in financial
inclusion with a focus on supply data. It explores
ways in which S-GDD has been used to inform thedevelopment of gender-responsive financial inclusion
policies and strategies, as well as the challenges andopportunities associated with this work. It highlights
lessons to date, seeks to identify existing gaps, andoutlines possible next steps for CGAP and otherstakeholders for future work in this area.
The interest in GDD emerged around 2010 whennumerous regulators began to develop national
financial inclusion strategies and saw the need for morenuanced data to set targets and measure progress(Data2X et al., 2016). The first efforts targeted thedemand side of the market in the form of surveys. This
included Finscope surveys in several African countries,
the World Bank’s Global Findex survey and database,and other national-level surveys. It was mainly thefindings from the demand-side gender-disaggregateddata (D-GDD) that spurred interest in supply-side (thatis, providers’ administrative data) gender-disaggregateddata (S-GDD) to understand the market dynamics andthe role played by formal providers. In the last five
years, key financial inclusion stakeholders have ramped
up efforts to advocate for S-GDD by documenting
country experiences, developing data collection
toolkits, and sharing findings, as explained in theremainder of this section.

Remarks made in the presentation of the UNSGSA report Collecting and Using Gender-Disaggregated Data for Financial Policymaking: Key
Findings from 11 Countries (UNSGSA 2020).

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

8The IMF and the World Bank are strongly committed
to supporting the expansion of initiatives andinvestments towards better and more GDD, including
S-GDD, through global engagement, global data
programs, advocacy work, and technical assistance tocountries. The World Bank’s Global Findex databasehas become a mainstay of global efforts to promote
financial inclusion. Regularly cited by scholars anddevelopment practitioners, it has been used to trackprogress toward the World Bank’s goal of universal
financial access by 2020 and the United Nations(UN) Sustainable Development Goals). As for the
IMF, its Financial Access Survey (FAS) is a key sourceof country-level supply-side financial inclusion data.
The FAS started collecting S-GDD on basic financial
services in 2018. Since then, the number of countries
reporting gender-disaggregated data has grown from35 to 83 in 2023, proving the growing demand forthese data and the increasing traction of global GDDefforts. The IMF is implementing a pilot to expand thegender-disaggregated variables collected throughits FAS. Additionally, as part of its Gender Strategy, aGender Data Hub (for internal use) was developed, andthe Strategy also includes plans to improve S-GDD
collection and modeling tools to conduct policy
analysis with a gender lens (IMF 2022). Also, on the
supply side, International Finance Corporation (IFC) has
led the industry in developing definitions and indicatorsthat financial institutions are required to report if they
have gender initiatives.
In addition, multiple UN agencies are also taking
steps towards expanding the use of GDD. In 2020,
the UN Secretary-General’s Special Advocate for
Inclusive Finance for Development (UNSGSA), in
partnership with the IMF, published a landmark note
documenting specific financial inclusion policies andprograms developed in 11 countries based on genderdisaggregated data (UNSGSA 2020). It identifies key
success factors in S-GDD collection and use andconcludes that designing effective policies to close
the gender gap in financial inclusion depends onstrong systems for collecting and generating data. In
2023, UNCDF published a self-assessment tool forpolicy makers and regulators to understand betterand improve their sex-disaggregated data journey andarchitecture (Falsini 2023). Also, in 2023, Better than
Cash Alliance, the Generation Equality Forum, UNCDF,
UNSGSA, UN Women, Women’s World Banking, and
the World Bank published an updated ten-point callto action for reaching financial equality for women,
which includes the collection, analysis, and use of
sex-disaggregated data (BTCA 2023).
The Alliance for Financial Inclusion (AFI), the Toronto
Center, UNCDF, and the Women’s Financial Inclusion
Data (WFID) Partnership, among others, havedeveloped several tools and resources that authorities
can use to mitigate some of these challenges andsupport authorities to start to collect and use S-GDD.
A detailed summary of these can be found in the
Appendix, as well as details on the work of otherstakeholders and S-GDD initiatives.
The Alliance for Financial Inclusion (AFI) has been
the most significant global player in fostering
the availability and use of supply-side genderdisaggregated data in the financial sector at thecountry level. Its 2016 Denarau Action Plan on Gender
Inclusive Finance calls for “collecting, analyzing, andusing sex-disaggregated data generated by providers
to promote women’s financial inclusion and for its
members to set specific gender objectives within
their National Financial Inclusion Strategies (NFIS).”
This prompted numerous regulators to realize theneed for more nuanced data to set financial inclusion
targets and measure progress. AFI has developeda range of resources to support members on their
S-GDD journeys.
For example, AFI’s practical guidance for policy makers
and regulators in formulating, designing, implementing,and measuring the progress of data-driven gendertransformative policies illustrates the applicationof S-GDD. The main resources are the Core Set of
Financial Inclusion Indicators (the “AFI Core Set”) andthe Sex-disaggregated Data Toolkit. These include
data reporting templates, guidance for designing data
standards (including key definitions), and the scopeof data use according to intended uses that can coverSupply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

9various policy and supervisory objectives (for example,
prudential control, consumer protection, combating
financial crime, competition, and market integrity).
The Toronto Centre has also supported research
and advocacy efforts to promote the collection anduse of S-GDD among regulators and supervisors.
They point to the potential of S-GDD to understandwomen’s pain points while adopting financial services
and to inform the supervision of key market conduct/consumer protection controls such as product design
and governance, behavior and remuneration of sales
agents, and complaints handling and redress (Toronto
Center 2021).
Another crucial global initiative pushing the S-GDD
agenda forward is the Women’s Financial Inclusion
Data (WFID) Partnership. Established in 2014 with eight
members, all of them global organizations,6 WFID has
developed a range of resources to support partners
and other stakeholders in their financial gender data
efforts, and they remain very active in the space.
Their publications include their Strategic framework,
several country-case studies and diagnostics, anda Gender Data Playbook—a step-by-step guide forstakeholders in the financial ecosystem on how toboost the systematic collection of high-quality, supplyside sex-disaggregated financial data to drive women’s
financial inclusion. In addition, WFID’s Gender Data
Dictionary helps countries develop gender-sensitive
metrics by product—accounts, cards, loans, insurance,and digital financial services––and by type of client(including definitions for women-owned small andmedium enterprises (WSMEs) used by IFC and others).
These, and more, global initiatives are summarized in
the Appendix.
At the local level, thanks in part to the help and supportof IFIs and global funders, there are compellingexamples of countries collecting and using S-GDD

in the financial sector to level the playing field for
women. Financial inclusion strategies now provide
sex-disaggregated reporting and recommend actions
such as financial literacy training for women andincreasing women’s access to and use of financial
services in Ethiopia, Pakistan, Rwanda, and Zambia(World Bank 2018b).
For example, Rwanda used S-GDD to develop
its Women’s Guarantee Fund, which provides
supplementary collateral for women entrepreneurs withinsufficient guarantees or credit history to get a loan.
Egypt’s central bank allowed financial institutions tooffer digital wallets with minimal opening requirements
to attract more women customers (Gender Data
Playbook 2023). In Mexico, based on data showingthat women have lower rates of non-performing
loans, the financial supervisors, the National Banking
and Securities Commission (CNBV), has lowered
the capital requirements for certain types of loans
to women. In Chile, leveraging insights from S-GDD,
Banco Estado, a public top-retail bank, created “cuenta
RUT” in 2006: a simplified deposit account that only
requires an ID for opening, is accessible throughnon-banking correspondents and can also be used
to provide government transfers: all features that arehighly convenient for women. The number of women’s
deposit accounts went up from representing 5 percent
of men’s accounts to being on par (100 percent)(Buvinic and Andrade 2019; Data2X et al. 2016). These
examples, and several others elaborated in the next
section (and Box 1), illustrate the potential use of
S-GDD for financial policy, supervision, or businesspurposes. Nevertheless, most authorities still do nothave a strategy around financial gender-disaggregateddata, as evidenced by a global survey of financial
authorities (Cambridge SupTech Lab 2022).7

6

As of January 2024, the WFID Partnership members are Data2X, the Financial Alliance for Women (FAW), the Inter-American Development
Bank (IDB), IDB Invest, International Finance Corporation (IFC), International Monetary Fund (IMF), the World Bank, the Alliance for Financial
Inclusion (AFI), the Organisation for Economic Co-operation and Development (OECD), European Bank for Reconstruction and Development(EBRD), and CGAP.

7

Only 21 percent have a currently operating strategy and 9 percent have one in development, while 70 percent report no strategy at all.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

10SECTION 2

Gender-Disaggregated Data in the
Financial Sector: Concept Mapping
and Building Blocks

T

HIS SECTION EXPLAINS WHAT GENDERdisaggregated data (GDD) means in thefinancial sector; why we refer to genderdisaggregated data as opposed to sex-disaggregated
data; how GDD can be obtained from both the demand
and the supply sides of the market and why thispaper is focusing on the latter (supply-side genderdisaggregated data, or S-GDD); and how S-GDD canbe used to promote women’s financial inclusion andsupport other gender-sensitive policies.
This paper uses the term “gender” instead of “sex” withan inclusive and forward-looking view. Sex refers to theclassification of a person as male, female, or intersex.
However, governments typically understand the term
sex as “sex assigned at birth” or the classificationof people at birth as either male or female. Genderrefers to social, behavioral, and cultural attributes, andexpectations and norms associated with being a man, awoman, or non-binary. Gender identity may or may notcorrespond with the person’s sex at birth or the gender
attributed to them by society (Gender Data Playbook
2023; World Bank 2021). Gender is a broader concept
than sex, and as such, in this paper, we use the term“gender-disaggregated” data to capture all potential
realities, from countries where data is disaggregatedonly by sex (that is, in binary terms) to countries (onlya very few, for now) that use a definition that includes

gender minorities (for example, a non-binary gender
option is legally recognized and the financial sector’sdata collection systems are prepared to transcend the
traditional binary approach).
Data are gender disaggregated when generated,collected, and analyzed separately by gender (forexample, including non-binary people for thosecountries where this is legally and operationallyfeasible). There are two main types of GDD, according
to the origins of the data: demand-side GDD andsupply-side GDD (Figure 1). They offer different, thoughcomplementary, insights into the financial needs ofwomen and whether, where, and how they can meetthose needs under fair and affordable conditions.
Demand-side gender-disaggregated data (D-GDD)
allow authorities to analyze, based on what customers
declare, whether and how the different genders
engage with financial service providers (formal orinformal) to meet their needs and in what conditions.
D-GDD can also help identify women’s motivations
and barriers to accessing and using regulated financial
services by analyzing their answers to questions on
the conditions and quality of the service received (AFI
2017a). D-GDD are collected directly from individuals,
households, and entrepreneurs by different public andprivate actors (for example, authorities, providers, andSupply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

11nongovernmental organizations). Currently, D-GDD arecollected primarily from surveys conducted every three
to five years, which typically comprise self-reported
data. These types of surveys can be costly, but they
are very valuable as they offer the only source of
information about women who are excluded from thefinancial sector, and they offer excellent insights about
women’s perceived financial needs, barriers to and use
of financial services, formal or informal and including
the utility they derive from using them.8

S-GDD offer information about
women already included in the formal
financial sector (who have financial
accounts): how they access the formal
market, which services they use, underwhat conditions, and the performanceof these services.
Phone surveys can be used as an alternative, lessexpensive tool for market monitoring to identify andassess consumer risks and outcomes disaggregatedby gender in the financial sector.9 These data capture
the financial needs, experiences, risks, and outcomesof individuals and microentrepreneurs and how theydiffer by gender and, as such, they allow authorities
to analyze whether and how the different genders
engage with financial service providers (formal orinformal) to meet their needs and in what conditions.
D-GDD can also help identify women’s motivations
and barriers to accessing and using regulated financial
services by analyzing their answers to questions on theconditions and quality of the service received. Other
sources of demand-side data that do not originate
in the financial sector can also complement financial

inclusion data, notably censuses (ID numbers, age) andnational household surveys (for example, family status,
education level, employment, living conditions, andaccess to public infrastructure and digital channels).
Supply-side gender-disaggregated data (S-GDD)
originate from the administrative records of financial
service providers whenever the gender of customers,
agents, and staff is recorded.10 For customers, thegender field is usually generated by the provider during
onboarding (FinEquity 2020). When a good national
ID system is in place, the customer’s ID number isused by the provider to identify the customer in its
records, and the provider may as well populate thegender variable for the customer at that stage. In theabsence of a national ID number, providers might use
other forms of legal identification, and if the gender isstated (for example, certificate of birth), they might aswell record the client’s gender. In some countries, theauthorities request the regulated providers to report
the gender variable along with other granular data. In
others, they do not because they are not interested
in getting S-GDD. A third option is for the supervisor
to use the customer ID (when available and reported)to pull the gender from a national ID database (forexample, in Chile, the supervisors extract the genderfield from the Civil registry by virtue of a memorandumof understanding). In some cases, secrecy laws prevent
providers from reporting deposit data on an individual
basis, and the account identification number is usedinstead. For example, Chile does not report to the IMF
FAS the number of women owning a deposit account,but rather the number of women-owned deposit
accounts, which may lead to double counting.
S-GDD offer information about women alreadyincluded in the formal financial sector (who havefinancial accounts): how they access the formal
market, which services they use, under what

8

In Economics, the term “utility” refers to the benefit that a consumer derives from consuming a good or service.

9

See Tool 8. Phone Surveys in CGAP’s Market Monitoring Toolkit (Izaguirre et al. 2022).

10 Providers are constantly producing a wealth of raw, highly granular data and all these microdata can be aggregated in different ways toperform different functions (for example, reporting, diagnosing problems, monitoring, product design, and strategy).

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

12conditions, and the performance of these services(for example, frequency, amounts, and rates;
collateral requirements; and complaints filed andrate of response). Examples of specific variables
disaggregated by gender include the number ofaccounts by gender, the number of men and womenwith an account, the number of women staff andtheir position at the provider, the outstanding amountof loans given to men and women, and payments
received in an account by men and women. When
additional socio-demographic data is available beyond
gender, it is possible to apply intersectional analysis
and disaggregate along dimensions (for example,
collateral requirements for young rural women).
Financial supervisors can collect S-GDD from theproviders they supervise in granular form (for example,
the list of all transactions for certain types of accounts
where gender can be identified) or aggregate (forexample, the total number of transactions for certain
types of accounts by gender). In both cases, thesupervisor will need to impose standards to allow
comparison across providers. Standardization includes
common definitions of data fields such as “gender,”“account,” and “transaction.” Granular data offer
richer information and broader analysis possibilities
than simple gender aggregates by product type, forexample. Granular data can also offer information
regarding customer experience and satisfaction whenthese data are generated through administrative
channels, such as formal complaints. However, mostfinancial sector authorities do not collect granular
data because standardizing, collecting, storing, andprocessing them can be costly, complex, and subject
to data privacy concerns.11

FIGURE 1. Attributes of Demand and Supply-Side

Gender-Disaggregated Data
Demand-Side Gender-Disaggregated Data
(D-GDD)• Mostly survey data
• Usually low frequency (years)• Both formal and informal financial services• Data on access, usage, and utility• Qualitative data (perceptions about value, risks,
impact)• Sociodemographic data

Supply-Side Gender-Disaggregated Data
(S-GDD)• Mostly administrative data
• High frequency (real time, monthly, yearly)• Mostly only formal financial services• Access, usage, and utility• Mostly quantitative data (effective volumes,
prices, headcount)• Limited data on sociodemographics
Source: Authors, based on reviewed literature.

11 See Tool 1. Analysis of Regulatory Reports in CGAP’s Market Monitoring Toolkit (Izaguirre et al. 2022).

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

13

SECTION 3

Key Lessons from Supply-Side
Gender-Disaggregated Data Initiatives

T

HIS SECTION PRESENTS THE MAIN
findings and lessons from a review of selected
global S-GDD initiatives, some of which haveanalyzed how different countries generate and use
S-GDD and offer targeted recommendations and tools
for authorities and providers to make further progress.

3.1 What drives countries tocollect and use S-GDD?
The S-GDD journey differs from country to country,
and to a certain extent, it is shaped by the initial
motivations that led the country into this journey(Figure 2).
Some countries were encouraged to capture S-GDD by
global initiatives targeting financial authorities (such as
IMF’s FAS) or led by financial authorities (such as AFI’s
Denarau Action Plan). Eighty-three countries reported
gender-disaggregated data in the last round of the IMF
FAS (IMF 2023a) on at least one of the FAS indicators,
including number of borrowers and depositors, loan
and deposit account ownership, and loan and deposit
volumes, by type of institution. Additionally, the IMF iscurrently implementing a pilot aimed at increasing thecoverage of these indicators, including data for small
and medium enterprises (SMEs). Based on an overview
of existing research, the global community has yet
to exploit these rich data. That said, it is more thanlikely that these data will be better utilized as S-GDD

coverage expands and the global community becomes
more familiar with its benefits.
In several countries, S-GDD efforts were prompted by
the desire of policy makers and regulators to address
gender gaps revealed by data from demand-side
studies. For example, the awareness generated by
the availability of demand-side data—which showed
not only a significant gender gap but also a strong
interest in and need for more women-centeredfinancial offerings—contributed significantly to theCentral Bank of Nigeria’s decision to mandate thereporting of sex-disaggregated data by financial sector
providers, as well as the introduction of the Women’s
Financial Inclusion Implementation Framework in 2020
(Data2X et al. 2022d). Nigeria also launched in 2022
a national strategy for leveraging agent networks todrive women’s financial inclusion (National Financial
Inclusion Governing Committee 2022). National
strategies, including explicit targets to reduce gender
gaps in the financial sector, have strongly incentivizedauthorities to start collecting S-GDD. For example,
the State Bank of Pakistan identified gender as a key
priority area in its National Financial Inclusion Strategy
and aimed to increase the share of women with accessto formal financial services from 13 percent in 2015 to30 percent by 2023 (Data2X et al. 2022e). Pakistan’s
Banking on Equality policy also emphasizes collecting
gender-disaggregated data in more granular detail,standardized frequency in reporting, and increased useof insights to inform future policies and initiatives.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

14That said, in some countries, the S-GDD journey inthe financial sector may not be rooted in making
financial inclusion more gender-sensitive but, rather,by a broader objective to set a strong gender agenda
overall, which can then trickle down to the financial
inclusion agenda. This is the case in Chile, where
gender equality has been a prominent issue for thelast three decades, with strong support from top
government officials. Since 1991, a government agency
has ensured that the public sector incorporates agender focus when planning, budgeting, implementing,and monitoring public policies. The use of
sex-disaggregated data is prioritized in the design andevaluation of public policies and legislative reforms aswell as in the monitoring of annual gender goals, andthis also applies to the financial sector, where a genderannual report has been published since the early 2000s(Buvinic and Andrade 2019).
In any case, having a strong culture of data-driven,
evidence-based policy making, as well as strongwilled and committed gender data champions with
influential roles in the financial sector, seems critical tolaunching S-GDD data collection efforts (AFI 2022b;
Data2X et al. 2022a). For example, a former deputy
governor of the Bank of Zambia was the Chair of AFI’s
high-level Gender Inclusive Finance Committee andchampioned gender data within her institution andwithin the AFI network (BoZ et al. 2021). In Rwanda, thegovernment passed several policies and programs toensure gender equality, including to enable women’s
financial inclusion and economic empowerment, witha dedicated Strategy on Women and Youth Access toFinance, which had commitments to collect S-GDD totrack policy impact (Data2X et al. 2019).
Gender data is also essential for financial sector
providers so they can better understand the women’smarket size, understand segment opportunities,
increase customer engagement, and serve more
women. Financial institutions that collect and analyze
gender-disaggregated data have a more accurate
picture of the market opportunity for serving women.
They also build a better business case for developing
products and services tailored to women’s needs. In

FIGURE 2. Main Drivers for Financial Policy

and Supervisory Initiatives on S-GDD
Main Goals• Financial inclusion with a focus on women as avulnerable group (women’s financial inclusion).
• Consumer protection with a focus on genderbased misconduct• Social responsibility. Adding a gender lens topolicies and strategies (for example, gender
diversity; not necessarily linked to financial
inclusion).
• Meeting the requirements or recommendationsof funders or technical assistance providers.
• Alignment with country, regional, or global data
initiatives (for example, IMF FAS).
• Assessment of women’s differentiated financial
risk patterns, needs, and behaviors.
Source: Authors, based on reviewed literature.

In any case, having a strong cultureof data-driven, evidence-based policy
making, as well as strong-willed andcommitted gender data champions with
influential roles in the financial sector,
seems critical to launching S-GDD datacollection efforts.
addition, financial service providers that launch or
maintain a segmented women’s market program canbenefit from understanding its impact on their bottom
line by capturing and analyzing gender data (Data2X
et al. 2020). For example, by gender disaggregating
its customer data, Bank al Etihad in Jordan observedthat women’s savings were lower than men’s. This
trend differed from global trends, which showed thatwomen tend to have stronger savings behavior. Basedon this data-driven analysis, Bank al Etihad launched
the Shorouq Savings Account to encourage women tobuild savings and financial independence through an
ongoing prize program that offered rewards speaking
to Jordanian women’s financial security ambitions:

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿15steady income and homeownership. The prize program
was an immediate success, resulting in female
depositor growth of 6x since the launch of the accountand increased savings behaviors (Data2X et al. 2020).

3.2 How do countries collect
S-GDD, and what data dothey collect?
There are five key steps involved in the data value
chain (Table 1). The combination of options chosen
by different countries in each of these steps explains
the wide array of S-GDD models observed. In many
countries where the financial sector authorities
collect gender data, this is done by including a gendervariable in the mandatory regulatory reports, whether
granular, aggregate, or both. Where available, a national

identification system contributes significantly to theauthorities’ ability to disaggregate data by gender
without having to update financial reporting templates(for example, Brazil, Chile, Costa Rica, Egypt, andMalaysia) (UNSGSA 2020).
In Chile, the supervisor for banks and insurers(Comisión para el Mercado Financiero, CMF) requests
its supervised firms to report certain S-GDD
aggregated at the level of portfolio and institution. The
CMF also collects granular provider data as part of its
prudential reporting process. For these microdatasets,
the CMF does not require the providers to add genderbut rather the individual’s ID number, which canbe cross-referenced with the civil registry records(on the basis of a memorandum of understanding
between both public institutions) to pull gender data
(Data2X et al. 2016). In Rwanda, the National BankTABLE 1. Core Elements of Existing S-GDD Frameworks and Options Available

Main Data Chain Steps

Options (Not Mutually Exclusive)

Data Generation• Done by providers with different degrees of automatization

Data Collection Regime• Mandatory reporting• Voluntary reporting• Cross-referencing with other databases (for example, ID).

Data Collection Mechanisms • Manual (paper templates, with human validation and physical storage).
• Digital (Excel templates sent via email, or templates with different file extensions submitted
through data portals, with digital storage, subject to some automated validation processes).
• Automatized (pull/push application programming interface––API, electronic data warehouses
with automated pulling, validation and digital storage).
Data Use• Policy making (for example, inform national strategies, regulatory processes).
• External disclosure (market discipline).
• Supervision of individual providers (for example, performance goals and KPIs, regulatorycompliance, and conduct, integrity, or prudential risks).
• Market-level monitoring (industry developments, consumer risks, prudential indicators).
• Regulatory or policy impact analysis (for example, policy traction, cost-benefit analysis).
• Supporting or meeting global agreements and assessments; benchmarking (SDG, ESG, FSAP,
and MDB conditionality).
• Analysis and research (for example, understanding provider’s business strategy).
• WFI advocacy primarily by publishing and disseminating reports and organizing stakeholder
meetings and consultations to raise awareness of WFI gaps and discuss solutions.

Data Sharing• Confidential (shared internally on a need-to-know basis; for example, supervisory function).
• External restricted (for example, credit registry data when accessible by providers, open data
arrangements, and interinstitutional working groups).
• External public (for example, IMF FAS, databases, and academic papers).

Source: Authors

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

16uses an electronic data warehouse to pull granularadministrative data from its supervised financial
institutions, which use the ID to fill in the genderfield for each client. In Peru, the Superintendence ofBanking, Insurance and Private Pension Funds requires
all regulated financial institutions to submit a monthly
granular regulatory report with credit information at adebtor level, including a gender variable, to its national
credit registry unit. It also requires pension fundadministrators to submit several regulatory reports
disaggregated by gender. In Pakistan, a regulation
requires regulated entities to report some S-GDD to
the State Bank of Pakistan (Data2X et al. 2022e).
In other countries, financial sector authorities haveadopted a more indirect approach to S-GDD. In a few
cases, authorities have sought to engage providers
to share S-GDD on an ad hoc or voluntary basis. For

example, Kenya’s two main regulators, the Central
Bank of Kenya and the Savings and Credit Cooperative
Societies Regulatory Authority, gather gender dataas needed because it is not currently part of theirmandated regular reporting (Data2X et al. 2022c).
Similarly, in Honduras, the National Commission of
Banking and Insurance began to engage banks toreport granular sex-disaggregated data for a wider
range of usage indicators than what is currently
mandated by regulation (Data2X et al. 2022b).
Several countries (for example, Egypt, Honduras, andRwanda) are moving toward consolidating their datareporting systems through centralized electronic
data warehouses or electronic information systems toincrease efficiency and improve quality. Enhancing theauthorities’ data visualization capabilities, alongsideskills to analyze and interpret the data, can significantly

TABLE 2. Scope and Formats of S-GDD in Existing Frameworks and Options Available

Elements

Options (Not Mutually Exclusive)

Scope of Data Collected• Credit (number and balance of loans, number of loan holders, delinquency rates, rejection
rates, conditions such as fees and rates, complaints).
• Savings (number and balance of accounts and deposits and deposit holders, use of account,
withdrawals, complaints).
• E-money (registered and active customers, balance for savings and credit products,
complaints).
• Payments (number and balance of accounts, remittances, G2P payments, salary payments,
complaints).
• Insurance (number of policies and beneficiaries, premium revenue, claims ratio, complaints).
• Pensions (rates of coverage and use, complaints).
• Employees by gender (total headcount, branch officials, agents, managers, members of the Board)

Granularity Level• Disaggregated (microdata): individuals or accounts.
• Aggregated by gender: individuals or accounts.

Identification Level• Account—individual• Account—shared• Account—business• Shared• Individual• Business

Gender Options• Man• Woman• Gender minority (which may be presented as third gender, non-binary, transgender, or “X”, among
other terms; only recognized in a few countries such as Bangladesh, Chile, India, and Pakistan.
• Other (when gender cannot be determined or fall in the above categories or validated).

Source: Authors

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

17improve the ability of authorities to provide valuable
market insights in accessible and practical ways
(Gender Data Playbook 2023).
On the type of data that is usually genderdisaggregated in the financial sector (Table 2), local
authorities tend to focus on retail accounts andtypically on credit, given its central role in financial
development and supervision. S-GDD on credit include,
for instance, the number of borrowers, the volume
of outstanding balances, interest rates, and in somecases, rejection rates and value of non-performing
loans, all of these by gender. When deposit accountdata are broken down by gender, they are often limited
to aggregate indicators of deposit volume and numberof accounts due to concerns regarding compliancewith banking secrecy laws that forbid providers toshare individual data for deposits other than at theaccount level.
Data collection for business accounts is mainly
done for sole proprietorships who run the businessin their own names, rather than including womenowned MSMEs. According to the existing literature,
the primary cause for this is the lack of commonly
accepted definitions of women-owned MSMEs
in most countries (especially in terms of how todefine women ownership), and where a definition
is standardized at the national level, such as in
Bangladesh, it is not consistently applied by reporting
institutions. This paper focuses mainly on data fromindividuals and microentrepreneurs.
In Chile, the CMF has been collecting S-GDD for thelast twenty years, first in aggregate form by productportfolio and, later also in granular form for individuals
or accounts. The CMF requires providers to submit
gender data as part of the aggregated regulatory
reporting templates for several savings products (thatis, number of accounts and outstanding amounts bytype of product), credit products (that is, numberof borrowers and amounts of credit by producttype, balances and value of non-performing loans,interest rate and term by product type), and insurance
products (currently with much less details than forsavings and credit). Providers are also required tosubmit individual microdata for specific products,
including the customer’s ID number but not theirgender, as already explained.

3.3 How are countries using
the S-GDD they collect,
and what challenges arethey encountering?
There are different examples of S-GDD utilization
across countries. In countries with more experiencein gathering S-GDD (such as Bangladesh, Chile,
Ecuador, India, Mexico, Rwanda, and Zambia), the datais allegedly used to develop gender-informed policies
and products (with different degrees of traction) and tofurther understand gender gaps in financial inclusion.
Several other countries, such as Ethiopia, Nigeria,
Pakistan, Rwanda, and Zambia, also used S-GDD to set
financial inclusion objectives and targets by gender aspart of their national financial inclusion strategies or
specific gender strategies.
Based on a high-level analysis of evidence from AFI
on 24 case studies across 18 countries (AFI 2017b),
activities done to use S-GDD in gender-specificinterventions included:12• Prioritizing women in strategic agendas (including
gender diversity)• Setting quantitative targets• Creating institutional structures or functions
geared to focus on women’s financial inclusion andeconomic empowerment• Funding support, training, and development
programs

12 The 18 countries analyzed are Bangladesh, Burundi, Chile, Colombia, Democratic Republic of Congo, Costa Rica, Ghana, Haiti, Malaysia,
Mexico, Morocco, Peru, Rwanda, Samoa, Senegal, Tanzania, Zambia, and Zimbabwe.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

18

BOX 1. Examples of S-GDD Applications

Gender-informed policies and regulations
S-GDD analysis in Rwanda showed that a lack of
traditional collateral is a key barrier for women who
need access to funds to start or grow their businesses.
In response to these findings, the Goverment of
Rwanda established the Women’s Guarantee Fund for
economically active women who have no collateraland no credit history. Women must present a bank or
microcredit institution with a viable business idea. The
fund guarantees 50 percent of loans made to women
entrepreneurs and 75 percent of loans made to groups,
with a three-year repayment period.
In Chile, the government issued a sustainabilitylinked bond in 2022. In 2023, it updated the bondby adding a gender KPI—reaching 40 percent of
women in board member positions at companies thatreport to the Financial Market Commission (CMF)by 2031. The performance of this KPI is monitored
using S-GDD from CMF. The Chilean government isworking towards establishing a mandatory quota for
women’s representation in boards of directors at allcompanies, both public and private, under the scopeof CMF.
In Ecuador, the Superintendence of Banks issued theControl Standard for the Protection of the Rights ofFinancial Consumers with a Gender Equality Focus,
with the objective to reduce the gender gap in theaccess and use of financial products or services. It
requires financial institutions to train personnel, provide
gender focus products and services, provide financial
education and report their portfolios by gender.
Identifying gender-specific inequalities
In Honduras, an analysis of supply-side data found that,compared to men, women borrowers consistently pay
an interest rate that is 5.8 percentage points higher
per year on business loans and 2.6 percentage points
more for microcredit. These disparate rates can bea deterrent for women business owners who mightotherwise be inclined to access financing.

Chile’s CMF publishes the annual report Gender in the
Financial System. It’s 2022 edition showed that theshare of women borrowers was 7 percentage points
higher than the share of men borrowers. Yet women’s
average loan balances were 43 points below men’s,
even though women consistently exhibited lower
delinquency rates.
Gender-informed products
In Kenya, the Digital Financial Services Associationof Kenya, a group that represents several key players
in the digital lending industry, views the collection of
sex-disaggregated data as foundational to targeting
the women’s market. The availability of such data
opens new opportunities for digital lenders to improvetheir value proposition for under-served populations
including women; for example, by showcasing thebenefits of using gender data in credit scoring.
In Chile, the state-owned commercial bank,BancoEstado, has set up a program to provide
women entrepreneurs with access to businesscapital, education, and networking opportunities,
based on insights gleaned from supply-side genderdisaggregated data.
In Mexico, supply-side data analysis had revealed
that women were not only saving lower amounts for
retirement, but were also doing so less frequently
than men, likely due to lower wages and higher job
informality. In response, the pension regulator has
developed programs to increase women’s retirementsavings, after discovering a gap between men’s andwomen’s rates of savings through disaggregated data.
In 2014, given that very few banks in Türkiye werelooking at the women’s market, Türk Ekonomi Bankası
developed a holistic customer value proposition
for women using S-GDD, which it launched as Türk
Ekonomi Bankası Women Banking in 2014. By 2016,
the bank’s total balance of loans to women MSME
owners had increased by 7 percent, making a strong
case for the continuous profitability of the segment.

Sources: Data2X et al. 2016, Data2X et al. 2019, Data2X et al. 2022; Gender Data Playbook, 2023; Ministry of Finance, Government of Chile,2023; CMF 2022); Ecuador Superintendence of Banks, 2022; and interviews with authorities.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

19• Changing policy, regulatory requirements, andcompliance• Designing specific initiatives and interventions that
address gender gaps
• Partnering with providers or mandating orcompelling them to serve financial inclusion markets• Incentivizing providers––rebates, tax incentives,
strategic alliances• Developing or co-developing and implementing
products, solutions, and services aimed to
improve women’s financial inclusion and economic
empowerment• Measuring impact––return on investment from
improving women’s financial inclusion and economic
empowerment.
Despite all these examples, the high and protracted
gender gaps observed across the board suggest thatthe potential of S-GDD to push the WFI agenda is not
yet being fully met due to several persistent challenges
related to the collection and use of S-GDD, including:• The S-GDD available is not adequate in terms ofaccuracy, quality, scope, or comparability;• Data collected is not fit for purpose;• There is a lack of awareness about the benefits ofusing them;• Authorities may lack the power (mandate),
willingness (incentives), coordination on data
sharing, or capacity (budget, staff) to use it and act.
Data quality challenges pose significant limitations
to its application. Evidence-based decisions requireappropriate data that is of good quality. Data quality
refers to accuracy, completeness, and comparability(World Bank 2022). For S-GDD, this applies to alldata fields contained in the data set, including thegender variable, which should be well-defined, andits entries validated for accuracy. According to theevidence, most data quality issues arise when (1)different supervisory authorities require S-GDD using
different standards (for example, definitions for gendercategories and types of transactions), (2) data aregathered and processed manually (either by reporting
entities or financial authorities), (3) data are generated
with errors by providers staff due to issues such as lackof data skills and siloed internal databases, (4) there isa lack of understanding of the data standards imposedby financial authorities, due to issues such as lack ofdetailed reporting guidance, and (5) data are submitted
late or incomplete.
In Costa Rica, while gender-disaggregated credit data
have been long collected by providers, only recently
did its financial regulator develop gender indicators
to inform the development of policies to bridge thefinancial inclusion gender gap. This might reflect
insufficient analytical capacity and data quality andadequacy (including the mismatch between the datacollected and the data needs of different units within
the supervisor to fulfill different objectives). Until
2019, they did not analyze the data on a gender basis,but the data was there because they could genderdisaggregate using the ID (Superintendencia Generalde Entidades Financieras Costa Rica 2022)
Lack of awareness and buy-in may explain why someauthorities (such as Brazil, Chile, Ghana, and Mexico),
may use available S-GDD for inclusion and evenprudential purposes, but not for market conduct
supervision (to assess how financial institutions
engage with customers and what outcomes
customers obtain from such engagement). Yet such
S-GDD could, for instance, help supervisors identify
potentially vulnerable female client segments, suchas those with high debt and delinquency levels andunsuitable credit products.
Sometimes, S-GDD are not used because they are
not fit for the user’s purpose or because of data gaps.
For example, some providers will only produce reports
disaggregated by gender if the supervisor requiresso (that is, for regulatory reporting purposes). But
the data produced for regulatory reporting may notnecessarily be the type of data the providers can use
to inform commercial product development decisions,or to help them improve their risk management.
Typically, regulators only ask for data on the number

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

20

of women accessing financial services. However, thisinformation is only the first step in designing effective
products and services that meet the needs of womencustomers. Gender-disaggregated indicators fordormancy, delinquency rates, or credit conditions
are generally not requested by regulators, but suchinformation, when reported on a timely basis and withstandardized frequency, can be very helpful for both
regulators and providers to better understand how well
products are used, identify risks and opportunities, andassess whether products are meeting the customer
needs and generating good customer outcomes. This is
why emerging customer-centric consumer protection
regulatory frameworks emphasize the need forproviders to have internal reporting and management
information systems that go beyond access and usage
data and allow prompt identification and measurementof customer risks and outcomes from different
segments (Izaguirre 2020).

The potential of S-GDD to push the WFIagenda is not yet being fully met due toseveral persistent challenges related tothe collection and use of S-GDD.

the potential for serving women, which poses a barrier
to expanding product offerings tailored to their needs(Data2X et al. 2022a). At the same time, the absenceof publicly available industry or market-level S-GDD
means that providers cannot see the full scope of
women’s activity in the financial system, which further
hampers their ability to both identify pockets of risk
and new business opportunities in serving women(Data2X et al. 2022).
Data must be used safely for all market actors, and,in some cases, the reporting and sharing of granular
S-GDD will not be possible due to privacy concernsand secrecy laws. In other cases, the lack of common
agreements or cooperation on data sharing among
multiple regulatory agencies, including financial
infrastructure agencies such as credit bureaus, causes
significant bottlenecks to access available S-GDD(AFI 2021). In most other cases, the more S-GDD
are accessible, understandable, and interoperable,
the higher the chances that they will be used andrepurposed by different stakeholders, minimizing
duplication efforts, and expanding the possibilities foranalysis and use. Yet, this requires a concerted effort at
multiple levels (for example, inter-departmental or interagency coordination in the public sector) that goes wellbeyond the gender dimension.

The lack of awareness or skills may also prevent
providers from harnessing S-GDD to serve women.
The WFID Partnership’s market modeling calculations
revealed an average annual revenue opportunityfrom serving women of about USD 628 million foreach of the six countries studied,13 ranging from USD
352 million in Honduras to USD 1.16 billion in Türkiye(Gender Data Playbook 2023). Yet, although thepotential for good business cases seems clear basedon this exercise, most providers do not see the valuein S-GDD or lack the necessary knowledge or skills to
deploy the gender data generation and analysis efforts
needed to fully tap into this market opportunity. This
results in a lack of an evidence-based understanding of

13 Bangladesh, Honduras, Kenya, Nigeria, Pakistan, and Türkiye.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

21

SECTION 4

The Way Forward
to Unlock S-GDD Potential

O

UR RESEARCH HAS CONFIRMED THAT,
even if there is consensus that S-GDD
are useful to inform gender policies in thefinancial sector and beyond, their potential is not
being sufficiently exploited. The collection and use of
S-GDD is suboptimal across the board due to low data
quality and suitability, lack of awareness, mandate orcapacity, and data privacy concerns. Financial sector
stakeholders, under the lead of the authorities, could
leverage the big S-GDD potential to advance women’s
financial inclusion if they enable S-GDD frameworks
that can generate, analyze, and use the relevant
S-GDD in effective, safe, and impactful ways. Several
useful tools are already available to guide stakeholders
at different steps along the S-GDD process (seeAppendix). Yet there is a need for a more holistic effort
that covers the full spectrum of considerations andactions required by the authorities to design effective
S-GDD frameworks, foster the needed collaboration
with the industry, and use the data in impactful ways.
For a comprehensive picture, S-GDD would encompass
both customer data and gender-disaggregated staff
data in the financial sector.
In the absence of global principles, authorities andpractitioners need guidance to design effective
S-GDD data systems. The best foundation for suchguidance would be a clearly articulated ToC for how
S-GDD, powered by adequate incentives, capacities,
and behaviors, can help public and private actors

In the absence of global principles,
authorities and practitioners needguidance to design effective S-GDD
data systems.
identify the risks and opportunities associated withserving women and strategically act on these. The
ToC would be a corollary to a conceptual frameworkthat identifies strong use cases for providers,
supervisors, and policy makers and articulates how
these use cases can be enabled in sustainable
and effective ways through the use of good GDD
indicators (Figure 4). This conceptual framework
would articulate how several S-GDD indicators
can be used by the different stakeholders to gaina better understanding of the market dynamics
from a gender perspective and identify potential
gaps and differences in the use of certain financial
products or services by gender. It could also show
how stakeholders can use S-GDD (probably in
conjunction with D-GDD) to assess whether theobserved differences and gaps are due to different
needs and preferences (also driven by the customer’s
own vulnerabilities and constraints) or rather to theexistence of market-related barriers or discriminatory
practices. The findings from this analysis will put the
stakeholders in a better position to take strategic
action towards reducing the gender gap in finance.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

22

FIGURE 3. Helping Financial Sector Authorities Unlock S-GDD Potential through a Theory of Change (ToC)and Guidance
S-GDD potential can be held back by

S-GDD potential can be unlocked with

Lack of awareness and prioritization• How can S-GDD support the goals of my institution?

Conceptual framework with strong ToC and use cases
Lack of an enabling environment

for how S-GDD can be used in effective and impactful ways

• Do we have the internal support and capacity to collect/
use S-GDD? Mandate? Champions? Staff?

Lack of guidance or benchmarks• What S-GDD to generate and how to analyze and use it
to produce relevant indicators?
• How to use the indicators to inform decisions?
• How to ensure data quality, safety, privacy?
• How to share the data and indicators?
• How to promote collaboration across authorities andwith providers?
• How to get staff to collect/analyze/use the data?

Technical guidance to design and put in place costeffective S-GDD frameworks conducive to high-quality
S-GDD indicators in support of data-driven gender
strategies

Source: Authors

For example, providers might decide that a reviewof the eligibility criteria for certain products, such asa basic account, is warranted to facilitate women’s
uptake and participation. They might also want toreview some decision processes for credit allocationor the protocols for complaints handling to ensure thatwomen are not discriminated against men. With thesame indicators, supervisors might decide whether
to take corrective action if it is found that women arebeing discriminated against by a particular provider oracross the board. And might even decide to adopt (orrecommend adoption of) new or revised measures toprevent discrimination practices, including by setting
inclusion targets, generating public awareness about
the situation through public data or reports, providing
financial education to women, and incentivizing
providers or women to participate in the market byadopting risk sharing schemes.

Such a solid conceptual framework would provide agood basis for technical guidance presenting(1) the key attributes and outcomes that a good S-GDD
framework should have to generate adequate S-GDD
indicators, (2) best practices and recommendations
for supervisors to generate relevant and high-quality
S-GDD, and (3) best practices and recommendations
for authorities to use and share the selected indicators
in meaningful and impactful ways. This guidanceshould address five main questions:
1. Who are the relevant stakeholders, and what are
their objectives and mandates regarding S-GDD?14
2.

What S-GDD are needed to achieve thoseobjectives (raw data, indicators)?

3.

How can S-GDD be most efficiently obtained andprocessed by the supervisor while ensuring its
quality and integrity?

14 International Financial institutions, funders and other global WFI advocates, policy makers, supervisor, regulator, provider of financial products
and services, ancillary services, social organizations, academics, market analysts, customers, investors.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

23

FIGURE 4. A Theory of Change for S-GDD: potential uses and flows of S-GDD in the financial sector

Shares aggregate S-GDD and analysis
Market, global
policymakers andinclusion and genderadvocates

Market intel

Demands suitablefinancial service/product
Gender diverse
customer baseOffers suitable(gender-smart) financial
service/product

Reports S-GDD
Financial sector
provider generates
and uses S-GDD

Supervisory
feedback/action

Financial Sector
Supervisor collects,
manages and uses
S-GDD

Regulatory/policy
actionRaises flags and informs
Financial Sector
Regulator andPolicymaker

Source: Authors

4. How can S-GDD be efficiently and safely usedand shared by authorities to contribute to theintended goals?
5.

How can collaboration across authorities andacross public and private stakeholders bepromoted all along the process to initiate a virtuous
S-GDD circle?

For the guidance to be flexible and scalable acrosscountries with different objectives, settings, andcapabilities, it should be outcomes-oriented andfocused on ensuring that the S-GDD framework
delivers results that are aligned with the intended

objectives, rather than prescribing specific methods,
formats, or tools. These good results include delivering
adequate data and using them to achieve theintended objectives, including informing decisions
and monitoring progress. There is consensus about
the attributes that data, including S-GDD, should haveto be useful and impactful (for example, robustness,reliability, quality, comparability, cost-effectiveness,and relevance) (World Bank 2021c).
Similarly, while there is no agreed definition of what
would constitute an “ideal” S-GDD framework, somefeatures already stand out from the literature. These

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

24

include having champions, producing data with
sufficient quality, embracing a customer-centric
approach to designing and analyzing data indicators,
promoting data sharing and collaboration acrossstakeholders, and seeking proportionality in the datarequirements. Other qualities that merit attention
include sustainability and efficiency (the incentivesof the different stakeholders are well aligned, andthe system’s resources are used in an optimal way),
flexibility (the framework is tailored to the country’s
needs and capabilities), safety (data is protected andused in safe ways), and effectiveness (data is used in
impactful ways).
A key area where more work is needed is thedevelopment of gender-sensitive financial indicators
to measure financial inclusion or to help regulatorsand supervisors fulfill their mandates for all individuals,
including the most vulnerable ones. Pailhé (2018)
proposes a broad set of S-GDD indicators that are
pertinent for financial inclusion (including access,usage, and quality of usage). Some of the indicators
proposed are also relevant for the prudential
supervisory function (loan portfolio delinquency for
women, number of loans to women with collateral)and for the conduct supervisory function (for example,
average cost of opening an account, complaints filed).
The Alliance for Financial Inclusion also publisheddetailed guidelines and reporting templates, including
selected financial sex-disaggregated data indicators,
for regulated financial institutions in different financial
sectors, including banking, non-banking financial
institutions, digital financial services institutions,insurance institutions, and pension schemes
institutions (AFI 2020). Conduct supervision, which
has a strong consumer protection angle, is key topromoting financial inclusion (World Bank 2023), butthere is little evidence that S-GDD is being used toreinforce this function.
The recent emergence of clearer consumer protection
mandates and responsibilities for several financial
sector regulators and supervisors globally, and thestrengthening of responsible finance standards forproviders, could change this status quo and facilitate

the collection and use of data to (1) inform regulation,(2) analyze consumer complaints data from providers
and customers, (3) conduct inspections, and (4) domarket monitoring (World Bank 2023). All of thesewould require substantive S-GDD under a gendersensitive supervisory and regulatory approach,especially under its more evolved form, from acompliance-based, provider-focused approach towarda customer-outcomes- and risk-based approach.
This trend is facilitating the development of new
customer-centric indicators based on customer
experiences with financial products and services,which aim to assess whether such products andrelated provider practices contribute to desired
immediate outcomes such as suitability, voice andchoice, security, or meeting the customer purpose.
In turn, this trend is also accompanied by increasing
efforts to develop indicators to measure financial
health outcomes and longer-term development
outcomes of financial inclusion.

Finding common ground to align the
incentives of all stakeholders fromthe outset of an S-GDD initiative will,
therefore, be essential.
As these indicators are developed under a customercentric approach, disaggregation by gender and othercharacteristics comes as a natural development toensure that the outcomes are adequately assessedfor different segments. Guidance to develop,
test, and use such indicators will have to allow fordifferent levels of development. The ability to workwith granular, complex customer-segment data
and to implement change activities will vary acrossdifferent types of providers (and authorities) withina jurisdiction, and among different providers andauthorities across jurisdictions. Those who alreadysegment their customers and engage in customercentric activities will likely derive more immediate
value. However, this shall not prevent less advanced
actors from using S-GDD to improve their objectives.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿25

A graduated approach based on good practices andlessons learned across different jurisdictions canhelp develop guidance that fits different stages ofdevelopment. In addition, data automation represents
a clear opportunity for the collection and analysis of
S-GDD, including the potential of using big data andSuptech approaches and complex analytical tools via
Machine Learning and AI to tap into predictive andprescriptive analysis.

awareness, helping to build capacity of the providers
or promoting collaboration and consultations among
key stakeholders to advance WFI.

Lastly, an important note on the need for collaboration.
In most countries, financial authorities have led theway and incentivized providers to focus on womenand increase their production of S-GDD to promote a
responsible finance ecosystem. This demonstrates the
key role they can play in advancing gender-equitablefinancial inclusion and is a reason to further invest
in their support of deepening country-level S-GDD
initiatives. Yet it will also be important to position the
S-GDD framework within broader data collection
efforts, including any ongoing efforts toward greater
data segmentation and disaggregation and toward
rationalization of overall data collection efforts.
Whether authorities mandate, compel, or incentivize
providers to cooperate, it is likely that S-GDD
collection and application will be more sustainable
in a collaborative ecosystem that supports thegoals and objectives of all players. This should also
include agreements on data sharing among various
government agencies and supervisors.
Finding common ground to align the incentivesof all stakeholders from the outset of an S-GDD
initiative will, therefore, be essential. Authorities
will be driven by their different mandates, including
stability, integrity, consumer protection, inclusionand development, data privacy, or gender equality,
while providers will be mainly motivated by thebusiness case. The guidance should identify effective
collaboration mechanisms (both across relevant
authorities and among these and financial providers)that are credible and can be implemented insustainable ways over the long term, in line with what
several regulators already do, including publishinggender and financial inclusion reports to raise
Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

26

APPENDIX

Financial Gender Data Initiatives
Reviewed for this PaperTHIS APPENDIX INCLUDES A MORE
detailed description of financial inclusion
gender data initiatives and efforts reviewed

for this paper. Table A1 summarizes the names andfocus areas of these initiatives and is followed by moredetailed descriptions for each.

TABLE A1. Summary of Selected Initiatives

Initiative Type

Implementing Institutions and Initiative Focus Areas

Global initiatives focused onincreasing the availability anduse of financial gender data forpolicy making with a focus on
S-GDD• Women’s Financial Inclusion Data Partnership (WFID): a global partnership created toincrease awareness of the importance of sex-disaggregated financial services dataand coordinate partners to maximize its collection and use. Focus areas: advocacy andawareness building on the importance of WFI data (D-GDD and S-GDD), country data
diagnostics and case studies, gender data playbook for supervisors.
• Alliance for Financial Inclusion (AFI): as part of the work of the Financial Inclusion
Data Working Group and Gender Inclusive Finance Thematic Area. Focus areas: policy
guidance, data collection and reporting templates for supervisors, country case studies,motivator for countries to start collecting S-GDD.
• Toronto Center: as part of the gender work and Gender Equality Community of Practice(CoP). Focus areas: supervisor guidance on using S-GDD to become agents of change inwomen’s financial inclusion.
• Office of the UN Secretary-General’s Special Advocate for Inclusive Finance forDevelopment (UNSGSA): as part of the Gender Working Group. High-level advocacy andawareness. Focus areas: policy guidance to help regulators collect gender-disaggregatedfinancial data, and design policies based on documented evidence.
• United Nations Capital Development Fund (UNCDF) Policy accelerator. Focus areas:
advocacy and awareness of S-GDD, tools for policy makers to assess their level of
preparedness to collect, analyze, and use sex-disaggregated demand-side and supplyside data.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

27

Initiative Type

Implementing Institutions and Initiative Focus Areas

Collection of GDD that isrelevant to analyze women’s
economic empowerment
through financial inclusion
and agency

World Bank
• World Bank Global Findex (demand-side financial data, global).
• World Bank Enterprise survey (firm-level surveys on broad range of business environment
topics, global).
• SME Finance Forum (SME finance gap including gender finance gap, global).
• World Bank Universal Financial Access reports (global progress toward universal
financial access).
• World Bank Global Payment Systems Survey (GPSS) (status of payment systems, global).
• World Bank Global Financial Inclusion and Consumer Protection (global data source ofefforts by financial sector authorities to improve the enabling environment for financial
inclusion and financial consumer protection).
• World Bank’s Women, Business and the Law (laws and regulations that affect women’s
economic opportunity, global).

The International Monetary Fund• IMF Financial Access Survey (supply-side financial access data, global).
• The Data Gaps Initiative (policy-relevant data gaps identified following the global
financial crisis).

Global System for Mobile Association (GSMA)• GSMA surveys (supply and demand data from mobile money industry, global).

Organisation for Economic Co-operation and Development (OECD)• International Survey of Adult Financial Literacy (financial literacy, financial behavior andattitudes, global).
• OECD Social Institutions and Gender Index (SIGI) (access to productive and financial
resources by women).

FinMark Trust• FinScope (regional and country-level demand-side data surveys in several African andAsian countries).
Initiatives focused on advancing
women’s financial inclusion
through supporting market
actors with data-driven
approaches• Networks, coalitions and partnerships that support providers with gender-disaggregateddata collection tools and capacity building:• Women Entrepreneurs Finance Initiative We-Fi (Women Entrepreneurs (WE) Finance
Code and entrepreneurial activities)• Financial Alliance for Women (FAW)• BBVA Microfinance Foundation (FMBBVA)• Women’s World Banking• Regional banks that support initiatives to promote women’s economic empowerment, andprovide technical assistance and support to member countries to improve the availability
and quality of gender-disaggregated data:• African Development Bank Group (AfDB)• Asian Development Bank (ADB)• Inter-American Development Bank (IDB)• CGAP––extensive work on customer centricity, customer outcome framework with agender component• FinEquity, convened by CGAP at the World Bank––community of practice focused on
women’s financial inclusion.

Source: Authors

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

28

Global initiatives focused onincreasing the availability anduse of financial gender data forpolicy making
WOMEN’S FI NAN CIA L IN CLUS IO N DATAPA RTNER SHI P (W FID )Advocacy and awareness building on WFI data
(D-GDD and S-GDD), data harmonization efforts,
resources, and publications.
Established in 2014, WFID Partnership is a coalition
focused on improving the availability, production, anduse of sex-disaggregated data to promote women’s
financial inclusion. Members include AFI, Data2X, EBRD,
Financial Alliance for Women, IFC, IMF, World Bank,
OECD, UNCDF, IDB, and IDB Invest.
The project developed a range of resources to support
partners and other FI stakeholders in their WFI data
efforts. These resources include:• Strategy brief on the role of sex-disaggregated data
in increasing financial inclusion for women maps out
the WFI data ecosystems and presents a theory ofchange (Data2x et al. 2018).
• Country case studies: Six country diagnostics—
detailed assessments of the availability and use
of gender data for achieving women’s financial
inclusion, including the opportunities to intervene,close data gaps, and expand access to financial
services (Bangladesh, Honduras, Kenya, Nigeria,
Pakistan, and Turkey); additional country casestudies on gender data availability and usage in FI(Chile, Mexico, Rwanda, and Zambia).
• Women’s Financial Inclusion Data Dictionary(Data2X 2022) is the result of a systematic review
of over 350 financial inclusion indicators in use
across the WFID partners’ programs. The dictionary
draws predominantly from the datasets and key
publications by the World Bank, IFC, IMF, AFI, andthe Financial Alliance for Women.

• Gender Data Playbook 2023: A step-by-step guidefor financial ecosystem stakeholders on how toboost the systematic collection of high-quality,
supply-side, sex-disaggregated financial data todrive women’s financial inclusion. In this Playbook,the authors present a stakeholder mapping toolthat uses three stakeholder categories withina country’s S-GDD ecosystem: data producers(mostly composed of providers), data aggregators(including supervisors, regulators, government
agencies, credit bureaus, development financeinstitutions, and other groups that collect datafrom financial services providers, aggregate it into
relevant indicators or statistics and, in some cases,
publish and disseminate some of the data; andother ecosystem influencers that are relevant indriving women’s financial inclusion such as tradeassociations, development finance institutions,nongovernmental organizations, and others. For
example, the National Financial Inclusion Council isa Mexican government agency that was establishedin 2013 with the goal of promoting financial inclusion
and reducing financial exclusion. In Rwanda, theMinistry of Finance and Economic Planning andthe Ministry of Gender and Family Promotion are
engaged in WFI initiatives; in Kenya, a country where
digital services are the major vehicle for WFI, theDigital Lenders Association of Kenya serves as a
focal point for sex-disaggregating digital credit data.

AL L I AN C E F O R F I N AN C I AL I N C L U S I O N (A F I)
Policy guidance, data collection and reporting
templates, country case studies, and motivator forcountries to start collecting S-GDD.
AFI’s Denarau Action Plan (DAP) on Gender Inclusive
Finance (AFI 2016 and 2022) sets the stage for
AFI’s members to commit to and act on advancing
women’s financial inclusion in their countries. It
specifically calls for the collection, analysis, and use of
sex-disaggregated data to promote greater women’s
financial inclusion and to set specific financial inclusion

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿29objectives and targets within members’ National
Financial Inclusion Strategies.
Since adopting the DAP, AFI has published knowledge
products specifically targeted at closing the gender
gap and supporting members on their S-GDD journeys.
These resources include:• Guidelines for policy makers and regulators on how
to leverage S-GDD to achieve gender-inclusive
policy changes (AFI 2022a).
• Practical toolkits on how to collect, analyze, anduse S-GDD (AFI 2017b and 2021).
• Data reporting templates by financial sub-sector(banking and nonbank financial institutions, digitalfinancial services providers, insurance, and pensions),
including guidance on reporting timelines, guiding
principles, definitions of key concepts included in thetemplates, and the generic templates that identify
the data to be collected (AFI 2020).
• Country case studies summarize lessons from AFI
member institutions in following a standard datacollection mechanism from the supply side.
• AFI data portal that allows AFI members toreport the AFI Core Set and additional indicators
segregated by sex.
In addition, AFI also promotes and demonstrates
the application of S-GDD in practical guidance forpolicy makers and regulators in formulating, designing,
implementing, and measuring the progress ofdata-driven gender-transformative policies (AFI 2022b).

UNSGSA
Policy guidance
Advocates for the relevance of S-GDD, documents
relevant country evidence, and presents
recommendations for policy makers to collect anduse gender-disaggregated financial data and design FI
policies based on such evidence. In 2020, it publishedCollecting and Using Gender-Disaggregated Data for
Financial Policymaking (UNSGSA 2020):• This paper is most useful for financial sector
regulators and policy makers, as well asorganizations that work with them on financial
inclusion and data collection. It focuses on 11
countries (Bangladesh, Chile, Costa Rica, Egypt,
Ghana, India, Malaysia, Mexico, Nigeria, Peru, andUganda) that collect GDD, although a few werereported to use solely demand-side data (D-GDD),
featuring a range of experiences.
• Documents specific policies and programs basedon gender-disaggregated data developed in the
study countries.
• Identifies key success factors in S-GDD collection
and use.

UN C DF P O L I CY AC C E L E R ATO R
Gender-disaggregated data mapping tool (Falsini 2023)
Developed a self-assessment tool for policy makers andregulators who want to understand and improve theirsex-disaggregated data journey and data architecture.
It works by assessing their level of preparedness tocollect, analyze, and use sex-disaggregated demandside and supply-side data.

TO R O N TO C E N T E R
Policy guidance
Published Guidance on how supervisors can use
S-GDD to be agents of change in WFI (Toronto Center2021) based on experiences from Colombia, Kenya,
Peru, and Zambia. The guide:• Examines how financial services regulators use, or
could use, S-GDD to enhance women’s access toand use of financial products and services of theright quality that meet their needs, and how newtechnologies could help.
• Includes a hypothesized applied theory of change
and causal chain of the steps that would benecessary to, or likely to enable or form a barrier to,
the use of SDD to enhance financial inclusion of
women, supported by RegTech.

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

30• Includes a maturity framework drawing on six
dimensions that interact to create the conditions
for the optimal use of SDD: regulatory remit andcapabilities, technological capabilities, financial
inclusion focus, gender equality focus, market
maturity, and infrastructure (physical, legal,
and institutional).

Data collection initiatives that
include gender-disaggregateddata that is relevant for financial
inclusion at global, regional, andcountry levels
While significant challenges exist in data availability
and use, growth in key data sets and surveys has
increased the availability and use of gender data on
access to financial services. Data are generated on
various levels: globally and regionally by cross-country
services or providers, and, on the whole, nationallyand sub-nationally by regulators or government
entities. Demand-side and supply-side data setsare complementary. Both are necessary to paint a
complete picture of a country’s or a region’s financial
inclusion situation. Below are some of the most
relevant data initiatives from a range of stakeholders
that include gender-disaggregated data.

DATA FROM THE WO R LD BA N K• The Global Findex Database (World Bank 2021b): A
survey conducted by the World Bank since 2011 thathas contributed to the availability of demand-side
gender-disaggregated data in financial inclusion.
The survey results, published every three years,
provide data on how people use financial services,from payments to savings and borrowing, andmanage financial events, such as a major expense
or a loss of income. For example, the data provide asnapshot of whether women in a given country haveaccounts (or are borrowing or saving) with formal
financial institutions, or whether they transact
with other providers. The latest edition, based onnationally representative surveys of 128,000 adults
in 123 economies during the COVID-19 pandemic,
was published in 2021 and includes a special brief
on gender financial inclusion.
• The SME Finance Forum at IFC was established by
the G20 Global Partnership for Financial Inclusion(GPFI) in 2012 as a knowledge center for data,
research, and best practices in promoting SME
finance. The SME Finance Forum estimates thesystemic MSME finance gap across developing
countries (IFC 2017). These initiatives provide a
detailed picture of the challenges women face inaccessing financial services and can help identify
areas for intervention.
• Other relevant World Bank surveys are used
to monitor progress on enablers and drivers ofuniversal financial access, which provide data that iscomparable across countries and over time. These
include the Global Payment Systems Survey (GPSS)(World Bank 2018a), the Global Financial Inclusion
and Consumer Protection (FICP) Survey (WorldBank 2017), and Enterprise Surveys on firms’ accessto financial services (World Bank 2023b). Genderdisaggregation in these supply-side databases isreduced but not inexistent, and, more importantly,
it is increasing. It is anticipated that the genderangle will be increasingly incorporated in global data
initiatives under the lead of the G20 and its Global
Partnership for Financial Inclusion.
• A series of other World Bank initiatives also produce
data relevant to understanding the status ofand potential enablers and barriers for women infinance. The World Bank’s Women, Business and the
Law annual studies measure the laws that affectwomen’s economic opportunity in 190 economies
across eight indicators structured around women’sinteractions with the law: mobility, workplace, pay,marriage, parenthood, entrepreneurship, assets,
and pension (World Bank 2023a). The World Bank
Entrepreneurship Database (World Bank 2020b)
added new gender indicators to its latest edition:of 143 economies for which data was collected,
44 provided sex-disaggregated data, allowing

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

31

International Development Association (IDA)
countries to more accurately capture and report on
economic activity, such as the percentage of new
women business owners.
• IFC launched a global initiative to strengthen
the capacity of strategic financial institutions toleverage sex-disaggregated data (SDD). The lackof sex-disaggregated data is a well-known barrier
for financial institutions to better support womenclients. To address this barrier, IFC launched a global
project to support 90 financial institution clientsin collecting, tracking, monitoring, and analyzing
sex-disaggregated portfolio data. These services will
be offered in two phases free of cost to selected
IFC clients.

DATA FROM THE IN T E R N ATIO N A L M O N E TARYF UN D (I M F)
• Financial Access Survey (FAS) is a key global
source of country-level supply-side financial
inclusion data. The IMF has been actively promoting
the collection of sex-disaggregated data byfinancial service providers and regulators, which has
contributed to increased availability of such data. In
2017, it announced its intention to include genderdisaggregated data as an integral part of annual
surveys, building on a pilot in which 27 countries
had participated. However, not all countries reportgender-disaggregated data for reasons includinglack of source data, technical and administrative
constraints, and gender-disaggregation not being
part of supervisory requirements. In 2023, of the 169
countries that have submitted data to the FAS, 83(up from 71 in 2021) reported gender-disaggregateddata (IMF 2023a). This also reflects growing demand
globally for these data to strengthen evidencebased gender policies.
• The Data Gaps Initiative was launched in 2009by the G20 Finance Ministers and Central Bank
Governors to close the policy-relevant data gaps
identified following the global financial crisis. The
most recent Data Gaps initiative (2022) recognizes

the importance of financial inclusion indicators(particularly for digital finance) for different income
groups, women, and possibly their intersection(IMF 2022).

DATA F R O M T HE GLO BAL SYST E M F O R
MO B I L E AS S O C I AT I O N ( GS MA)
The GSMA Mobile Money for Development program
contributes to the availability of global specialized
sex-disaggregated data by collecting data on mobile
money access and usage, and small and medium
enterprise finance, respectively. GSMA collects
supply-side data from the Mobile Money Deployment
Tracker, the Global Adoption Survey on Mobile Money,
and the Mobile Money Estimates and Forecasts. This
supply-side data is further enhanced with nationally
representative quantitative primary research from the
GSMA Consumer Survey of nine LMICs, and genderdata gaps on mobile money and mobile phones are
published annually (GSMA 2022, 2023a, 2023b).

DATA F R O M T HE O R GAN I S AT I O N
F O R E C O N O MI C C O- O P E R AT I O N AN D
DE V E LO P ME N T ( O E C D )• The OECD/International Network on Financial
Inclusion 2020 International Survey of Adult
Financial Literacy analyzes the financial literacy
data from 26 countries and economies. It primarily
reports the financial literacy scores and theirelements of knowledge, behavior, and attitude, ascalculated using the OECD/INFE methodology anddefinition of financial literacy. It includes a section
on vulnerable groups where it discusses genderdifferences in financial knowledge and well-being(OECD 2020).
• The Social Institutions and Gender Index (SIGI),
2023 Global Report provides a global outlook of
discriminatory social institutions, the fundamental
causes of gender inequality. It reveals how formal
and informal laws, social norms, and practices limit
women’s and girls’ rights and opportunities in all
aspects of their lives (OECD 2023).

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

32

DATA FROM FI N M A R K T R UST
The FinMark Trust FinScope Consumer and FinScope
MSME national-level demand-side surveys offer
regulators a nuanced measure of national progress infinancial access and usage in several countries, mostly
in Africa (25 countries) and Asia (7 countries). FinScope
surveys have been used for a long time in several
countries as a key source of demand-side data. The
sex-disaggregated survey data provides information on
how individuals manage their financial lives and offers
insight into attitudes, behaviors, and perceptions about
financial products and services.

Women’s financial inclusion
initiatives supporting providers
and other market actors with
data-driven approaches
A range of other financial inclusion stakeholders
contribute to the availability of supply-side
sex-disaggregated data in financial inclusion byencouraging financial institutions to collect andanalyze data on women’s access to financial services.
They also advocate for using this data to develop
targeted financial products and services for women.

NETWORKS, COALITIONS, AND PARTNERSHIPSTHAT SUPPORT PROVIDERS WITH GENDERDISAGGREGATED DATA COLLECTION TOOLSAND CAPACITY BUILDING
The Women Entrepreneurs Finance Initiative (We-Fi)
is a groundbreaking global partnership hosted by theWorld Bank that aims to increase access to financefor women entrepreneurs in developing countries
by providing financial and technical assistance tofinancial institutions. We-Fi’s partners include fourteen
donor governments, six multilateral developmentbanks as implementing partners, and numerous

other stakeholders in the public and private sectors
worldwide.15 Projects are implemented in dozens
of countries, with over half of the funds going to
low-income (IDA-eligible) countries, including manyfacing fragility, conflict, and violence. We-Fi takes anecosystem approach to removing barriers to women’s
economic empowerment, addressing constraints
and opportunities related to finance, market access,capacity, and the enabling environment. Throughits partnerships with financial institutions, We-Fi
encourages the collection of sex-disaggregated data on
loan disbursements, repayments, and defaults, which
can help identify the needs of women entrepreneurs
and develop targeted financial products and services.
We-Fi also recently launched the WE-Finance Code,a commitment by providers, regulators, developmentbanks, and other financial ecosystem players to work
together to close the finance and data gaps affecting
women entrepreneurs.16
The Financial Alliance for Women (FAW) is aninternational consortium of financial institutions
interested in the female economy. Its members workin more than 135 countries to build programs that
support women with access to capital, information,
education, and markets. FAW makes the case among its
private financial member institutions globally to collectsex-disaggregated supply-side data, allowing bankmanagers to understand that women, both current andpotential customers, represent an interesting businesscase and bring unique market opportunities, whichmakes a women-centered design approach financiallyworth it. FAW published a range of tools in this area,
including the Female Economy Analytics report (inits 5th edition). Since 2020, the Financial Alliancefor Women has also been the technical lead for the
Women’s Financial Inclusion Data Partnership (WFID),a coalition striving to increase the use of genderdata to drive women’s financial inclusion. This work is
described under item number one in this Appendix,

15 African Development Bank, Asian Development Bank, Inter-American Development Bank, European Bank for Reconstruction andDevelopment, Islamic Development Bank, and the World Bank (including IFC).
16 https://www.we-fi.org/we-finance-code/

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

33

under WDFI activities. As part of this initiative, FAW also
convenes a Community of Gender Data Champions, agroup of national-level stakeholders from each of thesix pilot countries, to share and learn from each other’s
experiences (FAW 2022).
Similarly, Women’s World Banking (WWB) andFundación Microfinanzas BBVA (FMBBVA) work toincrease the availability of sex-disaggregated data byencouraging partner financial institutions to collect anduse it to design products and services that address the
specific needs of women and by providing resources
and tools to enable financial institutions to do so. WWB
and FMBBVA also provide technical assistance andtraining to financial institutions to help them designand deliver gender-responsive financial products.
As part of this work, both WWB and FBBVA havepublished valuable resources, including the Gender
Performance Indicators (WWB 2013) and annual social
performance reports (FMBBVA 2022) that use S-GDD.

REGI ONAL BAN KS T HAT S UP P O R T
INITI ATI V ES TO P R O M O TE WO M E N ’ S
ECO NOMI C EM P OW E R M E N T
Regional Development banks such as theAfrican Development Bank (AfDB), Inter-American
Development Bank (IDB), and Asian Development
Bank (ADB) all contribute to the availability ofsupply-side sex-disaggregated data in financial
inclusion by advocating for its collection and use,
launching initiatives to promote women’s economic
empowerment, and providing technical assistanceand support to member countries to improve theavailability and quality of sex-disaggregated data. For
example, IDB argues that financial regulators in Latin
America and the Caribbean should gradually collectsupply-side data to build a database that is harmonized
and comparable among the region’s countries(Pailhé 2018). Similarly, ADB recommends that policy
makers need to adopt and implement strategic policy
measures that target the financial inclusion of women,such as policies that support, if not mandate, thecollection of sex-disaggregated data on the usage offinancial services alongside adopting gender-specificpolicies and strategies in national financial inclusion
strategies. It also published a brief guidance note tosupport financial institutions collecting and using
sex-disaggregated data (ADB 2022).

C GAP
CGAP’s extensive work has also been instrumental
in advocating for women’s financial inclusion anddeveloping relevant resources, including:• Customer Outcomes Indicator Framework–Peers’case studies and in-field experience suggest theneed for both existing data to be leveraged better,as well as more granular disaggregation (andreporting) by providers. AFI, in particular, points outthat “Women are not a homogenous group, andeach country has to consider its national context.”
Staff skills, limitations of data systems, and overall
resource constraints were identified as some of thechallenges to detecting and understanding gender
gaps. CGAP’s Customer Outcomes methodology
attempts to mitigate the challenges arising fromthe complexity of customer-segment data. The
Indicator Framework provides a list of customercentric measures and proxies (with an intense focus
on quantitative indicators) that can be adapted forjurisdictional-specific circumstances. The approach
is well-aligned with AFI’s approach, starting with
understanding the local context. Feasibly collectible
data, relevant indicators, deep “diagnostics andanalysis” focusing on cause-and-effect (linking
indicators), ultimately yielding evidence-based(data-driven) input into strategies and policies.
• CGAP’s Customer-Centric Guide and the Customer
Segmentation Toolkits aim to help providers better
segment data, including by gender, and to develop
tailored value offers.
CGAP also convenes FinEquity, a community ofpractice focused on women’s financial inclusion, whichdeveloped a practical gender data brief (FinEquity2020) and a resource guide focused on promoting
gender analysis in financial inclusion (FinEquity 2022).

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

34

References

Alliance for Financial Inclusion (AFI). 2016 and 2022. Denarau
Action Plan on Gender Inclusive Finance. https://www.
afi-global.org/wp-content/uploads/2022/09/Denarau_
Accord-22_stg3.pdf
Alliance for Financial Inclusion (AFI). 2017a. Bridging the Gender
Gap: Promoting Women’s Financial Inclusion. https://www.
afi-global.org/wp-content/uploads/publications/2017-11/
AFI2017_Gender_full_AW_ISBN_digital.pdf
Alliance for Financial Inclusion (AFI). 2017b. Sex Disaggregated
Data Toolkit: How to Leverage Sex-DisaggregatedFinancial Inclusion Data to Accelerate Women’s Financial
Inclusion. https://www.afi-global.org/wp-content/uploads/
publications/2017-03/GuidelineNote-26%20FID%20
Gender%20Data%20Toolkit_digital.pdf
Alliance for Financial Inclusion (AFI). 2020. Guideline Note on
Sex-Disaggregated Data Report Templates. https://www.
afi-global.org/wp-content/uploads/2020/12/AFI_GN39_AW_
digital.pdf
Alliance for Financial Inclusion (AFI). 2021. Policy Framework on
MSME Data Collection: A Guide for Gender Inclusive Finance.
https://www.afi-global.org/wp-content/uploads/2021/12/
FIDSMEGender-Framework.pdf
Alliance for Financial Inclusion (AFI). 2022a. Financial
Products and Services for Women’s Financial Inclusion: A
Policy and Regulation Design Toolkit. https://www.afi-global.
org/wp-content/uploads/2022/11/Financial-Products-andServices-for-Womens-Financial-Inclusion-A-Policy-andRegulation-Design-Toolkit.pdf

Alliance for Financial Inclusion (AFI). 2022b. Integrating Genderand Women’s Financial Inclusion into National Strategies.
https://www.afi-global.org/wp-content/uploads/2022/08/
Integrating-Gender-and-Womens-Financial-Inclusion-intoNational-Strategies-V.2.1.pdf
Asian Development Bank (ADB). 2022. Financial Instruments
to Strengthen Women’s Economic Resilience to Climate
and Disaster Risks. https://www.adb.org/sites/default/files/
publication/813981/financial-instruments-women-economicresilience.pdf
Bank of Zambia (BoZ), the Alliance for Financial Inclusion(AFI), and Data2X. 2021. Towards Enabling Women’s Financial
Inclusion through Data, Zambia’s Gender Data Journey. https://
data2x.org/wp-content/uploads/2021/11/case-study-zambiafinal-version-for-publication.pdf
Better Than Cash Alliance (BTCA), Women’s World Banking, and
the World Bank G20 Global Partnership for Financial Inclusion.
2022. Advancing Women’s Digital Financial Inclusion. https://www.gpfi.org/sites/gpfi/files/sites/default/files/saudig20_
women.pdf
Better Than Cash Alliance (BTCA). 2023. Reaching Financial
Equality for Women Coalition: A 10-Point Action Plan for
Governments, Companies, and International Organizations to
Help End Women’s Economic Exclusion. https://www.weps.
org/resource/reaching-financial-equality-women-10-pointaction-plan-governments-companies-andBull, Greta. 2021. Women and Finance: Enabling Women’s
Economic Empowerment. CGAP Leadership Essay Series.
https://www.cgap.org/blog/women-and-finance-enablingwomens-economic-empowerment

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

35

Buvinic, Mayra, and Gabriela Andrade. 2019. Enabling Women’s
Financial Inclusion Through Data: The Case of Mexico. InterAmerican Development Bank. https://data2x.org/wp-content/
uploads/2019/08/WFID-Mexico-Case-Study_FINAL.pdf

Data2X and Financial Alliance for Women (FAW). 2022c.
Towards Women’s Financial Inclusion: A Gender Data
Diagnostic of Kenya. https://data2x.org/wp-content/
uploads/2022/08/DataDiagnostics-Kenya-LATEST-1-1.pdf

Buvinic, Mayra, and Rebecca Ruf. 2022. Gender Data for
Financial Inclusion: A Synthesis Brief of Diagnostics in Six
Countries. https://data2x.org/wp-content/uploads/2022/06/
Gender-Data-Financial-Inclusion-Synthesis.pdf

Data2X and Financial Alliance for Women (FAW). 2022d.
Towards Women’s Financial Inclusion: A Gender Data
Diagnostic of Nigeria. https://data2x.org/wp-content/
uploads/2022/06/06.21_DataDiagnostics-Nigeria.pdf

Cambridge SupTech Lab. 2022. State of SupTech Report 2022.
Cambridge: Cambridge Centre for Alternative Finance (CCAF),
University of Cambridge. https://lab.ccaf.io/wp-content/
uploads/2023/01/Cambridge-State-of-SupTech-Report-2022.pdf

Data2X and Financial Alliance for Women (FAW). 2022e.
Towards Women’s Financial Inclusion: A Gender Data
Diagnostic of Pakistan. https://data2x.org/wp-content/
uploads/2022/06/06.21_DataDiagnostics-Pakistan.pdf

Central Bank of Nigeria and National Financial Inclusion
Governance Committees. 2022. National Financial Inclusion
Strategy 2021–2024 https://www.cbn.gov.ng/Out/2022/CCD/
NFIS1.pdf

Data2X and Financial Alliance for Women (FAW). 2022f.
Towards Women’s Financial Inclusion: A Gender Data
Diagnostic of Turkey. https://data2x.org/wp-content/
uploads/2022/06/06.21_DataDiagnostics-Turkey.pdf

Chen, Sharon, Sebastian Doerr, Jon Frost, Leonardo
Gambacorta, and Hyun Song Shin. 2021. “The Fintech GenderGap.” BIS working paper 931, Monetary and Economic
Department of the Bank for International Settlements. https://www.bis.org/publ/work931.pdf

Data2X and Financial Alliance for Women (FAW). 2023. The
Gender Data Playbook for Women’s Financial Inclusion. https://
data2x.org/wp-content/uploads/2023/05/Gender-DataPlaybook-FINAL.pdf

Comisión para el Mercado Financiero (CMF), Regulador ySupervisor Financiero de Chile. 2022. Informe de Género en
El Sistema Financiero 2022. https://www.cmfchile.cl/portal/
estadisticas/617/articles-52460_recurso_1.pdf
Data2X. 2022. Women’s Financial Inclusion Data Dictionary.
https://data2x.org/wp-content/uploads/2022/02/WFID-DataDictionary-Feb-2022.pdf
Data2X and Financial Alliance for Women (FAW). 2022a.
Towards Women’s Financial Inclusion: A Gender Data
Diagnostic of Bangladesh. https://data2x.org/wp-content/
uploads/2022/06/06.21_DataDiagnostics-Bangladesh.pdf
Data2X and Financial Alliance for Women (FAW). 2022b.
Towards Women’s Financial Inclusion: A Gender Data
Diagnostic of Honduras. https://data2x.org/wp-content/
uploads/2022/06/06.21_DataDiagnostics-Honduras.pdf

Data2X and Global Banking Alliance for Women (GBA). 2018.
The Way Forward: How Data Can Propel Financial Inclusion
for Women. https://data2x.org/wp-content/uploads/2019/08/
The_Way_Forward.pdf
Data2X and National Bank of Rwanda (BNR). 2019. Data Driving
Women’s Financial Inclusion: Rwanda’s Experience. https://
data2x.org/wp-content/uploads/2019/09/WFID-RwandaCase-Study-v14-digital.pdf
Data2X, the Global Banking Alliance for Women (GBA), and theInter-American Development Bank (IADB). 2016. Measuring
Women’s Financial Inclusion: The Value of Sex-DisaggregatedData. https://data2x.org/wp-content/uploads/2019/08/
MeasuringWomensFinInclusion-ValueofSexDisaggData.pdf
Data2X, United Nations Foundation, and Financial Alliance for
Women (FAW). 2020. A Data-Driven Path to Women’s Financial
Inclusion: Insights from Financial Service Providers. https://
data2x.org/wp-content/uploads/2020/07/WFID-A-DataDriven-Path-to-Womens-Financial-Inclusion.pdf

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

36

Ecuador Superintendence of Banks. 2022. Resolution
No. SB-2022-1213. https://www.superbancos.gob.ec/
bancos/wp-content/uploads/downloads/2022/07/
resol-SB-2022-1213.pdf

Global Partnership for Financial Inclusion (GPFI) 2016. G20
Financial Inclusion Indicators. https://www.gpfi.org/sites/
gpfi/files/documents/G20%20Financial%20Inclusion%20
Indicators%20%282016%20Update%29.pdf

Falsini, Sophie. 2023. UNCDF Gender Disaggregated
Data Mapping Tool. UNCDF Policy Accelerator. https://policyaccelerator.uncdf.org/all/gdd-mapping-tool

Global Partnership for Financial Inclusion (GPFI). 2023. Financial
Inclusion Action Plan. https://www.gpfi.org/sites/gpfi/
files/2023%20Financial%20Inclusion%20Action%20Plan%20
for%20publication%20blue%20%28by%20Bank%20of%20
Italy%29.pdf

Financial Alliance for Women (FAW). 2021. Measuring
the Value of the Female Economy: 2021 Edition. https://financialallianceforwomen.org/download/measuring-thevalue-of-the-female-economy-2021-edition/
Financial Alliance for Women (FAW). 2022. The Data
Needed to Drive Women’s Financial Inclusion. https://financialallianceforwomen.org/news-events/the-dataneeded-to-drive-womens-financial-inclusion/
Financial Alliance for Women (FAW) and Mastercard Data
& Services. 2022. Gender Data that Matters. https://financialallianceforwomen.org/download/inbrief-gender-datathat-matters/
FinEquity. 2020. Gender Data in Financial Inclusion. https://www.findevgateway.org/sites/default/files/publications/2020/
FinEquity_GenderDataBrief_Final.11.06.2020.pdf
FinEquity. 2022. FinEquity Knowledge Guide: Gender Data
and Analysis. https://www.findevgateway.org/finequity/
guide/2022/06/finequity-knowledge-guide-gender-dataand-analysis
FinMark Trust. FinScope Consumer surveys. https://finmark.org.
za/knowledge-hub/all?utf8=%E2%9C%93&topics%5B%5D=fin
scope-consumer&button=
FinMark Trust. FinScope MSME surveys. https://finmark.org.za/
knowledge-hub/all?utf8=%E2%9C%93&topics%5B%5D=finsc
ope-msme&button=
Fundación BBVA Microfinanzas (FMBBVA). 2022. Social
Performance Report 2022: Measuring What Really Matters.
https://www.fundacionmicrofinanzasbbva.org/informes/2022/
wp-content/uploads/2023/08/2022-Social-PerformanceReport.pdf

GSM Association (GSMA). 2022. The Mobile Gender Gap
Report 2022. https://www.gsma.com/r/wp-content/
uploads/2022/06/The-Mobile-Gender-Gap-Report-2022.pdf
GSM Association (GSMA). 2023a. The State of Mobile
Internet Connectivity 2023. https://www.gsma.com/r/
wp-content/uploads/2023/10/The-State-of-Mobile-InternetConnectivity-Report-2023.pdf?utm_source=website&utm_
medium=button&utm_campaign=somic23
GSM Association (GSMA). 2023b. State of the Industry
Report on Mobile Money 2023. https://www.gsma.com/
sotir/#download
International Finance Corporation (IFC). 2017. MSME Finance
Gap: Assessment of the Shortfalls and Opportunities in
Financing Micro, Small, and Medium Enterprises in Emerging
Markets. https://openknowledge.worldbank.org/entities/
publication/ff4c9839-21ac-5676-a23a-7cf6f745df0c
International Monetary Fund (IMF). 2022. Workplan for the New
Data Gaps Initiative. https://www.imf.org/en/News/Seminars/
Conferences/DGI/about#:~:text=The%20workplan%20
covers%2014%20recommendations,administrative%20
data%2C%20and%20data%20sharing.
International Monetary Fund (IMF). 2023a. Financial Access
Survey Data Trends and Developments. https://data.imf.
org/?sk=e5dcab7e-a5ca-4892-a6ea-598b5463a34c
International Monetary Fund (IMF). Gender notes. 2023b.
Integrating Gender into IMF’s Work. https://www.imf.org/en/
Publications/gender-notes/Issues/2023/10/06/IntegratingGender-into-the-IMFs-Work-539801

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

37

Izaguirre, Juan Carlos. 2020. “Making Consumer
Protection Regulation More Customer-Centric.” CGAP
working paper. https://www.cgap.org/sites/default/files/
publications/2020_06_WorkingPaper_Making_Consumer_
Protection_Regulation_More_Customer_Centric.pdf
Izaguirre, Juan Carlos, Denise Dias, Eric Duflos, Laura Brix
Newbury, Olga Tomilova, and Myra Valenzuela. 2022. Market
Monitoring for Financial Consumer Protection. Tool 1, Analysis
of Regulatory Reports. CGAP. https://www.cgap.org/topics/
collections/market-monitoring
Ministry of Finance, Government of Chile. 2023. Chile’s
Sustainability Linked Bond Framework. https://www.
hacienda.cl/english/work-areas/international-finance/publicdebt-office/esg-bonds/sustainability-linked-bonds
Office of the United Nations Secretary-General’s Special
Advocate for Inclusive Finance for Development (UNSGSA).
2020. Collecting and Using Gender-Disaggregated Data for
Financial Policymaking: Key Findings from 11 Countries. https://www.unsgsa.org/sites/default/files/resources-files/2020-09/
Policy_Note_Gender-Disaggregated_Data_FINAL.pdf
Organisation for Economic Co-operation and Development(OECD). 2020. International Survey of Adult Financial Literacy.
https://www.oecd.org/financial/education/oecd-infe-2020international-survey-of-adult-financial-literacy.pdf
Organisation for Economic Co-operation and Development(OECD). 2023. Social Institutions & Gender Index. https://www.oecd.org/stories/gender/social-norms-and-genderdiscrimination/sigi
Pailhé, Cristina. 2018. “Sex-Disaggregated Supply-side Data
Relevant to Financial Inclusion.” Inter-American Development
Bank (IDB) discussion paper no. IDB-DP-470. https://publications.iadb.org/en/sex-disaggregated-supply-side-datarelevant-financial-inclusion
Superintendencia General de Entidades Financieras Costa Rica.
2022. El segundo informe de brechas entre hombres y mujeres
en el acceso y uso del sistema financiero en Costa Rica.
https://www.sugef.fi.cr/informacion_relevante/informe%20
brechas%20de%20genero/Informe%20Brechas%20
Financieras.pdf

Tok, Yoke Wang, and Dyna Heng. 2022. “Fintech: Financial
Inclusion or Exclusion?” IMF Working Paper no. WP/2022/080
https://www.imf.org/en/Publications/WP/Issues/2022/05/06/
Fintech-Financial-Inclusion-or-Exclusion-517619
Toronto Center. 2021. How Regulators Use Sex-disaggregated
Data and Regtech to Enhance Financial Inclusion. https://www.
torontocentre.org/videos/TC_USAID_1676254216.pdf
Women Entrepreneur Finance Initiative (We-Fi). 2022. The
Case for Investing in Women Entrepreneurs. https://we-fi.org/
wp-content/uploads/2022/06/We-Fi-Case-for-Investment.pdf
Women’s World Banking (WWB). 2013. Gender Performance
Indicators: How Well Are We Serving Women? https://www.
womensworldbanking.org/wp-content/uploads/2013/09/
Womens-World-Banking-Gender-Performance-Indicators.pdf
World Bank. 2017. Global Financial Inclusion and Consumer
Protection (FICP) Survey. https://openknowledge.worldbank.
org/entities/publication/0cf3c524-4bb6-52d6-b7b8171780158efa
World Bank. 2018a. Global Payment Systems Survey (GPSS).
https://www.worldbank.org/en/topic/financialinclusion/brief/gpss
World Bank. 2018b. IDA18 Mid-Term Review Progress Report on
Gender Equality. https://documents1.worldbank.org/curated/
en/678031542811296396/pdf/gender-ida18-mtr-paper-corrigendum-11072018-636774840407947975.pdf
World Bank. 2020a. G-20: Data Enhancement andCoordination in SME Finance: Stocktaking Report. https://www.gpfi.org/sites/gpfi/files/g20_SME_stock_2020.pdf
World Bank. 2020b. Entrepreneurship Database Project. https://www.worldbank.org/en/programs/entrepreneurship/genderWorld Bank. 2021a. Equality of Opportunity for Sexual and
Gender Minorites. https://openknowledge.worldbank.
org/entities/publication/044a2ade-a8f1-5461-ba3474613678945a
World Bank. 2021b. The Global Findex Database 2021:
Financial Inclusion, Digital Payments, and Resilience in theAge of COVID-19. https://www.worldbank.org/en/publication/
globalfindex/Report

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

38

World Bank. 2021c. World Development Report 2021: Data for
Better Lives https://www.worldbank.org/en/publication/wdr2021
World Bank. 2022. World Development Report 2022: Financefor an Equitable Recovery. https://openknowledge.worldbank.
org/entities/publication/856e3de3-cff9-5f26-8c64a7ae95f29fa6
World Bank. 2023a. Women, Business and the Law 2023. https://
openknowledge.worldbank.org/server/api/core/bitstreams/
b60c615b-09e7-46e4-84c1-bd5f4ab88903/content
World Bank. 2023b. World Bank Enterprise Surveys (WBES).
https://www.enterprisesurveys.org/en/enterprisesurveys

Supply-Side Gender-Disaggregated Data for Advancing Financial Inclusion ﻿

39CGAP members as of February 2024

Transforming Lives with Financial Inclusion

cgap.org