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chunk_16_1 | Diversity And Inclusion
The Failure of the DEI-Industrial Complex
by Lily Zheng
December 01, 2022
Amanda Berglund
Summary. Despite the increase in organizations adopting DEI initiatives and the
proliferation of DEI firms and practitioners, the big, poorly kept secret is that the
majority of these initiatives are less effective than many make them out to be. On
the one hand, there is a lack of... more
There’s a big, poorly kept secret in
the Diversity, Equity, and
Inclusion (DEI) industry: the actual efficacy of an uncomfortably
large proportion of our “flagship” services, talking points, and
interventions — unconscious bias training, racial sensitivity |
chunk_16_2 | workshops, the “business case for diversity,” resume
anonymization, and the like — is lower than many practitioners
make it out to be.
Unconscious bias training rarely changes actual behaviors and
has little impact on explicit biases. A meta-analysis of hundreds
of prejudice-reduction interventions found few that
unambiguously achieved their goals. Many popular interventions
run the risk of backlash, strong adverse reactions that sustain or
even worsen the inequity that practitioners attempt to eliminate.
Even “the business case for diversity,” a decades-old rhetorical
framing and justification for DEI work, has been found to backfire
on marginalized groups’ feelings of belonging and weaken
support for diversity programs when organizational performance
drops.
Much of the problem rests with the extreme lack of standards,
consistency, and accountability among DEI practitioners. Few of
us measure the effectiveness of our interventions, and while there
are many players in the DEI certification space, there’s little
agreement on what actual skills and competencies are necessary
to become a “good” practitioner.
The other major contributor is that organizations keep asking us
for, and funding, interventions that don’t work.
In my experience as a DEI practitioner and strategist,
organizations large and small are often eager to fund one-time,
“inspirational” events to “raise awareness” of inequity, but far less
enthusiastic about medium-to-long term interventions that
change incentive structures, shift the balance of power and
resources, or reimagine personnel processes like evaluation,
promotion, and conflict resolution. And so regardless of which
interventions actually “work,” so long as organizations continue
seeking out 60-minute unconscious bias and racial sensitivity
training full of “business case for diversity” rhetoric, practitioners |
chunk_16_3 | will keep providing it with the rationale of, “an imperfect
intervention that might not work is still better than nothing at
all.”
The result? On a macro level, organizations can take credit for
“taking action” on DEI, and DEI practitioners willing to provide
these high-demand services make their livelihoods on them. The
only losers are employees experiencing discrimination,
harassment, and exclusion, who are disproportionately likely to
be women, disabled, LGBTQ+, Black, Indigenous, and people of
color (BIPOC), and otherwise from marginalized communities,
whose negative experiences remain unchanged no matter how
many DEI trainings they sit through.
This exploitative relationship, that purports to end inequity but
instead sustains it at great cost to marginalized populations, has a
name: the DEI-Industrial Complex. And to end it, organizations
seeking DEI services must become and start acting like conscious,
high-information consumers that hold themselves and the
practitioners they work with accountable for work that
measurably decreases inequity and improves outcomes for
marginalized populations. In other words, organizations need to
make substantially different decisions from what they do at
present.
[ 1 ]
Identify DEI challenges before prescribing
DEI solutions.
Too many organizations “start” their DEI journeys with arbitrary
DEI interventions that have no clear objective. While the
widespread assumption is that a one-off DEI coaching
engagement, inspirational speaker event, or language update at
work will do no harm, employees are likely to view such |
chunk_16_4 | initiatives as an indication that the organization has committed
to a longer-term strategy — and will be understandably
disappointed and frustrated when no such thing exists.
Instead, if your organization is interested in undertaking DEI
efforts, it should start by identifying the challenges such efforts
intend to solve, so that it can match the right solutions with the
right challenges. A bystander intervention training makes more
sense if employees aren’t speaking up when they witness
discrimination. A leadership coaching engagement can be
tailored to focus on respectful communication and emotional
intelligence if the organization knows that leaders require support
in these categories. To arrive at these conclusions, your
organization should start by listening and learning through DEI
audits, employee surveys, focus groups, and other interventions
that collect valuable data required to take effective action,
including disaggregated demographic data.
The impact on the DEI-Industrial Complex? Inspirational
speakers will ideally be used less as flashy window dressing, and
when we’re brought in, it’ll be for more tactical reasons, e.g., to
help build momentum for a new strategic plan or celebrate the
achievement of a milestone.
[ 2 ]
Find the right specialist(s).
While there has recently been pushback in the industry against
“one-size-fits-all” solutions, the continuing demand from
organizations for DEI generalists incentivizes practitioners to
continue offering these exact things, and has no doubt
contributed to the rapid proliferation of cookie-cutter DEI firms
and consultancies offering virtually the same services. But
recognizing that DEI solutions should be based on DEI challenges
should lead your organization to be choosier about the specialists
it brings in to provide these solutions. For example, a purposeless |
chunk_16_5 | unconscious bias training required for all employees is almost
certainly less effective than an unconscious bias training
deployed specifically for decision-makers like hiring managers or
supervisors, to increase their familiarity with newly implemented
bias-interrupting practices like hiring panels and scoring rubrics
after an audit found evidence of bias in hiring and promotion
processes. The former service can be delivered by just about any
DEI practitioner offering unconscious bias training, while the
latter absolutely requires finding a specialist.
To find and work with such specialists that can collectively
address your organization’s DEI challenges, your organization
should take the time to thoughtfully engage in substantial
research and vetting. You should take the time to search beyond
just the most visible “DEI influencers” to seek out professionals
with the specific experience delivering the services you’re looking
for or within your industry niche, even if they’re lesser known.
Don’t forget to thoughtfully engage with and vet the practitioners
you’re considering like any other contractor — make sure you
speak with their references, for example.
The impact on the DEI-Industrial Complex? It should be harder
for opportunistic DEI firms to continue developing
undifferentiated (and often ineffective) services, and will push
current and aspiring practitioners to develop real expertise in
specific niches. It may also normalize the practices of client
referrals and community-building among specialist networks,
rather than existing practices where practitioners are incentivized
to “lay claim” to an organization and as many of its DEI needs as
possible. |
chunk_16_6 | [ 3 ]
Measure not only inputs, but outcomes.
Any DEI initiative is essentially an experiment to achieve a
particular outcome using a particular intervention. And yet, as I
mention in step 1, organizations rarely connect their DEI
initiatives to the outcomes they aim to achieve, and if they do, it’s
often in an aspirational rather than a tangible sense. A hiring
campaign to improve racial diversity is useless unless racial
diversity is measured and the stakeholders involved in its support
and deployment — hiring managers, senior leaders, DEI
practitioners — are held accountable for its outcomes. Yet,
organizations are more likely to seek out “metrics” on the
attendance and satisfaction rate of a diversity hiring seminar than
they are to seek out metrics on its long-term impact. Stakeholders
may not even formally know the initiative has “failed” until many
months or even years later, when they realize that after all the
talk, their organization’s demographics haven’t changed. The
failure to center or even measure outcomes enables exactly the
sort of one-off, unaccountable, and performative DEI work that is
so often critiqued by stakeholders.
Instead, your organization should create tangible outcomes it
aims to change tied to its DEI data and develop clear indicators
and metrics to know when those outcomes have been achieved.
For example, an effort to improve belonging should use employee
surveys to measure and benchmark belonging scores, then set
clear scoring goals for when the survey is deployed again a year
later. An effort to improve employee conflict resolution can track
the proportion of complaints resolved satisfactorily, and set
yearly goals for higher numbers. These indicators and metrics
allow an organization to hold stakeholders accountable, identify
and celebrate an initiative’s success or failure, measure return on
investment, and make important decisions to tweak or change
initiatives that aren’t working. |
chunk_16_7 | The impact on the DEI-Industrial Complex? A higher bar both for
organizations to set itself up for success by bringing on the right
specialists, and for DEI practitioners to ensure their services
meaningfully create the outcomes they chase.
[ 4 ]
Have those doing the work inform the budget
for it.
Organizational leaders often dramatically underestimate the time
and resources required to genuinely achieve diversity, equity, and
inclusion as outcomes. I’ve seen leaders earnestly schedule week-
long diversity hiring campaigns and day-long inclusion trainings
with the hopes that these will fundamentally transform their
organization, and heard countless conversations about funding
DEI that end with, “well, what’s the average salary for a Director
of Diversity?” These naïve decisions from leaders with no
experience or knowledge about DEI as a practice result in the
perpetual under-resourcing of DEI work, and force practitioners
to do too much with too little, and to take the blame for failure
when they inevitably burn out.
The simplest way to address this common failure mode is to
involve experts from the start, as you gather information and
before a budget has been decided on. These experts can help
determine timelines and budgets that will realistically allow the
right practitioners to solve the right challenges and achieve the
outcomes you’re measuring. Experts’ estimates are almost always
going to cost more and take a longer period of time compared to
the uninformed estimates of non-experts, but if organizational
leaders want success, it’s their responsibility to equip DEI
practitioners with what they need — not the job of practitioners to
make something out of nothing, with employees’ trust and
wellbeing on the line. |
chunk_16_8 | The impact on the DEI-Industrial Complex? Greater resources for
practitioners commensurate with the greater degree of specificity
and accountability attached to the budgets we request. In
addition: Lower rates of burnout, and less incentive to “race to the
bottom” and offer sub-standard services for dirt cheap.
The DEI-Industrial Complex will persist so long as there are
corporations that care more about going through the motions
than eliminating inequity and effecting actual change, as well as
practitioners that find this acceptable. But leaders of
organizations who want better can drive a higher standard for DEI
work in how they interface with the industry and its practitioners,
to seek out and engage in work that works.
Lily Zheng
is a diversity, equity, and inclusion
strategist, consultant, and speaker who works
with organizations to achieve the DEI impact
and outcomes they need. They are the author of
DEI Deconstructed: Your No-Nonsense Guide to
Doing the Work and Doing it Right. |
chunk_16_9 | Recommended For You
To Avoid DEI Backlash, Focus on Changing Systems - Not People
PODCAST
You've Made Some DEI Progress. Don't Stop Now
Why Diversity Programs Fail
To Overcome Resistance to DEI, Understand What's Driving It |
chunk_17_1 | Towards Women’s
Financial Inclusion:
A Gender Data
Diagnostic of Pakistan
Prepared for the WFID Partnership
2022
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 1
March 2022 |
chunk_17_2 | ACKNOWLEDGEMENTS
This publication was prepared for the Women’s Financial
Inclusion Data (WFID) Partnership. The Partnership thanks
the following individuals for their work on this report:
Anna Gincherman, István Szepesy, Benedikt Wahler,
and Dóra Ayumi Solymos of the Consumer Centrix
(CCX) Inclusive Business Team who conducted the
research and provided sectorial insights, and the WFID
team who worked on this study: Mayra Buvinic, Neeraja
Penumetcha, Maria Dolores Vallenilla and Denise Bonsu
from Data2X, and Inez Murray, Rebecca Ruf, and Tessa
Ruben from the Financial Alliance for Women. We also
acknowledge Ann Moline and Ernie Agtarap for their role
in the production of this report.
We thank all participants of WFID Pakistan gender
data pilot working group for their valuable insights
during the development of this diagnostic, especially
Karandaaz Pakistan and the Alliance for Financial
Inclusion (AFI). This diagnostic was made possible thanks
to the generous financial support and cooperation
from the Bill & Melinda Gates Foundation.
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 2
March 2022 |
chunk_17_3 | CONTENTS
ACKNOWLEDGEMENTS 2
ABOUT WOMEN’S FINANCIAL INCLUSION AND THE WFID PARTNERSHIP 6
ABOUT THE GENDER DATA DIAGNOSTIC 8
EXECUTIVE SUMMARY: PAKISTAN 9
OVERVIEW: WOMEN’S FINANCIAL INCLUSION IN PAKISTAN 12
BARRIERS TO WOMEN’S ACCESS TO FINANCIAL SERVICES 15
THE ROLE OF BRANCHLESS BANKING 16
ENABLING POLICY ENVIRONMENT ON WFI 17
SIZE OF THE MARKET OPPORTUNITY 19
PAKISTAN’S BANKS AND WFI 19
ROLE OF RESEARCH INSTITUTES, DONORS, AND DEVELOPMENT 22
FINANCE INSTITUTIONS
MAPPING PAKISTAN’S SUPPLY-SIDE DATA ECOSYSTEM 23
DIGGING DEEPER: GAPS AND OPPORTUNITIES IN SUPPLY-SIDE 24
DATA COLLECTION AND USE
DATA PRODUCERS 24
DATA AGGREGATORS AND USERS 26
OPPORTUNITIES: WHY A BETTER UNDERSTANDING OF HOW TO USE EXISTING 27
DATA COULD ADVANCE THE CASE
LESSONS LEARNED FROM PAKISTAN’S EXPERIENCE 28
RECOMMENDATIONS 28
APPENDIX A. FORECASTING MODEL DESCRIPTION – PAKISTAN 33
APPENDIX B. WOMEN’S MARKET OPPORTUNITY CALCULATIONS 38
REFERENCES 41
END NOTES 42
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 3
March 2022 |
chunk_17_4 | List of boxes
Box 1. PAKISTAN AT A GLANCE
Box 2. HBL’S HOLISTIC WOMEN-CENTERED STRATEGY
Box 3. SBP CONTRIBUTES TO GLOBAL KNOWLEDGE BASE ON WFI
Box 4. A PROMISING MODEL: THE UK’S INVESTING IN WOMEN CODE
List of figures
Figure 1. Stakeholder pathway to champion women’s financial inclusion
Figure 2. Modeling women’s market opportunity in Pakistan
Figure 3. WFI progress in Pakistan and the gender gap in access to finance, 2008–2020
Figure 4. Modeling of future gender gap in access to finance in Pakistan,
if no other factors change
Figure 5. Forecasting future gender gap in access to finance in Pakistan, accounting
for actions being taken and changing conditions
Figure 6. Timeline of Pakistan’s NFIS efforts
Figure 7. How Pakistani commercial banks perceive the women’s market opportunity
Figure 8. Reasons cited by FSPs for targeting women
Figure 9. Pakistan’s formal supply-side data ecosystem
Figure 10. Share of women clients among Pakistani FSPs
Figure 11. Types of gender data reported by Pakistani FSPs
List of tables
Table 1. The five pillars of SBP’s Banking on Equality policy
Table 2. Opportunities to be leveraged
Table 3. Connecting the findings from the Pakistan Gender Data Diagnostic
to data gaps and interventions
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 4
March 2022 |
chunk_17_5 | List of acronyms
A2FS Access to Finance Survey
BOE Banking on Equality policy
CCX ConsumerCentriX
DFI Development finance institutions
EMIs Electronic Money Institutions
FSP Financial service provider
GDP Gross domestic product
GEM Global Entrepreneurship Monitor
HBL Habib Bank Limited
IDB Inter-American Development Bank
IFC International Finance Corporation
IMF International Monetary Fund
KPI Key performance indicator
MFB Microfinance bank
MFI Microfinance institution / non-bank microfinance companies
MSME Micro-, small-, and medium-sized enterprises
NPL Non-performing loan
OECD Organisation for Economic Cooperation and Development
POS Point of sale
SBP State Bank of Pakistan
SECP Securities and Exchange Commission of Pakistan
UNCDF United Nations Capital Development Fund
WFI Women’s financial inclusion
WFID Women’s financial inclusion data
WSME Women-owned and women-led small and medium-sized enterprises
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 5
March 2022 |
chunk_17_6 | ABOUT WOMEN’S FINANCIAL
INCLUSION AND THE WFID
PARTNERSHIP
Global awareness and political will around women’s financial inclusion (WFI)
are at an all-time high, yet the gender gap in financial inclusion persists.
Women remain both unserved and underserved compared to men in all
segments, from bottom-of-the-pyramid to high-net-worth. These gaps
continue because of a widespread lack of awareness of the multi-trillion-
dollar opportunity to serve the women’s market. Gaps in the collection, quality,
and usage of gender data pose a major barrier to growing awareness and
developing strategies that tap into it.
Gender data is key for financial service providers (FSPs) to understand
the nature of the gender financial inclusion gap and the women’s market
opportunity and to create tailored solutions for women. It is also a critical
input for policymakers to design and monitor policy interventions that
increase women’s financial inclusion.
In 2014, against this backdrop, leading proponents of women’s financial
inclusion formed a coalition to increase the availability and use of sex-
disaggregated financial data. The Women’s Financial Inclusion Data (WFID)
Partnership includes the Alliance for Financial Inclusion (AFI), Data2X, the
European Bank for Reconstruction and Development (EBRD), the Financial
Alliance for Women, the Inter- American Development Bank (IDB), IDB Invest,
the International Finance Corporation (IFC), the International Monetary
Fund (IMF), the World Bank Group (WBG), the Organisation for Economic
Cooperation and Development (OECD), and the United Nations Capital
Development Fund (UNCDF).
The WFID Partnership is coordinated by Data2X, a United Nations Foundation
initiative. The Financial Alliance for Women is its technical lead.
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 6
March 2022 |
chunk_17_7 | THE WFID PARTNERSHIP’S
THEORY OF CHANGE
In 2017, the WFID Partnership developed a global gender data strategy with the
support of McKinsey & Company. The strategy included the WFID Partnership’s theory
of change. This theory of change holds that the production, availability, and use of sex-
disaggregated data on the demand for and supply of financial services will enable FSPs
and policymakers to take action toward closing the financial inclusion gender gap.
Data helps actors move through the WFI pathway by increasing awareness, catalyzing
action, and ultimately leading to the development of WFI champions—stakeholders
who have had an impact on WFI through either policy action or serving the market.
These WFI champions are the final stage of the funnel framework shown in Figure
1 on the next page. FSPs and policymakers move through a WFI pathway1 with five
stages: from being simply unaware of the relevance of WFI; to becoming aware of
the gaps; to considering action in response to the knowledge they have attained;
to implementing strategies to close gaps; and finally, to demonstrating impact and
becoming champions of WFI.
Figure 1. Stakeholder Pathway to Champion Women’s Financial Inclusion
WFI
Unaware Aware Consider Action Champion
Pathway
Global Data
Strategy I. Create case for change II. Move to III. Track &
action prove impact
Themes
IV. Build foundational data capabilities
The WFID Partnership’s theory of change is based on the significant role that data
can play in moving actors and organizations along this pathway. With more and
improved sex-disaggregated financial data, policymakers can design and monitor
WFI interventions, and FSPs can both see the market opportunity and build a
business case for targeting women as clients.
The strategy also found that many of the global and national-level data gaps are on
the supply-side versus the demand-side. In addition, the strategy stressed that the
development of gender data is most effective in improving WFI if efforts are at the
national level versus the international level; as the process of creating awareness
encourages local players to act and move through the pathway.
From 2020–2022, WFID is working in six countries (Bangladesh, Honduras, Kenya,
Nigeria, Pakistan, and Turkey) to test its theory of change and develop gender data
supply-side interventions to increase women’s financial inclusion in partnership with
the public and private sectors.
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chunk_17_8 | ABOUT THE GENDER
DATA DIAGNOSTIC
Before designing interventions, the WFID partnership undertook
diagnostics of each of the six pilot countries to understand the
state of gender data at the national level. This diagnostic includes
mapping the data value chain, understanding what is being tracked
and by whom, identifying gaps and opportunities in gender data
collection, and developing recommendations for areas
of intervention. This entailed the following activities:
• Reviewing existing literature;
• Conducting a survey of a majority of FSPs in each
nation’s financial sector;
• Interviewing public, private, and non-governmental
stakeholders;
• Conducting comprehensive modeling to estimate
the women’s market opportunity in each country
(see Appendix A); and
• Conducting predictive modeling to estimate the
WFI gap in the future (see Appendix B).
Although the diagnostics were developed as part of the WFID
Partnership’s intervention plans, they can also become a blueprint
for governments, FSPs, and other stakeholders who are interested
in improving their own gender data ecosystems.
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chunk_17_9 | EXECUTIVE SUMMARY: PAKISTAN
In a nation that had one of the world’s lowest
levels of financial access just over a decade
By the numbers:
ago, there is now strong political will and The scope of the untapped
momentum for change. As part of a broader opportunity in women’s
push for economic development and growth, financial services in
the government has prioritized increased Pakistan
women’s financial inclusion (WFI). It has done
82%
so by reforming policies and implementing
Of Pakistani women remain
initiatives such as branchless banking and digitized unbanked or underserved by
government subsidy programs. The numbers financial services
show that the gender focus is making a difference.
More than $650 M
Women’s account ownership has more than
(PKR 101 B)
quadrupled since 2008, when the first inclusion
Potential annual banking revenue
policies were put in place: from 4 percent in 2008 from expanding financial services
offerings for women customers
to 18 percent in 2020.
across segments
Despite this progress, 82 percent of Pakistani
women remain unbanked and the gender gap in
access that had started to shrink is expanding.2 Policies that increase WFI would foster
greater stability in the banking system and enhance economic growth. This would
translate into more effective monetary and fiscal policies.3
For Pakistan’s FSPs, expanding financial services offerings to women customers would
mean a market opportunity of more than $650 million (101 billion Pakistani rupees (PKR))
(Figure 2).
The government’s commitment to action on WFI continues to grow, along with a
heightened focus on data. A regulatory mandate in place since 2017 requiring sex-
disaggregated reporting has significantly increased the availability and quality of supply-
side sex-disaggregated data. It should support evidence-based decision making, driving
further progressive policy actions.
Figure 2 - Modeling women’s market opportunity in Pakistan
Unbanked / Annual revenue
Segments and average monthly income in USD Description of underserved opportunity
women’s segment women (total unbanked and
underserved
• 12% women (within segm)
5% A • 43% employed, 10% self-employed
US$ 97+ • Education: 27% less than primary, 44% primary/ 1.7 / 0.35 Mn $124Mn
PKR 15,000+ secondary, 29% diploma PKR 19.2Bn
4% B • 10% women (within segm)
US$ 65-97 • 42% employed, 16% self-employed
PKR 10,000-15,000 • Education: 38% less than primary, 56% primary/ 2.4 / 0.23 Mn $106Mn
secondary, 6% diploma PKR 16.3Bn
C • 14% women (within segm)
9% US$ 32-65 • 25% employed, 9% self-employed
PKR 5,000-10,000 • Education: 51% less than primary, 39% primary/ 5 / 0.74 Mn $101Mn
secondary, 10% diploma PKR 15.7Bn
• 78% women (within segm)
D • 2% employed, 2% self-employed
82% < US$ 32 • Education: 49% less than
primary, 46% primary/secondary,
< PKR 5,000 5% diploma
$320Mn
49.5 / 5.3 Mn PKR 49.5Bn
Socioeconomic segments based on monthly income Source: CCX calculations based on A2FS 2015 data
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chunk_17_10 | In another sign of Pakistan’s growing commitment to WFI, the State Bank of Pakistan
(SBP), the nation’s regulator, recently launched its Banking on Equality (BOE) policy.
The policy aims to reduce the gender gap in financial inclusion by promoting inclusive
business practices in the financial sector. With a focus on gender- and transgender-
sensitivity, the policy sets out short-, medium-, and long-term targets for financial
institutions. The initiative includes establishing a forum on gender and finance,
with the goal of reviewing and improving the existing policy framework. It also
places an emphasis on SBP’s collection and analysis of more robust and detailed
sex-disaggregated data.
This will be aided by a recent shift in core banking systems to cloud-based platforms,
which has enhanced the quality and reliability of data being produced. Today, most
Pakistani FSPs can generate good quality sex-disaggregated data for retail customers,
sole proprietorships, and—to an extent—women-led small and medium companies
(WSMEs).
Despite the availability of good quality sex-disaggregated data, required reporting, and
the market opportunity, many FSPs do not include sex-disaggregated data in their
own reporting to management or in their decision making processes on the types
of offerings to provide to clients. While some FSPs have launched women-centered
offerings, data did not seem to play a significant role when doing so. Among FSPs
interviewed, many indicated an interest in learning more about how to best leverage
sex-disaggregated data to inform decisions. Many Pakistani FSPs also stated that they
would welcome data-driven, quantitative evidence of the value of women’s market.
SBP also has an opportunity to build on the momentum to further optimize the use
of available data. For example, additional data analysis could yield market-level
insights that FSPs could use to gain a deeper understanding of the market opportunity.
This also would enhance the business case for WFI.
Interviews with SBP and other data-aggregating institutions revealed a strong
appetite for strengthening the quality of supply-side data and understanding more
about how to generate actionable insights. They expressed interest in using this data
to underpin policy design and drive additional progress on women’s financial inclusion.
With SBP’s clear commitment to WFI, as evidenced by the new BOE policy, and FSPs
appetite for data-driven insights, Pakistan is well-positioned to strengthen its supply-
side gender data. In turn, this will enable the creation of banking products and services
that meet the needs of women and further women’s financial inclusion.
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chunk_17_11 | To drive action and move more banks and the regulator further along the WFI pathway,
priority efforts should focus on several recommendations already identified in the new
BOE policy, including:
• Enabling easier access to SBP supply-side data for commercial FSPs through
regularly published reports so it can be used to its full potential, including
for competitor benchmarking.
• Proposing robust sex-disaggregated data collection.
• Incentivizing efforts to serve the female customer base, for example by
building gender targets into management key performance indicators (KPIs).
Additional recommendations drawn from our diagnostic include:
• Building stronger industry alignment on WFI through sharing use-cases or
developing industry code.
• Pursuing other interventions to move FSPs and SBP forward along the WFI
pathway proposed in Table 3, page 25.
• Building data analysis capacity for industry players and regulators, promoting
incorporation of data into FSP management reports, and encouraging data
analysis for business development.
• Providing technical support to upgrade system capabilities.
• Leveraging available data to build capacity on scaling value propositions
to individual women customers and female business owners.
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chunk_17_12 | OVERVIEW: WOMEN’S FINANCIAL
INCLUSION IN PAKISTAN
Pakistan, a lower-middle income South Asian nation, has succeeded in more than tripling its overall
financial inclusion in recent years. From a mere 10 percent of the population in 2008, formal
account ownership stood at 35 percent as of 2020.4 Women’s account ownership more than
quadrupled during this same period, from 4 percent in 2008 to 18 percent in 2020.
The introduction and expansion of branchless banking, the digitization of government subsidy
programs, and the government’s strong focus on financial inclusion have all contributed
significantly to the WFI progress made thus far.
Box 1. PAKISTAN AT A GLANCE23
ECONOMY
• Textiles is a key industry sector: more than 420 textile companies, representing
nearly half of all manufacturers and providing half of all export earnings
• Remittances accounted for almost 10% of 2020 GDP
• Negative GDP growth in 2020/21 due to COVID-19
SOCIOECONOMIC STATUS
• Among most populous countries in the world; growing youth population
• 5% of residents live on $1.90/day or less
• Economic impact of COVID-19 may push 2 million more Pakistanis into poverty
• 47% overall literacy rate for women; 71% for men
• 21.3% of women are in the labor force22
• 34% of Pakistani girls attend high school; only 8% enrolled in post-secondary courses
• World Economic Forum gender gap rank: 153 out of 156 countries in the world
WOMEN IN BUSINESS
• 1% of Pakistani women are entrepreneurs, the world’s lowest rate
• Pakistani women earn 26% less than men
• Women represent only 5% of managers in Pakistani firms
FINANCIAL INCLUSION
• 35% of Pakistanis hold formal bank accounts
• 18% of Pakistani women hold formal bank accounts
• 32% gender gap in active account ownership
• 2% of women have mobile money accounts (as of 2014)
• 6% of Pakistanis have saved and 2% have borrowed from financial institutions
• 2% of Pakistani women have saved and 1.5% have borrowed from financial institutions
• 70% of surveyed commercial banks reported having women-focused products and services
WOMEN’S VOICE & PARTICIPATION
• Pakistan has had one female head of state
• 20% of Pakistan’s parliamentarians are women
• 11% of government ministers are women
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chunk_17_13 | Despite the WFI progress that has
been made, a substantial majority KEY TAKEAWAYS
of Pakistani women—82 percent—
• Pakistan is making headway on
remain unbanked or financially
WFI; however, a large majority
underserved.
of women remain unbanked.
What the data reveals about
• Government emphasis on WFI
closing the gender gap in has contributed significantly to
access to finance its progress, including policy
mandates and actions, requiring
Calculations using supply-side data
monthly sex-disaggregated
revealed that while women’s access to reporting since 2017, which has
banking services increased by nearly vastly increased the availability
14 percentage points in the period of good quality data.
2008–2020, the gender gap has
• The digitization of government
more than doubled during the same
subsidies to low-income women
period.5 (See Figure 3.)
has contributed to the expansion
of Pakistan’s branchless banking
Looking ahead, calculations using
industry and increased WFI.
demand-side data show that WFI
growth will flatten in the next decade • Some FSPs acknowledge the
if key actions are not taken, as importance of serving women
shown in Figure 4. Figure 5 presents and have launched women’s
a more realistic scenario, in which market offerings with positive
results.
WFI could significantly improve if
average levels of access are matched
• FSPs do not yet use available data
by improvements in the predictive
to yield insights into women
model’s key financial inclusion drivers:
customer behaviors or market
access to education, income from trends.
farming, salary or business, ownership
of a mobile phone, and proximity to • Increased use of supply-side
data could accelerate FSP and
a mobile money agent.6 However, if
regulator advancement along
women are not targeted specifically,
the WFI pathway by quantifying
the gender gap in access to finance
the business case and yielding
will not close in the next decade.
market-level insights.
• Local and international
institutions have played an
important role in advancing the
WFI agenda and improving the
gender data landscape.
• Data insights have informed
additional policy enhancements,
validating the WFID theory of
change.
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chunk_17_14 | Figure 3. WFI progress in Pakistan and the gender gap in access to finance, 2008–2020
A2FS bank acc’t ownership SBP Unique number of active account holders (18+)
60%
32%
30%
27% 50%
50%
23% 20% 44%
40%
40%
34% 34%
30%
12%
20% 16% 18%
14% 13% 14%
11%
10%
4%
0%
2008 2015 2017 2018 2019 2020
Men Women Gender gap
Data sources: 2008–2016: FinMarkTrust/Access to Finance Survey; 2017–2020: State Bank of Pakistan
Figure 4. Modeling of future gender gap in access Figure 5. Modeling of future gender gap in access
to finance in Pakistan, if no other factors change to finance in Pakistan, accounting for actions
being taken and changing conditions
60% 60%
50% 50%
40% 40%
30% 30%
20% 20%
10% 10%
Men Women Men Women
0% 0%
2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
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chunk_17_15 | BARRIERS TO WOMEN’S “Women’s equal access to
financial services is a key
ACCESS TO FINANCIAL
priority for a country like
SERVICES
Pakistan whose female
Women in Pakistan face several barriers in population of more than
accessing financial services: gender biases 100 million significantly
among FSP staff and management, low lags behind men in terms
labor force participation of women, a lack of of financial inclusion and
geographic proximity to banks, and limited contribution to economic
education and financial skills. activity.”
For example, research conducted in 2017 by – Dr. Reza Baqir, Governor, SBP,
as quoted in TheNews.pk, March 9, 2021
IFC and Habib Bank Limited (HBL)—Pakistan’s
largest commercial bank—found that many
women were reluctant to access financial services at bank branches because male
bank staff did not treat them with respect.7
In addition, just 23 percent of Pakistani women participate in the labor force, with most
of these workers in the low-paying agricultural sector.8 The nation also has a 1 percent
rate of women‘s entrepreneurship which is one of the lowest rates in the world—
far lower than the 21 percent rate of entrepreneurial activity among Pakistani men.
Women’s low level of economic participation is a major reason for the large numbers
of unbanked women.9
Another barrier is lack of geographic proximity to a bank. In a country where more
than 60 percent of the population live in rural areas—and where road and transport
networks are unreliable—many women cannot access a bank branch.10
Lack of education represents another significant barrier. As in many countries, Pakistani
women with limited access to education are less likely to have basic financial skills and
far more likely to be financially excluded than educated women.11
All these issues are either caused or compounded by social norms around appropriate
roles and behaviors of women and men in society. In many parts of the country,
women cannot interact in a bank branch or agent without being accompanied by
another adult. In many communities, girls are more likely to be taken out of school
than boys before finishing their second level, and getting more women to work in
FSP customer-facing roles is challenging. The financial sector can play a significant
role in changing social norms by instituting progressive gender diversity and inclusion
strategies in their own organizations. In doing so, they will not only lead by example
but also become more effective at reaching and impacting the women’s market.
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chunk_17_16 | THE ROLE OF BRANCHLESS BANKING
In tandem with the policy interventions that have prioritized gender, the entry of
branchless banking and digital payments into the financial services ecosystem
has been instrumental in expanding women’s access to formal financial services
in Pakistan.
Branchless banking offers more flexibility for account holders who cannot access
a brick-and-mortar location, and digital payment systems—originally intended as a
way of improving security and reducing fraud, waste, and abuse—have had the added
benefit of increasing WFI. For example, the government is in the process of automat-
ing and digitizing the social safety net program known as the Benazir Income Support
Program, which provides subsidies for low-income women. As part of this effort,
beneficiaries will receive smart cards linked to simple bank accounts, moving millions
of previously unbanked women into the ranks of the banked.
Although many women still receive their government subsidies by way of a money or-
der delivered in the mail each month, some six million Pakistani women have already
started receiving benefits electronically and have set up basic accounts at partici-
pating banks HBL and Bank Alfalah. In turn, this has expanded these banks’ footprint
in the women’s market. Once complete, the digitization initiative will require all benefi-
ciaries to open a full-fledged account at the bank of their choice.
A second related initiative, enabled by the
2008 branchless banking policy, facilitates “I want to remind our
the electronic payment of wages and salaries. banker friends that this
Pre-COVID, the government had set a target [new Banking on Equality]
of digitizing 100 percent of all government policy is not only the right
payments and receipts (Government to Per- thing to do, but it’s an area
son, Person to Government, Government to where…there are financial
Business, Business to Government) by 2023. interests for you as well.”
While it may not meet 100 percent of the
– Dr. Raza Baqir, Governor, SBP, at press
target, it is well on its way to doing so. As of
conference launching the new policy
March 2021, branchless bank operators held
66.5 million accounts, of which 25 percent
are owned by women, almost half of them subsidy recipients.12
The shift to digital platforms has also made a profound difference in the availability
of sex-disaggregated data. Electronic systems make it easier to generate and collect
anonymized, individual account-level gender data, enabling more visibility into the
behavior of women customer segments.
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chunk_17_17 | ENABLING POLICY ENVIRONMENT ON WFI
By enacting progressive laws and policies, Pakistan’s government and SBP have
driven tangible progress on WFI and increased the availability of gender data. In
2008, the banking regulator SBP introduced a sweeping change: a branchless banking
policy that enabled banks to offer services through a network of agents, making it easy
for customers to open and manage simple accounts without setting foot in a bank
branch. This action catalyzed initial momentum on inclusion, sparking a marked in-
crease in the overall number of Pakistani citizens with accounts. Subsequently, in 2015,
the government collaborated with SBP to introduce the National Financial Inclusion
Strategy, with women’s financial inclusion designated as a specific priority. The initial
strategy envisioned that at least 25 percent of adult women would hold a formal fi-
nancial account by 2020. Government officials updated the strategy in 2018, adjusting
the targets with a goal of 65 million total active digital transaction accounts, with 20
million accounts by women (about 29 percent of the female population, ages 14 and
up), including digital accounts, by 2023.13
In 2017, SBP began mandating six-monthly sex-disaggregated data reporting of
unique account holder data from regulated FSPs. This requirement has transformed
the sex-disaggregated data landscape in Pakistan. The availability of quality data has
allowed for more accurate measuring of progress on WFI, benchmarking against
government inclusion targets, and evidence-based identification of areas where im-
provement is needed. It has enabled the reliable sizing of the women’s market oppor-
tunity and has helped inform decisions on future policies. One of the major initiatives
under NFIS was the launch of National Financial Literacy Program that imparts basic
financial literacy to unbanked/underserved population. The program has a mandate to
cover 50% of women to be financially literate under this program.
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chunk_17_18 | A new Banking on Equality policy, launched in September 2021, continues this prog-
ress (see timeline on Figure 6 below). It weaves a gender perspective into the policy’s
five-pillar strategy, as shown in Table 1. Designed to catalyze market and societal
change, it features a strong push for FSPs to:
• Build a gender-diverse employee base and in all touch points with customers;
• Integrate women-centric products and implement strategies to target women
customers;
• Collect and analyze sex-disaggregated data;
• Establish KPIs and targets; and
• Set up a policy forum to encourage more effective policy design.
This multi-faced approach validates the WFID Partnership’s theory of change and
demonstrates the importance of sex-disaggregated data for regulators, from raising
awareness to driving policy decisions aimed at increasing WFI.
Table 1: The five pillars of SBP’s Banking on Equality policy14
GENDER WOMEN WOMEN ROBUST POLICY
DIVERSITY IN CENTRIC CHAMPIONS SEX- FORUM ON
FINANCIAL PRODUCTS AT ALL DISAGGREGATED GENDER &
INSTITUTIONS & TARGET TOUCH DATA FINANCE
AND THEIR OUTREACH POINTS COLLECTION
ACCESS AND TARGET
POINTS SETTING
Figure 6 - Timeline of Pakistan’s NFIS efforts
Updated NFIS as part of the GoP’s
100-days agenda with Launch of BOE policy
targets for 2023
2018 2021
2015 2017 2020
Launch of National Financial Literacy
Launch of NFIS in collaboration
Program (NFLP) and collection of Draft BOE policy
with the World Bank
disaggregated data of bank accounts
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chunk_17_19 | SIZE OF THE MARKET OPPORTUNITY
The market sizing undertaken for this
diagnostic estimated an annual USD Box 2. HBL’s Holistic
$650 million (PKR 101 billion) revenue Women-Centered Strategy19
opportunity for Pakistani FSPs if they
HBL launched its women-centered
effectively target the women’s market.
initiative in 2016 to better serve
There is plenty of opportunity in all
women’s financial needs. Through
women segments, including from the
the Nisa program, HBL offers a
5 percent of the female population
complete suite of financial services
earning more than $97 per month. This
for women, along with value-added
segment alone represents a $124 million
services such as insurance, credit
opportunity. At the other end of the
guarantees, and a financial literacy
spectrum, the 82 percent of the female
toolkit. Internally, the bank focused
population earning less than $32 per
on creating an inclusive workplace
month (including those in the informal
culture and hiring a more gender-
and formal economies) represents a
diverse staff, particularly at branches,
$320 million opportunity. (See Figure
which has put female customers
2). In addition, all government subsidy
at ease. HBL also strengthened its
beneficiaries will soon be required to
internal female leadership pipeline, to
open full bank accounts, into which
enable gender-diverse perspectives
subsidy payments will flow, enabling more
in decision making.
access for women and an additional FSP
opportunity.
Results:
PAKISTAN’S BANKS • 3.3 million women customers,
AND WFI 650,000 of whom participate in
the Nisa program
Pakistan’s banks are beginning to
• 1.8 times more female employees
recognize the strategic importance of
in 2020 than in 2010
serving the women’s market. To an ex-
• 2 times more women in
tent, FSPs recognize that it makes good
management since 2010
business sense to address the women’s
market. After all, women represent nearly
50 percent of the adult Pakistani population, and the government is clearly prioritizing
inclusion through its policy actions.
Seven out of nine commercial banks surveyed for this diagnostic cited growth in their
customer base as a key reason for wanting to target a new or underserved segment
(Figure 8). Half of the banks interviewed saw women as a core element of their growth
strategy, as either new or existing customers.
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chunk_17_20 | Availability of women-focused offerings
While 75 percent of the surveyed banks stated that they have launched women-
focused offerings, most are standalone products and not part of a broader strategic
effort to target the women’s market (Figure 7). However, some FSPs are embracing
the value of a holistic women-centered strategy across segments and business
lines—with good business results. For example, HBL, a member of the Financial
Alliance for Women, launched Nisa, a comprehensive women’s banking program more
than five years ago—the only such initiative in Pakistan to date. At the same time, it
looked inward, to enhance diversity and inclusion in its own operations. The bank is
experiencing tangible gains from these efforts. (See Box 2.)
For microfinance banks, women customers remain a core component of their strate-
gy: non-bank microfinance companies (microfinance institutions, or MFIs) have more
than 50 percent female borrowers, while women represent 25 percent of microfinance
bank (MFB) customers. However, among the 40-plus non-bank MFIs and 11 MFBs that
operate in Pakistan, most have not developed solutions specifically tailored to meet
the needs of women. Exceptions include MFIs such as the Kashf Foundation, with a
mission specifically focused on WFI.
Among the branchless banking operators, some have launched women-focused
propositions, also with strong results. For example, JazzCash’s strategic approach
includes women-friendly products such as community savings, maternity and tele-
health insurance, quick loans, women-oriented communications and outreach, a more
user-friendly app, and financial literacy tutorials. The result was a 55 percent increase
in the number of women clients since the launch of the initiative in 2016.
Still, concerns about scaling and
“We have launched some
mainstreaming women’s market offerings
products, but making the
remain. When questioned on the reasons
business case for serving
why they haven’t progressed further in
the women’s market across
their WFI pathway, most FSP respondents
various segments remains
said that they needed more evidence of the
a tough sell.”
business case.
– FSP survey respondent
Providing guidance on how to use the
data already available to FSPs to quantify
the business case for serving women could play an important role here. So, too,
could encouraging the collection and analysis of timely and granular data on the
transactional behavior of women customers by segment. The insights generated
from such analysis could give FSPs the evidence they need to move from small, siloed
offerings to scalable and profitable comprehensive women’s market solutions that
include both financial and nonfinancial services that women need to succeed—access
to finance, financial and business education, networking, and recognition.
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chunk_17_21 | Figure 7. How Pakistani commercial banks perceive the women’s market opportunity
0% 10% 20% 30% 40% 50% 60% 70% 80%
What best describes
your institution’s Women are a core element of
our strategy and we launched
perspective dedicated product(s) for them
on women as
We see women as an opportunity
customers for for which we are actively
considering a dedicated approach
financial services?
We have launched a product for
women, but they are not a core
Share of FSPs part of our strategy
Figure 8. Reasons cited by FSPs for targeting women
0% 10% 20% 30% 40% 50% 60% 70% 80%
Why did your To grow our customer base
by targeting a new or unserved
institution choose segment
to target women as
To increase our engagement
a business priority? of existing customers / expand
cross-sell opportunities
Corporate social responsibility
(multiple selection) initiative
Share of FSPs
To differentiate ourselves from
the competition
To improve profitability
Other (please specify)
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chunk_17_22 | ROLE OF RESEARCH INSTITUTES, DONORS,
AND DEVELOPMENT FINANCE INSTITUTIONS
Local and international organizations, donors, and development finance
institutions are playing an important role in advancing women’s financial
inclusion and increasing sex-disaggregated data collection in Pakistan.
They are providing significant levels of funding and expertise. And they are
supporting FSPs in developing women-centered financial solutions. Among
the activities making a difference:
• Research and data generation: The World Bank is conducting an
analysis of the government subsidy beneficiary base for insights
into their needs and behaviors. Other institutions such as IFC are
undertaking research as well, aimed at building the business case
for increased industry focus on the female economy. Efforts also
include a quantitative study on the WSME market from Karandaaz and
Microfinance Strategy, and InterMedia’s Financial Inclusion Insights.
• Support for regulatory changes: The World Bank, the Alliance for
Financial Inclusion, and the Bill & Melinda Gates Foundation, among
others, provide guidance and support on policy interventions to boost
WFI.
• Capacity building for FSPs: IFC, Financial Alliance for Women,
Women’s World Banking, the Asia Development Bank, the Pakistan
Microfinance Network, and the United Kingdom’s Foreign,
Commonwealth & Development Office, among others, provide advice
and guidance to Pakistani Banks. HBL is a member of the Financial
Alliance for Women.
• Financial literacy training: Institutions are partnering with the Pakistan
Microfinance Network to develop training modules for subsidy
beneficiaries on financial literacy. These training resources will be
helpful to FSPs as they seek to provide additional services beyond the
payment delivery itself.
• Funding to support increased WFI: Several institutions have provided
grant funding and mechanisms such as credit guarantees to increase
the availability of financial services for women, including by expanding
the branchless banking industry.
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chunk_17_23 | MAPPING PAKISTAN’S SUPPLY-SIDE
DATA ECOSYSTEM
The primary stakeholders in Pakistan’s financial services sector include:
Data producers/financial service providers
• Commercial banks
• Development finance institutions
• Exchange companies
• Microfinance banks (MFBs) and their branchless banking affiliates
• Fintechs/mobile money operators (MMOs)/non-bank finance companies
(NBFCs)
• Insurance companies
• Modarabas (specialty Islamic finance companies)
Data users/aggregators
• SBP: Regulates commercial banks, development finance institutions, exchange
companies, and microfinance banks/branchless banking operators
• Securities and Exchange Commission of Pakistan (SECP): Regulates non-bank
finance companies, insurance companies, and modarabas
There is little detail available about the informal financial services sector in Pakistan.
Figure 9 provides an overview of the data flow between the stakeholders in Pakistan’s
formal supply-side data ecosystem. The blue arrows indicate where the data reported
is disaggregated by sex.
Figure 9. Pakistan’s formal supply-side data ecosystem
Bankers+ Fintech Ministries & Data reporting
MFB Credit Bureaus (2) MNOs
Associations Agencies
Association
Data reporting gender disagg.
Data generated by usage
Regulators FSPs
Data provider / reporter
SBP-regulated SECP-regulated
State Bank Data user
of Pakistan Commercial Banks (33)
DFIs (9)
Exchange Companies
(52)
MFBs (11) NBFCs (25 NBMFCs)
SECP Electronic Money
Institutions (EMIs) (11) Insurance Companies
Modaraba Compnies
Donors / Impact
Investors PMN
Investors
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chunk_17_24 | DIGGING DEEPER: GAPS AND
OPPORTUNITIES IN SUPPLY-SIDE
DATA COLLECTION AND USE
This section details the state of
supply-side data collection and use in KEY TAKEAWAYS
Pakistan. It highlights gaps and uncovers
• All FSPs regulated by SBP generate
opportunities to optimize the potential of
account-level sex-disaggregated data
the data to provide insights on female on retail customers and most on sole
proprietors but only a few track WSMEs.
customer behavior.
• SBP collects banks’ account ownership
data but does not gather performance
DATA PRODUCERS metrics such as non-performing loans.
• SBP’s gender data is reported internally
Combined, banks and MFIs have the although it is not part of mainstream
largest share of women customers reporting; new Banking on Equality
policy paves the way for increased use
among the financially included segment
of data insights to inform policy.
in Pakistan (Figure 10). However, in the
• Real-time transactional data can be sex-
coming years fintechs are expected to disaggregated but remains untracked.
play an increasingly important role. • There are significant opportunities to
make better use of existing data to yield
Banks and MFIs actionable insights and validate the
theory of change.
Virtually all banks and MFIs generate
sex-disaggregated account
ownership data on retail clients
Figure 10. Share of women clients
and sole proprietors, as mandated
among Pakistani FSPs (%)
by SBP. Nearly 80 percent of
Branchless
commercial banks track sex for all Banking accounts 25%
products offered, while 60 percent
Depositors with
of MFIs do so. A minority of the commercial banks 31%
interviewed banks and MFIs—about 22
Loan accounts with
percent—track data on WSMEs. This Microfinance banks 37%
represents a significant gap, given the
Non-bank
growing donor focus on women’s microfinance 50%
entrepreneurship, and expectations companies
0% 10% 20% 30% 40% 50%
that WSME demand will increase in the
coming years.
Many FSPs have the capacity to run sex-disaggregated reports at a somewhat granular
level, including loans by number and value, and deposits/savings accounts by value.
Seventy-one percent can generate sex-disaggregated loan loss statistics, while 43
percent can generate sex-disaggregated revenue data (Figure 11). Most FSPs also have
the ability to generate real-time transactional data; however, among those interviewed,
it appeared that they are not making use of it. Doing so would provide even greater
insight into the ways in which women customers use their accounts and could
contribute to more evidence-based decision making on the types of products to offer.
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chunk_17_25 | Those interviewed did not report data quality as a major issue, since widespread adoption of
electronic platforms and automated data collection has enhanced reliability and reduced the
risk of recording errors. However, issues do remain, particularly around proxy use—in which men
applying for loans put down a woman’s name as the applicant—and the lack of data on WSMEs.
Figure 11. Types of sex-disaggregated data reported by Pakistani FSPs
What types of reports does your institution have available split by women and men?
Share of respondents of those that have sex-disaggregated customer reports
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Accounts Transactions Number of Customers Loans Loans Deposit / savings NPLs / Loan Revenue Net interest Customer
(by number) Products (by number) (by value) accounts Loss statistics Margin Lifetime
(by value) Value
Retail clients Retail and business clients Neither NA
Disconnect between data availability and usage
“We have the capacity
Despite decent data capabilities, less than 40 percent to generate all of this
of FSPs include sex-disaggregated data in their regular, information and we are
automated management reporting, while 50 percent obligated to report it
report the data to management only on occasion. to SBP. But we are not
Because senior decision makers may not see the data or obligated to report it to
any insights derived—for example, on product uptake by management. And we
women customers—they might not realize the strength of definitely do not run
the business case in support of investing in new women- analytics on it.”
focused offerings or in the value women customers bring.
– Bank representative
Fintechs, mobile money, and non-bank financial
companies
In interviews, representatives from these FSPs indicated that they do not have a sense of the size of
the market opportunity. They typically target those who are already banked, rather than focusing
on attracting the unbanked, where most women are.
While institutions currently produce sex-disaggregated data on retail and business customers,
they are not required to report it to SECP, their regulator. Although the data is available, only
about 33 percent include it as part of regular or occasional reporting to management. These
include institutions such as Tez, Oraan, and Finca that have WFI embedded in their missions.
These institutions collect and analyze their sex-disaggregated data to support the business case
for serving the women’s market.
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chunk_17_26 | DATA AGGREGATORS AND USERS
State Bank of Pakistan
Various SBP departments collect
Box 3. SBP contributes
sex-disaggregated data on account
to global knowledge base
ownership. With the exception of the
on WFI20
unique depositor’s report, most data is
collected at the aggregate level. For SBP has provided sex-disaggregated
example, FSPs report the overall number data for the International Monetary
of accounts, as opposed to detailed, Fund’s highly respected annual
customer-level data, risking double- Financial Access Survey (FAS) since
counting individuals with multiple 2015. Through the years, it has
accounts. Each SBP department sets its increased the extent of detail it has
own collection schedule, so some data reported in a sex-disaggregated way:
streams are reported annually while
others are semi-annual, quarterly, or • Since 2015: commercial bank
monthly. SBP makes use of the data depositors, deposit accounts and
collected in its own internal reporting, borrowers
although not all of it is available publicly, • Since 2017: commercial bank loan
not providing the FSPs access to the accounts, outstanding loans, and
industry-level data. outstanding deposits
• Since 2018: depositors, deposit
While the regulator demonstrates
accounts, loan accounts,
a strong commitment to sex-
outstanding deposits, and
disaggregated data collection and use,
outstanding loans from deposit-
there are areas where changes could
taking microfinance institutions;
further enhance the value of the data.
borrowers and outstanding loans
For example:
from non-bank microfinance
• SBP does not currently require companies
reporting of sex-disaggregated
transactional data, which could
provide stronger evidence of the value of women customers.
• Aggregate-level reporting increases the risk of inclusion numbers not being
accurate, since some women hold more than one account.
• Differing data collection schedules set by various SBP departments makes it
harder to consolidate data to produce comprehensive and timely overviews
of women customer segments.
• SBP does not publish data insights, so FSPs do not have access to market-level
sex-disaggregated data that could be used to benchmark performance or
provide intelligence on women customer behaviors and performance.
The regulator is aware of these shortcomings and has taken steps to address them.
The new Banking on Equality policy emphasizes collecting sex-disaggregated data
in more granular detail, standardized frequency in reporting, and increased use of
sex-disaggregated data for insights that will inform future policies and initiatives.
Plans also include publishing annual data insights and analysis, such as a sex-
disaggregated overview of the unique number of depositors.
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chunk_17_27 | Securities and Exchange Commission of Pakistan
SECP does not gather sex-disaggregated data from the institutions it regulates, and
SBP’s new Banking on Equality policy prescriptions will not apply to SECP-regulated
FSPs. However, SECP has indicated plans to adopt a similar gender policy for the
non-banking financial sector that will mandate sex-disaggregated data reporting.
A donor-supported digital transformation initiative currently under way will enable
more extensive data analysis in the next few years. This will contribute to a more
comprehensive understanding of the state of WFI in Pakistan.
OPPORTUNITIES: WHY A BETTER UNDERSTANDING
OF HOW TO USE EXISTING DATA COULD ADVANCE
THE CASE
There is an immediate opportunity to make better use of current available data.
For FSPs, the examination and analysis of firm-level customer data as well as aggregate
FSP data will produce insights that support the business case for providing more
women’s market offerings, moving more FSPs along the WFI pathway from the
“consider” stage to the “action” stage. Running more detailed data analyses would also
help FSPs refine and expand on the women’s market offerings they currently provide,
moving these FSPs along the WFI pathway from the “action” stage to “champion.” For
the regulator, optimizing data already being generated through deeper analysis and
more routine reporting could help inform future policy interventions and optimize
positive impact. Table 2 presents an overview of these opportunities.
Table 2. Opportunities to be leveraged
OPPORTUNITIES TO BE LEVERAGED
COMMERCIAL • Enhanced reporting requirements and upcoming publication of data insights to
BANKS heighten awareness of the business potential in the women’s market
DATA • Widespread availability of high-quality data on some women customer segments
PRODUCERS
• Emerging evidence of successful women’s market programs
FINTECHS • Availability of high-quality sex-disaggregated data
DATA
PRODUCERS
MFIS • Mission-central commitment to women
DATA • Widespread availability of high-quality data on some women customer segments
PRODUCERS
SBP • Political will and commitment
DATA • Mandated sex-disaggregated data reporting
AGGREGATOR • Development of financial inclusion policies
& USER
SECP • Political will
AGGREGATOR • Digital transformation
& USERS • Commitment to development of financial inclusion policies
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chunk_17_28 | LESSONS LEARNED FROM
PAKISTAN’S EXPERIENCE
The diagnostic offers lessons for Pakistan—as well as for other countries.
These include:
• Political will and regulatory involvement incentivize the push for more
supply-side sex-disaggregated data. SBP’s mandate to report sex-
disaggregated data triggered the widespread availability of high-quality
sex-disaggregated data.
• However, just because the data is available doesn’t mean it’s being used.
Most FSPs do not incorporate sex-disaggregated data into their routine
management reporting or use available data to develop of their women’s
market offerings. Although SBP uses the data in its own reporting and
policymaking, it does not publish insights based on this data. This leaves
FSPs without access to data-driven market perspectives or intelligence on
women customer behaviors and performance.
• The lack of focus on women SMEs impedes a holistic understanding
of the female economy. Women’s entrepreneurship in Pakistan is
expected to gain traction in the coming years, as the government
and the international donor community place increased emphasis on
encouraging the development of women’s businesses. Without data
analysis on the WSME segment, FSPs will have a harder time identifying
products and services that meet the segment’s needs and tap into the
growing revenue opportunity.
• Sex-disaggregated data collection and reporting alone are not enough
to advance banks’ WFI pathway. Stakeholders need use cases and
guidance on how to visualize, communicate, and understand the data
in informing their business case for scaling up their women’s market
propositions.
RECOMMENDATIONS
The recommendations that follow are aimed at increasing the collection,
quality, and use of supply-side sex-disaggregated financial data in Pakistan.
For a summary connecting the diagnostic’s findings to the challenges identified
and recommended interventions, see Table 3.
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chunk_17_29 | Table 3. Connecting the findings from the Pakistan Gender Data Diagnostic to data gaps
and interventions
DATA GAPS
POTENTIAL INTERVENTIONS
AWARENESS AVAILABILITY QUALITY USAGE
Lack of bank Limitations include: Limited use of sex-
management • no segmentation disaggregated reports:
buy-in about • not structured for • not part of regular
the business customer-centric automated
case for No granular detail analysis management Industry workshops and trainings with global case studies on how
serving the available reporting to build scalable and profitable women’s proposition
women’s • mainly generated on
market, an ad hoc basis
however this is
changing16
Limited WSME data collection Inadequate internal
awareness limitations include: capacity for data
of data’s • manual data entry analysis:
Data analysis capacity building on how to use and interpret data to importance or • no standard WSME • limits data usage
generate actionable business insights
the full data definition to inform design of
value chain No standard • leads to questions about financial solutions for
WSME definition quality women
• Lack of incentives
to leverage data in Guidance on developing WSME market proposition
designing solutions
for women/WSMEs Work with stakeholders on a standardized WSME definition
• Limited reporting
Women may be used as Training on women’s market modeling and business case analysis
Limited
proxies for loans going financial Lack of incentives
to men
solutions to leverage data in Data analysis capacity building: how to use and interpret data to
No gaps identified targeting designing solutions for produce actionable insights
women women
customers
Enhanced KYC to reduce risk of women being used as proxies
Limited No gaps identified Majority do not
awareness include sex- Awareness building on the business case for serving the women’s
of women’s disaggregated data in market
market Women may be reporting used as proxies for Industry roundtable to share best practices in sex-disaggregated
Business focus loans going to men data analysis and usage Including global examples
Sex-disaggregated
on the banked
segment data not used to advise Enhanced KYC to reduce the risk of women being used as proxies
product development
WSME / enterprise data Mainstreaming of gender data collection across all SBP
is collected, however departments Knowledge sharing with other national regulators on
Marginalized Limitations include: sex-disaggregated data collection, use, analysis, and data sharing
gender data best practices
collection • manual data entry Development of centralized WFI dashboard to increase gender
• no standard WSME data usage, to include key data points, KPIs, trends on verticals/
No data gaps • d Ise sfi un esit i wo in th reporting D ora lt ea v n eo rat ga eg dg r te og ia nt fe od rm segments/geographies, and reports on public consultations
identified template lead to double market on state of WFI Addition of WFI-related reports in the micropayment platform,
counting highlighting insights derived from transactional data
Limited data Development of standard WSME definition and promote better
availability data collection and usage
Inclusion of unique customer level data collection in monthly
reporting for all departments
Incorporation of sex-disaggregated data collection and analysis
into SECP’s WFI strategy, currently in development
Knowledge sharing with other regulators on sex-disaggregated
No sex- No available data to data collection (templates), and analysis (KPIs)
No data gaps disaggregated identified data collection at No gaps identified produce market-level Collaboration with SBP to consolidate insights from sex-
present insights disaggregated data analysis, creating a holistic, national-level WFI
picture
Technical assistance to develop data warehouse capacity for
automated collection and analysis of the data
Ecosystem recommendations
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ataD
/ sIFM
/
sBFM
&
shcetniF
srecudorP
ataD
/
SKNAB
LAIC-REMMOC
PBS
/ sresu
ataD
PCES
/
sresu
ataD
srecudorP
srecudorP
ataD |
chunk_17_30 | With the upcoming implementation of the Banking on Equality policy and a national-
level action plan for full WFI, it will be important to maximize the use of gender data
as a way of measuring progress. In addition, ensuring that the short- and long-term
policy recommendations are implemented in the market requires making them
tangible and action-oriented. For example:
• Replace “Simplify loan applications for women who are applying for financing;”
with concrete steps and processes banks need to take to do so.
• Replace “Provide non-financial advisory services for WSME loan customers”
with “Offer trainings, networking opportunities, and other non-financial
services to a specific proportion of the female customer base.”
Such efforts will contribute to mobilizing the entire financial sector toward greater
financial inclusion.
Box 4. A Promising Model: The UK’s Investing in Women Code21
In 2018, the United Kingdom Treasury commissioned Alison Rose, CEO of
NatWest and long-standing member of the Financial Alliance for Women, to lead
an independent review of women’s entrepreneurship in the UK to tap the unre-
alized economic potential of women entrepreneurs by making the UK a global
destination for women to start and grow a new business. The approach of the
report itself and many of the initiatives proposed could be adapted for applica-
tion in other countries.
In particular, the first of eight initiatives included in the report was to promote
greater transparency in UK funding allocation through a new Investing in
Women Code, and as part of this, to report a commonly agreed set of data on
all-female-led businesses, mixed-gender-led businesses, and all-male-led busi-
nesses. The Code has already been signed by over 100 institutions, including the
UK’s major banks, and released its first report in April 2021. Signatories provide
their results to relevant industry associations, which review and collate the data
and pass it on to UK Treasury, which produces the annual report. This constitutes
the first time most of these organizations provided a public accounting of the
extent of their financing for women entrepreneurs.
The UK’s Investing in Women Code has shown remarkable success in the speed
at which signatories were willing to sign on, assign a leadership champion in
their own institutions, begin reporting sex-disaggregated data, and take action to
better meet the needs of women’s entrepreneurs.
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chunk_17_31 | Industry recommendations
Most of Pakistan’s commercial banks are in the “consider” to “action” stage of
the WFI journey. The diagnostic uncovered several key challenges that could
impede progress, including limited analysis of available data and lack of use
in management reporting. These factors could contribute to decision makers’
hesitancy to move forward with a broader set of women’s market offerings,
since they may not see an evidence-based business case.
Recommendations that encourage FSP engagement include:
• Raise awareness of the value of data for informing business case
for women-centered solutions.
• Build capacity on how to use, analyze, and interpret sex-disaggregated
data and produce actionable insights, including women’s market
modeling, and business case analysis.
• Provide technical advice on how to gather more detailed, anonymized,
customer-level gender data.
• Share best practice approaches and commercially viable business
models for serving the women’s market through trainings such
as Financial Alliance for Women’s All-Stars Academies.
• Leverage the Banking on Equality policy for new business
opportunities: For example, by increasing the customer base through
participating in government-to-person (G2P) transfer programs.
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chunk_17_32 | Regulatory recommendations
SBP has clear political will to enhance the collection and use of disaggregated data by
providers and government. This is evident in the progression of changes implemented,
beginning with the sex-disaggregated data reporting mandate in 2017,17 and
continuing with the recent launch of the Banking on Equality policy. Here are some
recommendations for actions that SBP itself can take to build on the progress already
happening:
• Include unique customer-level data in monthly reporting.
• Cross-check anonymized customer-level data to ensure proper aggregation.
• Define women-centric products clearly for easier reporting.
• Ensure clear definitions for women accounts, women customers,
and women SMEs.
• Collect all customer indicator reports monthly instead of twice-yearly,
for more timely analysis.
• Disaggregate credit product data, including loan size, NPL, and interest rate.
• Revise data collection templates to enable monthly data gathering for more
timeliness and to ensure collection at the unique customer level.
• Share user-friendly aggregate analyses so FSPs have access to actionable
insights, with the goal of spurring action to close WFI gaps.
• Adapt Know-Your-Customer (KYC) requirements to ensure women are using
the loans, not male family members.
Suggested interventions to support SBP’s efforts include:
• Align the implementation phase of Data2X-WFID Gender Data Ecosystem
project with AFI’s ongoing SBP advisory project in the rollout of the Banking
on Equality policy18.
• Develop a WFI performance dashboard, including types of reports to generate
and encourage dashboard usage.
• Interact and share knowledge with regulatory counterparts in other countries
on best practices in sex-disaggregated data collection, use, analysis, and
publication of insights for industry.
SECP is following SBP’s lead, with its plan to implement gender policies that will further
increase the availability of sex-disaggregated data. Suggested interventions to support
SECP’s efforts include:
• Incorporate sex-disaggregated data collection in the WFI strategy.
• Interact and share knowledge with regulatory counterparts in other countries
on best practices in sex-disaggregated data collection, use, analysis,
and publication of insights for industry.
• Build data warehouse capacity for automated data collection and analysis.
Through 2022, WFID will be working on prioritizing and piloting interventions.
We welcome input from and collaboration with partners from stakeholder groups.
Please feel free to contact us at info@data2x.org.
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chunk_17_33 | APPENDIX A. FORECASTING MODEL
DESCRIPTION
The logistic regression assumes a linear relationship between a set of explanatory
variables and the log-odds of a given event:
The probability of the event (e.g., the likelihood of an individual being banked), is
therefore given by the non-linear relationship:
The mean value of the event for a group within the dataset (for example the average
probability of an individual being banked, or the average probability of females being
banked) is the average of the individual probabilities for each individual, weighted by
the survey probability weights. This sum can differ from the probability assessed at the
average value for each of the explanatory variables, assessed at the mean, due to the
functional form. Thus, for N households, with average values of explanatory values
given by xx:
This differs from a linear model, where:
Model projections are made at the mean value for each variable, instead of simulations
for every household. Simulations would be challenging and somewhat ad-hoc for
variables such as increase in school completion rates or mobile phone ownership,
where ownership status would have to change for individual households to match
the projected growth rate. Consequently, the non-linear nature of the model implies
that the model evaluated at the mean value for each variable will be different from the
average of the values for each individual.
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chunk_17_34 | Data
• Baseline microdata is from the Financial Inclusion Insights (FII) program,
collected by the Bill & Melinda Gates Foundation, in partnership with Kantar.
The sixth survey (Wave 6) was conducted from February 18 to March 22, 2020,
targeting individuals aged 15 years and above.
• The sixth survey (Wave 6) was conducted from February 18 to March 22, 2020,
targeting individuals aged 15 years and above. Data was stratified by rural and
urban areas, and also by province, covering Punjab and Islamabad, KP, Sindh,
and Baluchistan. Probability proportionate to size (PPS) sampling was the basis
of the sample design, with a targeted sample of 6,000 individuals targeted
before the COVID-19 pandemic and subsequent restrictions. The final survey
data collected comprised of 3,567 observations.
• A follow-up survey was conducted in November to December 2020, with
3,144 of the same households in the first survey. A subset of the variables
collected in the first survey were collected in the follow-up survey, including
mobile phone ownership, mobile money usage, and bank account ownership
and use.
• Data collected within the survey included access and usage of banking
services, including payments, savings, credit, and transfers. In addition, data on
household and individual characteristics were collected.
• For the purposes of analysis, ‘Banked’ is defined as account ownership with a
full-service financial institution, which is an institution that offers loans to its
customers and at least one of the following additional services: savings, money
transfers, insurance or investments. The institutions covered are banks, MFIs,
co-operatives, and post office banks.
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chunk_17_35 | Model estimates by gender
• The February–March 2020 sample indicates that 21.8 percent of the adult population
had
• individual accounts with full-service financial institutions. Access to finance statistics
• indicated significant gender disparities, with 36.5 percent of male adults banked relative
to 7.3 percent of female adults, corresponding to a 29.2 percentage point difference.
• The November–December 2020 sample indicates 25.1 percent of the adult population
had individual accounts with full service financial institutions, with 40.1 percent of
males banked relative to 10.5 percent of females (a 29.6 percentage point difference).
• Overall estimates show similar patterns between men and women, with the most
important determinant of access to finance for both men and women including
completing tertiary education, age, income from salary or wage, and owning a mobile
phone.
• The follow-up survey did not capture 11.8 percent of the original individuals
(423 observations). The dropped individuals were less likely to be banked than those
that were covered in both rounds of the survey. Of the individuals not covered in the
follow up survey, 21.0 percent were banked, with 34.1 percent of males banked relative
to 5.7 percent of females.
• Proximity to a mobile money agent is a significant determinant of access only for
women, while asset ownership is a significant determinant of access only for men.
• Estimates show that neither household proximity to banking sector infrastructure
nor income by sector have a statistically significant impact on the likelihood of being
banked. However, estimates by rural/urban areas show that income from salary or
wage is an important determinant of access to banking for urban areas, while income
from farming has higher statistical significance in rural areas.
Variables Male Female
Asset score 0.2222 *** 0.5484
Completed primary 0.3410 0.1061
Completed secondary 0.5724 *** 1.0782 ***
Completed tertiary 1.3853 *** 1.4644 ***
Age 0.0231 *** 0.0139
Household size 0.0836 (0.1621)
Urban 0.0780 (0.0876)
Married 0.0062 (0.0322)
Income from salary or wage 0.0698 0.3998
Income from farming 0.1361 0.3536
Income from business 0.2299 (01363)
Owns mobile phone 2.1347 *** 2.3086 ***
Close to a bank branch 0.2428 (0.1545)
Close to a bank ATM 0.2547 0.1955
Close to a banking agent (0.3346) * (0.4230)
Close to a mobile money agent 0.0206 0.6485 **
Close to MFI 0.1266 0.2727
constant (4.6272) *** (6.4937) ***
Number of observations 1,549 1,595
Pseudo R-squared 0.1960 0.3007
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chunk_17_36 | Access to finance projections
• The modeling of access to finance indicators is dependent on modeling of
underlying changes in the key explanatory variables. Model forecasts of key
variables are dependent on projections obtained from reputable and widely
cited sources, including the World Bank, IMF, and Shared Socio-Economic
Pathways (SSP) data, in addition to trend projections from time-series data.
• Currently, Pakistan has the second highest number of out of school children
in the world, with sharp disparities in level of education by gender, where
boys outnumber girl at every stage of education. Growth rates in education
completion suggest an increase in equity, but large gaps by gender remain.
• Mobile cellular subscriptions have increased rapidly over the last 15 years,
rising from 8 percent in 2005 to over 76 percent in 2019. The growth rate
has slowed down to 4 percent per annum between 2014 and 2019.
Access to finance by gender (2020 - 2030)
0.60
0.50
0.40
0.30
0.20
0.10
Men Women Gap
0.00
2020 2021 2022 2023 20214 2025 2026 2027 2028 2029 2030
• Projections indicate an increasing gap in access to finance by gender,
rising by 12.5 percentage points over 10 years.
• Access to finance for women shows virtually no improvement over the
projection period, with all gains in access to finance accrued by men.
Access to finance increases by 14.5 percentage points for men relative
to 2.0 percentage points for women.
• The projections are made based on a marginal analysis at mean values,
due to the non-linear nature of the logit model. The graph is rebased
from mean values to actual values in 2020.
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 36
March 2022 |
chunk_17_37 | Access to finance simulation
• The evolution of the access to finance trajectory is simulated under scenarios
that consider different assumptions of the initial levels of key explanatory
variables. Considering levels of education, income from farming, salary or
business, ownership of a mobile phone, and proximity to a mobile money
agent, the simulations assume that the initial levels of these factors are at
the same level for women as they are for men.
• The combination of these factors increases access for women in 2020 by
almost 10 percentage points. Over the forecast horizon, access for women
increases by 12 percentage points. The gap between men and women does
not increase over the forecast horizon.
Access to finance by gender (2020 - 2030)
0.60
0.50
0.40
0.30
0.20
0.10
Men Women Gap
0.00
2020 2021 2022 2023 20214 2025 2026 2027 2028 2029 2030
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 37
March 2022 |
chunk_17_38 | APPENDIX B. WOMEN’S MARKET
OPPORTUNITY CALCULATIONS
The high-level logic of the model can be described through the following key steps:
1. Determining socioeconomic segments (on the base of monthly income,
occupation, and by gender)
2. Determining % of unbanked
3. Determining % of underbanked*
4. Assumptions on potential revenue per segment (net interest income
and fee & commission income)
The assumptions used for the model were based on the following data sources:
Area Assumption Source(s)
Sociodemographic /
economic
Global Findex 2017 Survey, A2FS 2015 Survey
Economic activity
data
Population
Access to finance /
banked
Usage/degree of being
CCX assumptions based on past experience
underserved
Deposits/savings
Products Loans Banks’ and MFIs’ terms and conditions sheets
Payments
*Underbanked: Customers who may have access to a basic transaction account offered by a formal
financial institution, but still have financial needs that are unmet or not appropriately met.
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 38
March 2022 |
chunk_17_39 | Revenue source assumptions used for the modelling
Net Interest Income (after risk cost) Fees & Commission Income
From Loans From Deposits
Bottom-up
Market
Estimate Retail MSME / Agri
Refinancing Rate Fees & Charges
Assumptions per Assumptions per Assumptions per A
segment and loan segment: segment:
type (short-term Retail, • Ratio of short-term • Money transfers
medium-term Retail, savings of monthly per month B
Small Biz, Agri): income (up to 1 • Withdrawals per
• Credit volumes as month) month
share of income • Ratio of medium- • Share of income used C
• Market Penetration term savings in cashless payments
• Expected NPL ratio (>1 month
D • Avg. loan interest rate • Avg. deposit interest
rate
The untapped potential banking revenues of women and men in Pakistan (in $ millions and by %)
Women Breakdown of the total un- and
A 22% Men u ren vd ee nr use er (v Ue Sd D p 2o .t 3e 5n bt nia pl b .aa .)nking
Men Underserved
B 15% 9% W Uno sm ere vn e d
24%
C 16% 4%
63% Women
Underserved
Men
D 77% Unserved
0 200 400 600 800
USD mn
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 39
March 2022
emocnI
ylraeY
/ ylhtnoM |
chunk_17_40 | An overview of the assumptions deployed in the model can be found below:
D ($16 avg. monthly C ($49 avg. monthly B ($81 avg. monthly A ($194/+ avg. monthly
income) income) income) income)
MEN WOMEN MEN WOMEN MEN WOMEN MEN WOMEN
Deposits and Savings
Short term savings (…) 35% 35% 35% 35% 40% 40% 40% 40%
Long term savings (…) 8% 8% 10% 10% 12% 12% 15% 15%
Transactions and Payments
Money transfers per month 0.5 0.25 0.5 0.25 2 2 2 2
Withdrawals per month 1 1 1 1 3 3 4 4
% of income used in cash-
10% 5% 15% 10% 25% 25% 35% 35%
less payments
Loans Retail, (very) short-term liquidity mgmt
Credit Volume (% of
100% 100% 100% 100% 150% 150% 200% 200%
MONTHLY income)
Credit Penetration (% of
10% 10% 10% 10% 10% 10% 10% 10%
client)
Expected Loan Losses (net
3.0% 2.0% 2.5% 1.5% 2.0% 1.0% 1.0% 0.8%
of recovery)
Loans Retail, medium-term
Credit Volume (% of ANNU-
40% 40% 60% 60% 80% 80% 100% 100%
AL income)
Credit Penetration (% of
10% 10% 15% 15% 20% 20% 30% 30%
clients)
Expected Loan Losses (net
4.0% 2.0% 3.5% 1.5% 3.0% 1.0% 3.0% 1.0%
of recovery)
Loans Small Business, e.g., inventory finance
Credit Volume (% of
40% 40% 35% 35% 30% 30% 20% 20%
MONTHLY income)
% of Segment small business
9% 2% 31% 9% 40% 16% 50% 10%
owners
Credit Penetration (% of
90% 90% 80% 80% 70% 70% 50% 50%
clients)
Expected Loan Losses (net
3.0% 2.0% 2.5% 1.5% 2.0% 1.0% 1.0% 0.8%
of recovery)
Loans Agri-Finance
Credit Volume (% of ANNU-
40% 40% 40% 40% 30% 30% 20% 20%
AL income)
Share of Segment active in
22% 2% 17% 5% 26% 12% 37% 2%
agriculture
Credit Penetration (% of
60% 60% 80% 80% 60% 60% 30% 30%
clients)
Expected Loan Losses (net
3.0% 2.0% 2.5% 1.5% 2.0% 1.0% 1.0% 0.8%
of recovery)
RATES
Borrowing rate 36.0% 36.0% 27.9% 27.9% 19.7% 19.7% 11.6% 11.6%
Deposit rate 3.7% 3.7% 4.4% 4.4% 5.0% 5.0% 6.0% 6.0%
Refinancing rate 7.7% 7.7% 7.7% 7.7% 7.7% 7.7% 7.7% 7.7%
Money transfer fee, US$ 0.28 0.28 0.29 0.29 0.30 0.30 0.32 0.32
Withdrawal fee, US$ 0.13 0.13 0.13 0.13 0.12 0.12 0.12 0.12
Fee for cashless payments
(% of value of transactions, 2.00% 2.00% 2.00% 2.00% 2.00% 2.00% 2.00% 2.00%
banks’ share)
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 40
March 2022 |
chunk_17_41 | REFERENCES
• Ali, O.R. and Hilali, H., 2021. “Empowering girls through education in Pakistan”.
EduFinance.org
• CIA World Factbook. Pakistan, 2021.
• Čihák, M. and Sahay, R. 2018. “Women in Finance: An Economic Case for Gender
Equality.” International Monetary Fund Blog.
• Financial Alliance for Women, 2021. “Case Study: HBL Pakistan - The Path to Inclusion
from the Inside Out.”
• Financial Inclusion Insights, 2020. “Pakistan: Sixth Annual Tracker Survey.”
• FinMark Trust and State Bank of Pakistan, 2008&2015. “Access to Finance Survey”.
• Human Rights Watch, 2018. ”Barriers to Girls’ Education in Pakistan”.
• Iftekhar, B. 2021. ”Determinants of Female Labour Force Participation in South Asia”
The Case Study of Pakistan.
• The International Monetary Fund. ”Financial Access Survey”. Database.
• State Bank of Pakistan, 2018. “National Financial Inclusion Strategy - Government’s
100-days Agenda”.
• State Bank of Pakistan, 2021. “Branchless Banking Key Statistics.”
• State Bank of Pakistan, 2022. “Banking on Equality”. Policy paper.
• The World Bank. “Enterprise Surveys, The World Bank”. Database.
• TheNews.pk. 2021. “SBP says gender divide ‘severely’ impedes economic
development”. March 09, 2021.
• WFID Partnership, 2018. “The Way Forward: How Data Can Propel Full Financial
Inclusion for Women.”
• World Bank Database, 2019. “Labor force participation rate, female (% of female
population ages 15+) (national estimate)”. Derived using data from International
Labour Organization, ILOSTAT database.
• World Bank Database, 2020. “Rural population (% of total population) - Pakistan”.
World Bank staff estimates based on the United Nations Population Division’s World
Urbanization Prospects: 2018 Revision.
• World Bank, 2018. “State of Financial Inclusion of Women in Pakistan”.
• World Bank. 2017. “Global Findex Database 2017: Measuring Financial Inclusion and
the Fintech Revolution.”
• World Economic Forum, 2021. “Global Gender Gap Report 2021”.
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 41
March 2022 |
chunk_17_42 | END NOTES
1. WFID Partnership. 2018.
2. Women’s access to banking services increased by 14 percent from 2008 to 2020; however, the
gender gap has more than doubled during the same period.
3. Čihák and Sahay. IMF Blog. 2018.
4. Derived from Unique number of active deposit accounts as presented in the Banking on Equality
Policy Paper. 2022.
5. Before 2017, the most robust data available to assess the women’s market in Pakistan came from
FinMarkTrust’s Access to Finance surveys. Commissioned by SBP and first conducted in 2008,
followed by a second round in 2015, these surveys looked at the demand-side of the market, using
a sample size of 10,000 people. This changed in 2017, with the State Bank of Pakistan’s mandated
sex-disaggregated reporting of unique account holder data from regulated FSPs, providing an
exact overview of the men and women with an account at a formal FSPs. To calculate WFI progress
and the gender gap in the years 2008–2016, we used the Access to Finance survey data to draw
the baseline for overall financial inclusion. To calculate WFI progress and the gender gap from
2017–2020, we used SBP’s number of active account holders.
6. Important sources of demand-side data include Kantar’s Financial Inclusion Insights (FII) studies,
the World Bank Global Findex studies, and the State Bank of Pakistan’s Access to Finance studies;
most recent data available from 2020; very limited WSME demand-side research is available. The
second model simulates how the access to finance trajectory for women would evolve if the initial
levels of access for certain key explanatory variables (levels of education, income from ownership
of farming, salary, or business, ownership of mobile phone and proximity to mobile money agent)
were the same for both men and women.
7. Financial Alliance for Women. HBL Case study.
8. World Bank Database, 2019
9. Financial Inclusion Insights. 2021.
10. World Bank Database, 2020.
11. See e.g., Ali and Hilali. 2021.
12. SBP. Branchless Banking Statistics April–June 2021.
13. SBP, 2018
14. For more information on SBP’s Banking on Equality policy please see: https://www.sbp.org.pk/boe/
index.html
15. USD/PKR conversation rate as of December 31, 2019, from SBP. https://www.sbp.org.pk/ecodata/
crates/2019/Dec/31-Dec-19.pdf
16. Prior to the enactment of the Banking on Equality Policy, there were no gender targets in
management KPIs or incentives for action. Under the BOE, managers have outreach targets for
increasing the number of women account holders and staff gender diversity, along with a host of
other measures. These KPIs will be built into performance of C-suite executives.
17. See SBP’s Banking on Equality policy
18. Note that the Alliance for Financial Inclusion already has an ongoing project supporting SBP on
implementation of the new policy.
19. Source: Financial Alliance for Women.2021. “HBL Pakistan: The path to inclusion from the inside
out.”.
20. Source: IMF. https://data.imf.org/fas
21. Source: Financial Alliance for Women. “The UK’s Investing in Women Code.” Case study.
22. Labor Force Survey of Pakistan, 2020-2021
23. Sources for statistics: CIA World Factbook 2021, Invest Pakistan, WEF Global Gender Gap Report
2021, Global Findex 2017, World Bank Enterprise Survey 2017
Prepared for the WFID Partnership Towards Women’s Financial Inclusion: a Gender Data Diagnostic of Pakistan 42
March 2022 |
chunk_17_43 | Towards Women’s
Financial Inclusion:
a Gender Data
Diagnostic of Pakistan
Prepared for the WFID Partnership
March 2022 |
chunk_18_1 | Diversity And Inclusion
Why Diverse Teams Are
Smarter
by David Rock and Heidi Grant
November 04, 2016
Striving to increase workplace diversity is not an empty slogan —
it is a good business decision. A 2015 McKinsey report on 366
public companies found that those in the top quartile for ethnic
and racial diversity in management were 35% more likely to have
financial returns above their industry mean, and those in the top
quartile for gender diversity were 15% more likely to have returns
above the industry mean. |
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chunk_19_1 | OXFAM CASE STUDY MARCH 2017
INSTITUTIONALIZING
GENDER IN
EMERGENCIES
Case study of Pakistan
This case study describes implementation of the project
Institutionalizing Gender in Emergencies: Bridging Policy and
Practice. The project, supported by ECHO Enhanced
Response Capacity and Oxfam, was implemented by Oxfam in
Pakistan between September 2015 and March 2017.
www.oxfam.org |
chunk_19_2 | CONTENTS
1 The Project in Context ..................................................................... 3
2 Project Highlights and Milestones .................................................... 5
3 Coalition-Building: The Development of the Gender in Emergencies
Working Group (GiEWG) ................................................................. 6
4 Improving the Evidence Base – Gender Analysis ............................ 9
5 Improving Technical Capacity for Gender in Emergencies ............. 12
6 Trialling the Accountability Framework .......................................... 15
7 Conclusion ..................................................................................... 18
8 Next Steps ..................................................................................... 18
2 |
chunk_19_3 | 1 THE PROJECT IN
CONTEXT
Pakistan faces frequent natural disasters, including earthquakes, floods,
cyclones, drought and tsunami, and there is ongoing conflict and military
operations in the northwest of the country (in Khyber-Pakhtunkhwa (KP)
and the territory of FATA). In general terms, Pakistan is characterized by
very low human development and a very large number of people in need
of humanitarian assistance.1 This is combined with one of the highest
levels of gender inequality in the world.2
In Pakistan, the sociological data in reports and presentations in most
cases fails to record differences in survey responses by age and sex
(known as sex- and age-disaggregated data (SADD)), and is
characterized by limited or missing gender and social analysis. What
scarce evidence is available suggests that the differential needs and
capacities of affected populations in disasters are not sufficiently
addressed.3
THE CHALLENGES
Globally, good policies and international standards on gender in
emergencies do exist. However, the implementation of humanitarian
assistance with a strong gender perspective remains ad hoc, and there is
limited accountability of implementing agencies.
This project: Institutionalizing Gender in Emergencies: Bridging
Policy and Practice was designed to explore how to better
institutionalize gender-related standards in humanitarian assistance. The
project was developed from an analysis of policy and practice both at a
global level and at country level. The project was piloted in four countries:
Ethiopia, Pakistan, South Sudan and the Dominican Republic from
September 2015 to March 2017.4
The project in these four countries focused on the following issues in
which significant gaps were identified:
• Insufficient gender analysis and evidence to inform humanitarian
response planning and practice;
• Low technical capacity in gender in emergencies across sectors and
organizations;
• A lack of coordination on gender across different agencies to support
sector programmes;
• Lack of accountability for implementation of gender-related standards
within organizations and across the humanitarian system.
3 |
chunk_19_4 | OBJECTIVE, STRATEGIES AND
INTENDED RESULTS
The objective of this project was:
To enhance the capacity of humanitarian organizations to provide
adapted assistance to meet the needs of women, girls, men and
boys in emergency scenarios.
Two strategies were adopted by the project team to achieve the
objective: (A) the institutionalization of gender mainstreaming in
emergencies, and (B) the creation of more robust accountability
mechanisms within humanitarian organizations.
The project aimed to deliver four results:
• Functioning Gender in Emergencies Working Group (GiEWG)
established;
• Gender evidence base via a consolidated Country Gender Analysis
for use by all actors, established;
• Technical capacity for gender in emergencies within humanitarian
organizations,5 enhanced;
• Workable Accountability Framework in coordination mechanisms
tested.
This case study describes the experiences of implementing the project in
Pakistan for each of the four projected outcomes. This includes a
description of the activities carried out, the results achieved, and
important contextual factors affecting the success of the project. It also
provides a reflection on key challenges, limitations and significant events,
and key lessons that may be applicable at global level. It then draws
conclusions and provides recommendations for next steps and future
directions that will be led by Oxfam.
4 |
chunk_19_5 | 2 PROJECT HIGHLIGHTS
AND MILESTONES
Table 1 below summarizes the implementation timetable of the project in
Pakistan and describes the key actors and targets involved at each
stage. This summary is followed by a detailed analysis of interventions.
Table 1: Institutionalizing Gender in Emergencies Project – Pakistan
implementation timetable
Timeline Key milestone of the project Targets/Actors
1. Creation of the Gender in Emergencies Working Group
Oxfam Pakistan’s gender team
Seven humanitarian organizations including
worked to create a Gender in
November–December 2015 INGOs, national NGO, women’s rights
Emergencies Working Group
organizations and Cluster Leads.
(GiEWG)
February 2016 Official project launch UN agencies, humanitarian organizations
2. Improving the Evidence Base – Gender Analysis
Oxfam team, with GiEWG, undertake
Working group, UN agencies, government
April 2016 a desk review of evidence related to
and Clusters
gender in emergencies in Pakistan
Development of ToR for a gender Partners in six locations across
April 2016
analysis and completion of fieldwork Pakistan/Government agencies
Data collection from six disaster
prone-districts – surveying more than
Partners in 6 locations across Pakistan /
October- November 2016 1,500 men and women, using focus
Government agencies
group discussions and key informant
interviews
Compilation and finalization of gender
December 2016–January 2017 Oxfam Team, GiEWG members
analysis in consultation with GiEWG
February 2017–March 2017 Publication and launch GiEWG and all stakeholders
3. Developing Technical Capacity in Gender in Emergencies
Self-assessment tool showing gender
February 2016 GiEWG membership
gaps in practice and policy
The first Gender Leadership in INGO, local NGO, Cluster, regional
May 2016
Humanitarian Action training course government participation
Second Gender Leadership in National, international organizations and
December 2016
Humanitarian Action course government
4. Accountability Framework in Coordination Structures
Sharing common Accountability
UN OCHA, UN Women, Pakistan
November 2016 Framework with key stakeholders and
Humanitarian Forum, Cluster Leads for KP
consultation and planning
UN OCHA, UN Women, WASH cluster,
Sharing Accountability Framework for
January–February 2017 START Network, National Humanitarian
feedback and adaptation
Network, Gender Task Force, HTC
5 |
chunk_19_6 | 3 COALITION-BUILDING:
THE DEVELOPMENT OF
THE GENDER IN
EMERGENCIES WORKING
GROUP (GIEWG)
ISSUE
The analysis at global level revealed that gender issues are only
addressed in a limited way in humanitarian coordination mechanisms,
and are mostly confined to the gender-based violence (GBV) sub-cluster
of the protection cluster. This limits the understanding and awareness of
gender-related issues by humanitarian actors. It may mean that
differential vulnerabilities, as well as the long-term social norms and
underlying root causes of gender inequality are not examined or
adequately addressed within programming. It also suggests that the
discussion of gender within humanitarian response efforts may not
benefit from the input of local actors, including women’s rights
organizations.
INTENDED RESULT 1
The project design included the establishment of a national Gender in
Emergencies Working Group (GiEWG). This collaborative venture was
intended to bring together different actors in the humanitarian system to
lead on the project activities and create sustainable change in the
humanitarian system.
Important actors had been identified at global level as cluster lead
organizations, including UN agencies and INGOs, as well as key local
NGO partners and organizations/coalitions working on women’s rights.
ACTIVITIES AND RESULTS
Activities
During the inception phase of the project, Oxfam reached out to relevant
agencies in Islamabad and secured agreement of participation from
CARE International, the United Nations Food and Agriculture
Organization (UNFAO), International Rescue Committee (IRC), UNICEF,
UN Women, and the Aurat Foundation – a prominent national NGO
working on women’s rights issues across the country. At the time of the
6 |
chunk_19_7 | launch of the project in February 2016, the GiEWG had the buy-in and
support of these major organizations, and this interest and support was
maintained throughout the project.
Each collaborating agency designated a focal person, and the group
developed clear terms of reference (ToR): to meet monthly, to engage in
project activities, and to share knowledge resources (human and
coalition-building).
During the project, eight monthly meetings were held, each including at
least 60 percent of members.
Results
The GiEWG provided technical support for the review of documents &
processes in the project (as described under the other outputs below).
The GiEWG also supported non-project-related activities: this involved
reviewing the Aurat Foundation’s comprehensive policy framework on the
rights of internally displaced persons (IDPs), and providing technical
support to a scoping study on GBV in humanitarian settings in 2015 in
collaboration with the UN Population Fund (UNFPA).6
GiEWG members are also the part of Gender Task Force (GTF), a broad
coalition of more than 80 delegates including researchers and policy
makers in Pakistan, convened by UN Women. The GTF is an advisory
body to the UN Office for the Coordination of Humanitarian Affairs
(UNOCHA) in Pakistan and so the GiEWG has remained a part of this
group and boosted its functioning and membership. Project results and
learning have been shared at each stage with the GTF.
CHALLENGES AND LIMITATIONS
The key challenges in establishing the GiEWG related to contextual
factors, and the experience of the working group demonstrated the
importance of paying close regard to these factors and adapting the
GiEWG to respond to the specific context in question. A number of
issues were faced in building a collaboration in this way in Pakistan:
Government collaboration
Increasingly, the key actors in humanitarian assistance are governmental
ones. Within the national federal government, the National Disaster
Management Authority (NDMA) leads humanitarian policy, coordination,
technical assistance and planning. In each province the Provincial
Disaster Management Authority (PDMA), a part of the provincial
government, coordinates the response and supports District Disaster
Management Authorities.7 Consequently, the project had to rely upon
government support to effect change in the areas of the country where
government leads the response.
The NDMA has undertaken a number of positive steps to work on a
gender equality approach and has been supported in these efforts by the
7 |
chunk_19_8 | cooperation of international organizations. Within the structure of the
NDMA is a Women and Child Cell which leads on gender issues, and the
NDMA has recently ratified important national policy guidelines for
supporting vulnerable populations in disasters.8 This gave a strong policy
backing to the project, as it shows a high level of awareness by the
government of the needs of vulnerable groups. However, the GiEWG
was not formally endorsed by the NDMA during this project, despite
positive communication and the sharing of results throughout.9
Collaboration with humanitarian organizations
The issue of ‘shrinking humanitarian space’ for INGOs also had an
impact on the project. At the time of the project inception, many INGOs
(including Oxfam GB) were waiting for extensions to their Memorandum
of Understanding (MOU) with the government, necessary for continuing
operations. This meant that there was an uncertain environment in which
to commit resources. It was also difficult to secure support due to the fact
that there was no sub-granting of funds to other agencies, with the result
that the collaboration relied on voluntary commitment of time, and
organizations feared they would be financially liable for project activities It
therefore took more than five months to secure the services of a clear
delegation of personnel to the project. Formal MOUs establishing the
GiEWG within the structure of key organizations were not possible.
Collaboration with the cluster system
The UN Cluster System operates in Pakistan as a ‘one UN’ system.10
During the project, the UN Cluster System was in operation only in KP
and FATA. This led to a decision by the project team to work with
national-level organizations based in Islamabad, with the knowledge that
the clusters leads would need to be approached separately.11 This
constraint was partly because Oxfam does not have an MOU to work in
KP and FATA. However, this led to delays and a lack of ownership from
the cluster later in the project.
LESSONS
The GiEWG is the first forum in Pakistan with a focus on gender in
emergencies, and this is an important and positive development. It has
been able to: share knowledge with a wider range of stakeholders on
gender in emergencies than previously; implement project activities;
advocate among different elements of the humanitarian architecture and
contextualize international approaches; and build trust and a shared
platform. The fact that is has become a reference point for organizational
initiatives means that it is playing an active role in the humanitarian
system in Pakistan.
Funds for a GiEWG are necessary for organizations to commit sustained
resources, beyond individual volunteering of time.
The project analysis did not focus on changes in the government system,
but, in Pakistan, government support is the key to sustainable change.
8 |
chunk_19_9 | The challenges and delays faced by this project demonstrate that it is
imperative to work closely with government authorities.
Developing relationships with local actors requires substantial resources
in terms of people and time. A formal role for the GiEWG is achievable,
but this would require a long-term strategic and consistent engagement
with a wide range of government institutions, as well as sustained and
broad coalition-building within civil society.
In the current context, projects need to include funds for sustaining the
relationships with government.
In retrospect, it became apparent that Cluster Organizations should have
been engaged earlier in the project, but there were significant constraints
to doing so.
4 IMPROVING THE
EVIDENCE BASE –
GENDER ANALYSIS
ISSUE
At the international level, there is insufficient gender analysis and
evidence to inform humanitarian response planning and practice.
INTENDED RESULT 2
The process entailed the consolidation of available data on gender
issues in emergencies at a country level (desk review), in order to
undertake a gap analysis of areas of deficiency, and to use this to
conduct a field study. Put together, this would form a consolidated
country Gender Analysis. The aim was to support humanitarian actors in
developing proposals and designing humanitarian programme strategies
and contingency plans, and also to help to establish links with long-term
development projects.
ACTIVITIES AND RESULTS
Activities
The project team first collated all the available evidence on gender in
emergencies, reaching out to the GiEWG and beyond. The desk review
(completed April 2016) incorporated findings from more than 90
documents covering different aspects of mainstreaming within different
disaster responses in Pakistan.12 There were strong findings from
9 |
chunk_19_10 | existing reviews that women, children and other vulnerable groups were
particularly disadvantaged in an emergency context and less able than
men and boys to access humanitarian assistance. However there was no
consolidated data on gender in emergencies at country level. As sex-
and age-disaggregated data (SADD) in most reports and presentations
was missing, information on gender was confined to specific studies and
evaluations.13
After completing the desk review, comprehensive ToR were developed
by Oxfam, with consultation from regional staff, as well as the GiEWG
members.
Six districts were selected, based on the NDMA Implementation Road
Map Phase 1, in October 2016. This was to ensure that findings from the
study were directly relevant to public policy. The field study included
Oxfam partners to implement the survey.14
From October to December 2016, the field data was collected from more
than 1,500 individuals in disaster-affected areas across Pakistan, as well
as with key informants in partner agencies, and district authorities.
Results
Initial results have been shared with members of the GiEWG to develop
strong recommendations for different humanitarian actors.
Before this project, no consolidated country gender analysis had been
carried out. The type of data that has been gathered has not been
collected before and should therefore make a major contribution toward
achieving more targeted humanitarian response.
CHALLENGES AND LIMITATIONS
Implementing the desk review was an extremely challenging process in
itself, as the project encountered very poor information management and
high turnover of staff in humanitarian programmes (often hired for a
specific project on a short-term basis), which meant that personnel within
organizations were unaware of, or not able to access, relevant reports.
The implementation of a field study of this size has proved to be
impossible in the original timescale. Consequently, the intended step of
using the gender analysis to influence organizational strategies and
proposals has not been achieved in the project timeframe. Delays were
experienced as a result of a number of factors:
• At the outset, there were differences of opinion regarding how to take
the study forward, as it had been envisaged that other agencies in the
GiEWG would contribute both technical and financial resources to the
study, yet this did not prove possible. Oxfam’s MOU only permits
Oxfam to work in Punjab and Sindh, while the gender analysis field
study required a countrywide study.
• The scope of the study also required approval not just by Oxfam but
by the NDMA. Getting this approval took time. For the findings to be
10 |
chunk_19_11 | useful and influential, government stakeholders needed to be involved
from the start. Government restrictions on surveys and research also
necessitated that prior approval be obtained from the Ministry of
Interior as well as from particular district authorities, which took two to
four months in some cases.
• Major logistical problems included monsoon rains blocking access to
the field and primary data that was temporarily seized by intelligence
agencies at provincial level (later released).
• A delay was incurred due to the fact that the external consultant
needed additional support to develop the analysis required within the
agreed timeframe.
LESSONS
A key role of a GiEWG is to support better information management of
existing contextual knowledge on gender in emergencies. Resources are
required for expertise to be updated and transferred in the future.
The desk review and consolidated study represent a step forward in
understanding gender in emergencies at national level. Data aggregated
at national level should support policy change.
Developing the ToR took time, but was necessary, as robust consultation
supports positive dissemination and uptake of results.
The logistical challenges of undertaking research with a large primary
dataset need to be better integrated into a project timeframe.
In this project we did not originally plan for such a large primary dataset.
This was a significant problem, as the need for a larger study was only
revealed at the gap analysis stage.
A realistic timeframe is required for analysis of data. Additional resources
will be required for the services of external consultants to conduct
analysis of research results and recommendations from the study.
The analysis presented in this study will not only help humanitarian
actors in Pakistan to shape their current programming, but it also
provides a baseline that can be updated in the years to come.
11 |
chunk_19_12 | 5 IMPROVING
TECHNICAL CAPACITY
FOR GENDER IN
EMERGENCIES
ISSUE
The issue addressed was low technical capacity across sectors and
organizations on gender in emergencies.
Intended result 3
The objective was to create a baseline of capacity on gender in
emergencies for participating agencies. This exercise was designed to
raise awareness of capacity gaps that could then be addressed through
training courses, designed at global level and adapted at national level,
focused on gender leadership in humanitarian action. The training would
lead to the creation of a national-level action plan, with the aim of
achieving concrete changes in internal guidance and policies, as well as
follow-on training by participating organizations.
ACTIVITIES AND RESULTS
ACHIEVED
Activities
The project (at global level) designed an organizational self-assessment
study as a tool for the GiEWG based on the Oxfam minimum standards
for gender in emergencies.15 In February 2016, the organizational self-
assessment was completed by the members of the GiEWG: UN Women,
FAO, IRC, UNICEF, the Aurat Foundation and Oxfam GB.
The responses included a wide range of opinions about how effectively
organizations were working and scores ranging from 48 to 92 out of 100.
While international organizations had strong organizational policies on
gender in emergencies, these were not always implemented well in the
specific countries. Most agencies were weak at using gender analysis
through the project cycle.
The Gender Leadership in Humanitarian Action course aimed to develop
gender leadership to drive change in the humanitarian system. Modules
addressed technical capacity as well as soft skills in conflict management
and how to lead change.
12 |
chunk_19_13 | Figure 1: Sample modules of the Gender Leadership in Humanitarian
Action course
Managing conflict CHS, IASC
What is gender?
– Killman’s model Marker
Power walk in a
External talks on Gender Analysis,
disaster scenario
leading change Feminist MEAL
Feminist
Full simulation
GBV / PSEA Leadership
from IASC online
Diamond
The first training took place in Pakistan in May 2016. There were 23
participants (16 women and seven men) representing a range of
organizations, including six collaborating agencies from the GiEWG and
Cluster members from Food Security and Community Restoration
Clusters.
The second training event was held in December 2016 for 16 participants
(six women and 10 men). This course engaged a wider range of
participants, including government staff from Sindh PDMA, KP Social
Welfare and Child Protection department, and FATA Disaster
Management Authority officials. The training also engaged clusters and
national partners of other agencies and Oxfam.
Results
The self-assessment was a breakthrough in building trust and
collaborative spirit between a range of very different organizations, and
facilitated productive exercises in comparing practices. It also highlighted
the need for further training and capacity-building in this area.
Feedback indicated that the training was in-depth and relevant to the
context, and that it included gender-related standards and approaches,
and the Gender and Age marker.16 Participants reported that being
asked to reconsider gender leadership skills was a new and worthwhile
experience, and, it was felt that the training provided an opportunity for
cross learning through sharing experience and good practices.
As a result of the training, action plans were developed at three levels:
that of the individual, the organization, and the group. The action plans
were compiled into a single country ‘road map’ – a process led by
UNOCHA and including actions for the Clusters.
Since the initial training, three of the seven agencies involved have
13 |
chunk_19_14 | replicated this training with their staff, and five have undertaken other
initiatives outlined in their action plan that reflect the ownership and
commitment of the partner organizations.
CHALLENGES
It was initially challenging to consider how to conduct a survey that
explored organizational gaps, without subjecting it to lengthy sign-off
procedures on publication of results. The organizations involved decided
that they would treat the examination as an internal exercise that would
serve as a baseline for the project.
Several PDMA Baluchistan staff were trained but then left their position.
Staff turnover is a major factor affecting the sustainability of training
outcomes.
LESSONS
Self-assessment is a very useful way of understanding organizational
strengths and weaknesses and building awareness of capacity gaps.
Organizational gender reviews through self-assessment may support
organizations to grow and learn, and could be repeated on a regular
basis.
By maintaining the confidentiality of results among the GiEWG, gender
focal personnel can acquire good evidence of gaps to report back to their
management teams, without going through sign-off procedures that may
cause delays or open the organization up to external criticism.
Gender leadership in humanitarian action is a new and attractive area for
participants in Pakistan.
There is a substantial need for further development of technical capacity
in gender in emergencies across humanitarian actors, including INGOs,
local NGOs, UN agencies and government.
14 |
chunk_19_15 | 6 TRIALLING THE
ACCOUNTABILITY
FRAMEWORK
ISSUE
The issue addressed was the lack of accountability for implementation of
gender-related standards within organizations and across the
humanitarian sector.
INTENDED RESULT 4
The intended result was to trial a global accountability framework with
cluster organizations. This framework was intended to support the
clusters to develop action plans that would improve accountability for
gender in their sector coordination mechanisms.
ACTIVITIES AND RESULTS
ACHIEVED
Activities
The global project team examined accountability for gender at all levels
and developed an Accountability Framework. It identified specific actions
to be taken by coordination mechanisms that would promote gender
equality (outlined below). The framework included key elements and best
practice examples to support self-assessment.
15 |
chunk_19_16 | Table 2: Outline of Global Accountability Framework
Ten things we want Clusters to do on gender
Rating
1. Quality gender analysis
Very Good
2.Gender-responsive strategic planning documents
3. Contextualized minimum gender commitments Good
4. Adequate gendered competency of agency expertise and
staff
Unsatisfactory
5. Inclusive and participatory cluster/sector meetings
6. Learning spaces on gender-responsive implementation Weak
7. Gender-responsive cross-cluster/sector coordination
mechanisms
8. Continuous review and adaptation of ways of working with
affected populations
9. Recurrent monitoring of the IASC Gender and Age Marker
10. Enhancement of linkages between humanitarian and
development interventions
In Pakistan, the Accountability Framework was first shared with the
GiEWG, and a joint meeting and review of the tool was subsequently
convened with the UN OCHA head, UN OCHA gender adviser, and
ECHO technical assistant. Initial feedback was that, while the measures
appeared important and valid, there was a concern that the tool was
being ‘imposed’ and that it may duplicate existing monitoring
arrangements. It would need formal endorsement by the Humanitarian
Country Team (HCT) to be implemented.17
It has since been shared and consulted upon with the Gender Task
Force, the Pakistan START Network, and the KP WASH Cluster.
Results
The feedback from the START Network was very positive. They felt that
the accountability framework measures could support them in developing
Standard Operating Procedures and simulations for groups of specialists
they are developing as a part of their own project, Transforming Surge
Capacity.
The initial feedback from the WASH Cluster is that the measures are
valid areas for the Cluster to monitor and complement the use of the
Gender Marker. However, it would be important to contextualize the
measures and include reference to Pakistani Law. They noted that such
a mapping may support better allocation of gender resources within the
cluster.
16 |
chunk_19_17 | The project aims to complete a revision of the framework and seek
formal endorsement of the tool.
CHALLENGES
There have been challenges and delays owing to the fact that the
Clusters are grouped in a specific geographical location, and since the
tool was designed at a global level, it encountered initial resistance on
the basis that it was being externally imposed on actors in-country.
Application within Pakistan’s ‘one UN’ system requires formal
endorsement by the HCT. Entry points for change are via the Pakistan
Humanitarian Forum (PHF), the National Humanitarian Network (NHN)
and the HCT.
It is still unclear how this tool will be different, distinct or add value in
comparison to existing monitoring and reviewing tools, and this
consultation is ongoing.
‘Accountability’ is an overused and loaded term in Pakistan and is viewed
negatively by a number of organizations.
LESSONS
The way that the cluster system operates in Pakistan offers a significant
opportunity to advocate for gender accountability via a formal process of
endorsement. If achieved, this would represent a step change in gender
accountability within Pakistan.
The measures may improve practice and monitoring by the Cluster. The
tool offers an entry point for the GiEWG to support the Clusters and other
initiatives such as the START Network.18
Collective ownership is crucial. We should view this tool as a basis for
local adaptation to context, through reference to local law and rescaling
as necessary to respond to context-specific constraint.
The GiEWG should be involved in revising the language of the
framework. It may need to change its name (one recommendation:
Gender Responsive framework).
17 |
chunk_19_18 | 7 CONCLUSION
The approach of the project to institutionalize gender standards and
approaches is, in itself, new to Pakistan’s humanitarian system, and as
such, it addressed a significant gap. The project has helped to move the
gender agenda forward among humanitarian organizations, and a
significant outcome is the development of Oxfam’s own organizational
action plan.
The project required a long-term perspective in the Pakistani context –
with a more strategic analysis of key actors, a focus on developing
strategic relationships with government partners, and early buy-in from
cluster organizations.
8 NEXT STEPS
The project has outlined next steps that Oxfam and other members of the
GiEWG intend to deliver at country level. These include:
• To incorporate a gender perspective at all stages of the programme
cycle: proposal development, implementation, monitoring, evaluation
and reporting by partners;
• To undertake gender-sensitive contingency planning for the coming
year;
• To plan events and allocate resources for capacity-building clusters
and PDMAs regarding gender in emergencies;
• To develop a humanitarian strategy with a focus on gender equality
and women rights;
• To maintain gender- and age-disaggregated data collection at staff
and partner level for any assessment/report;
• To map grassroots level women groups and create linkages and
dialogue;
• To include gender in preparedness planning, emergency response
and rehabilitation activities.
18 |
chunk_19_19 | NOTES
1 Pakistan is ranked 147 out of 188 countries in the human development index (HDI) (UNDP HDI
ranking 2014, 2015). The Global Acute Malnutrition (GAM) rate of 15.1% in Pakistan is classified as
critical according to the World Health Organization (WHO) emergency threshold and represents one
of the highest worldwide. According to SIDA Crisis Analysis Report (2015), Pakistan has the third
largest caseload (3.3 million) of acutely under-nourished children in the world.
2 According to the Global Gender Gap Report 2015, Pakistan ranks 144 out of 145 countries in
terms of the overall gender gap, measured in educational attainment, health and survival, and
political empowerment (World Economic Forum, ‘The Global Gender Gap Report 2015’. Geneva).
3 For instance, in Punjab flood response in 2014, almost 20% of respondents from female-headed
households (7%), child-headed households (4%), older persons and people living with disabilities
(5%) were excluded from distributions. Female headed-households, such as widows without National
ID Card and domicile, were not registered for assistance (‘Multi-sector initial Rapid Assessment
(MIRA) Punjab Floods’ (PDMA, NDMA, HCT, 2014).
4 For global analysis see ‘Humanitarian Response Index: Addressing the Gender Challenge’ (DARA,
2011) and ‘Humanitarian Emergency Response Review’ (DFID, 2011).
5 To meet Oxfam minimum standards for gender in emergencies (2013), see http://policy-
practice.oxfam.org.uk/publications/oxfam-minimum-standards-for-gender-in-emergencies-305867
6 This scoping review highlighted some recommendations regarding gender in emergencies which
included introducing doorstep measures for community mobilization, sensitization, protection
monitoring, and engaging community key informants and students from law backgrounds to
volunteer their time to hold gender awareness sessions. GiEWG members recommended that strong
feedback mechanisms be put in place to engage communities and vulnerable population groups in
identifying risks, which may facilitate the identification and reporting of GBV incidents to ensure
preventative measures are adopted.
7 For more details about the humanitarian system in Pakistan see www.ndma.gov.pk
8 See Government of Pakistan (2014) ‘National Policy Guidelines on Vulnerable Groups in
Disasters’. http://ndma.gov.pk/plans/gcc_policy.pdf
9 One reason for this may be that the GiEWG has been seen by the NDMA as a project-based
working group, and not a long-term group. However, limitations of working with the GTF include a
very broad membership and focus on both long-term and humanitarian issues.
10 See One UN Programme at https://www.un.org.pk/one-un-programme/ for more details.
11 There are three organizations in the GiEWG that are Cluster Leads: UNICEF (WASH Cluster
Lead) Food and Agriculture Organisation (FAO) (Food Security Cluster Co-lead) and IRC (Protection
Co-lead). However, in Pakistan, the clusters report directly to UN OCHA and operate separately.
12 Oxfam (April 2016) ‘Consolidated Country Gender Analysis: Desk Review report’.
13 Ibid.
14 Implementing partners were the Doaba Foundation, Thardeep Rural Development Program, Aga
Khan Rural Support Programme, People Welfare Council, Khendow Kor, Act International and
SHINE in six multi-disaster-prone districts (Muzaffargarh, Tharparkar, Muzafrababd, Naseerabad
Peshawar and Gilit Baltistan).
15 This simple questionnaire of 20 questions allowed participants in the GiEWG to score their own
organization, investigating and comparing their work in four areas: exploring internal practices,
gender analysis through the project cycle, ensuring dignity and empowerment, and preventing GBV/
Prevention of Sexual Exploitation and Abuse (PSEA). For the full Oxfam minimum standards for
gender in emergencies (2013), see http://policy-practice.oxfam.org.uk/publications/oxfam-minimum-
standards-for-gender-in-emergencies-305867
16 The IASC Gender Marker is a tool that codes, on a 0 2 scale, whether or not a humanitarian
project is designed well enough to ensure that women/girls and men/boys will benefit equally from it
or that it will advance gender equality in another way. Se–e
https://www.humanitarianresponse.info/en/topics/gender/page/iasc-gender-marker. A revised version
(forthcoming) will incorporate both gender and age.
17 The Humanitarian Country Team (HCT) is the central UN body at Country level for coordinating
Humanitarian response. See: Inter-Agency Standing Committee (2010) Guidance for Humanitarian
Country Teams. https://interagencystandingcommittee.org/leadership-and-humanitarian-
coordination/documents-public/guidance-humanitarian-country-teams
18 See Startnetwork.org for information about the START Network in Pakistan and globally.
19 |
chunk_19_20 | © Oxfam International March 2017
This case study was written by Uzma Batool, Irnum Malik, Eliza Hilton and Steph
Avis. Comments and contributions were made by Tess Dico-Young, Julie
Lafrenière and Karen Iles. It is part of a series of papers and reports written to
inform public debate on development and humanitarian policy issues.
For further information on the issues raised in this paper please email
ehilton1@ght.oxfam.org.
This publication is copyright but the text may be used free of charge for the
purposes of advocacy, campaigning, education, and research, provided that the
source is acknowledged in full. The copyright holder requests that all such use
be registered with them for impact assessment purposes. For copying in any
other circumstances, or for re-use in other publications, or for translation or
adaptation, permission must be secured and a fee may be charged. Email
policyandpractice@oxfam.org.uk.
The information in this publication is correct at the time of going to press.
Published by Oxfam GB for Oxfam International under
ISBN 978-0-85598-913-2 in March 2017.
Oxfam GB, Oxfam House, John Smith Drive, Cowley, Oxford, OX4 2JY, UK.
This initiative is funded by the European Commission’s Humanitarian Aid and
Civil Protection department (DG ECHO).
This document covers humanitarian aid activities implemented with the financial
assistance of the European Union. The views expressed herein should not be
taken, in any way, to reflect the official opinion of the European Union, and the
European Commission is not responsible for any use that may be made of the
information it contains.
OXFAM
Oxfam is an international confederation of 20 organizations networked together
in more than 90 countries, as part of a global movement for change, to build a
future free from the injustice of poverty. Please write to any of the agencies for
further information, or visit www.oxfam.org.
www.oxfam.org
20 |
chunk_20_1 | Inclusion & Belonging Pilot Pulse Survey Results
Harvard Office for Diversity, Inclusion, and Belonging
October 29, 2019
List of Tables
1.1 Overall agreement per question . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2.1 IfeellikeIbelongatHarvard. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2.2 MyrelationshipsatHarvardareassatisfyingasIwouldwantthemtobe. . . . . . . . . . . . . . . . . . . . . 3
2.3 IfeellikeIcanbemyauthenticselfatHarvard. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.4 The academic/professional goals I have for myself are being met at Harvard. . . . . . . . . . . . . . . . . . . 5
2.5 Iknowwhatconstitutesgoodperformanceinmyrole. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.6 Ireceivemeaningfulrecognitionfordoinggoodwork. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.7 IfeelcomfortableexpressingmyopinionstoothersatHarvard. . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.8 I believe Harvard leadership will take appropriate action in response to incidents of harassment and discrimi‐
nation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.9 IhavetheskillstoaddresshostilebehaviorthatIwitness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1 Overall results by question
Table 1.1: Overall agreement per question
N % Agr % Dis
1. I feel like I belong at Harvard. 20,583 77.0% (0.3) 15.1% (0.2)
2. My relationships at Harvard are as satisfying as I would want them to be. 20,577 69.1% (0.3) 23.6% (0.3)
3. I feel like I can be my authentic self at Harvard. 20,566 70.2% (0.3) 22.4% (0.3)
4. The academic/professional goals I have for myself are being met at Harvard. 20,570 75.6% (0.3) 17.3% (0.3)
5. I know what constitutes good performance in my role. 20,555 83.6% (0.3) 9.8% (0.2)
6. I receive meaningful recognition for doing good work. 20,559 68.8% (0.3) 20.6% (0.3)
7. I feel comfortable expressing my opinions to others at Harvard. 20,566 68.1% (0.3) 23.5% (0.3)
8. I believe Harvard leadership will take appropriate action in response to incidents of harass‐ 20,557 60.3% (0.3) 25.9% (0.3)
ment and discrimination.
9. I have the skills to address hostile behavior that I witness. 20,537 71.1% (0.3) 16.6% (0.3)
Note:
Standard errors shown in parentheses. % Agr = ‘Somewhat agree’, ‘Agree’, or ‘Strongly agree’. % Dis = ‘Somewhat disagree’, ‘Disagree’, or ‘Strongly disagree’.
% Agree and % Disagree columns do not sum to 100%. The remainder is % ‘Neither agree nor disagree.’
2 Detailed results by question
1 |
chunk_20_2 | Table 2.1: I feel like I belong at Harvard.
Academic/Faculty Staff Students
% Agr % Dis % Agr % Dis % Agr % Dis
Overall 77.7% 14.9% 80.3% 10.8% 73.7% 19.3%
Gender identity
Female 73.2% 18.1% 80.8% 10.5% 72.1% 20.5%
Male 82.4% 11.7% 83.3% 9.0% 77.7% 16.0%
Genderqueer or nonbinary (c) (c) 61.2% 29.9% 47.5% 44.6%
Aggregated* (c) (c) 66.7% 19.0% 46.1% 44.7%
Race/ethnicity
Asian or Asian American 77.9% 13.5% 81.3% 9.2% 74.8% 16.6%
Black or African American 76.7% 12.3% 73.3% 16.5% 64.5% 27.5%
Hispanic or Latina/o/x 72.0% 18.7% 78.7% 13.0% 71.0% 22.3%
Middle Eastern 67.4% 20.9% 84.4% 9.4% 62.4% 28.2%
White 79.8% 14.3% 83.4% 8.8% 76.9% 16.7%
Aggregated† 74.4% 10.3% 73.0% 18.2% 62.4% 32.0%
Two or more 77.7% 13.6% 75.2% 15.8% 74.1% 21.1%
Sexual orientation
Bisexual 63.1% 31.0% 77.5% 14.4% 65.0% 28.0%
Gay/Lesbian 74.6% 15.8% 82.1% 11.0% 71.8% 21.4%
Heterosexual 79.6% 13.7% 82.9% 9.2% 76.5% 16.8%
Aggregated‡ (c) (c) 65.7% 20.9% 60.2% 30.8%
Parent education level
Middle school or less 73.4% 20.3% 82.8% 12.6% 59.1% 33.8%
High school 75.9% 16.1% 80.8% 11.8% 67.7% 25.2%
Bachelor’s degree 78.0% 13.9% 81.2% 10.2% 71.2% 21.4%
Post‐bac degree 78.8% 14.3% 82.0% 9.5% 77.0% 16.3%
US citizen
Yes 80.0% 13.6% 81.2% 10.4% 74.0% 19.3%
No 70.4% 19.2% 70.3% 13.3% 75.0% 17.7%
Political ideology
Conservative§ 82.2% 13.3% 80.4% 10.7% 76.8% 18.2%
Moderate 73.8% 16.4% 81.4% 9.0% 76.5% 15.6%
Liberal¶ 79.3% 14.1% 82.4% 10.0% 74.5% 18.7%
Other 64.8% 23.9% 69.2% 18.5% 56.8% 32.7%
Religious preference
Buddhist (c) (c) 83.7% 10.2% 71.7% 22.3%
Hindu 80.9% 10.6% 79.7% 7.6% 73.7% 18.0%
Jewish 86.9% 8.6% 85.9% 6.7% 79.4% 14.0%
Muslim 73.3% 13.3% 79.7% 11.4% 61.2% 28.1%
Protestant 79.7% 13.4% 86.1% 8.1% 75.9% 18.6%
Roman Catholic 80.8% 14.4% 84.0% 9.0% 77.1% 16.3%
No religion 75.3% 17.4% 78.4% 11.7% 74.2% 19.0%
Aggregated** 79.1% 10.0% 81.8% 10.9% 70.0% 22.3%
Two or more 78.5% 14.0% 83.0% 8.6% 74.3% 18.6%
Frequency of attendance at religious services
Never 75.8% 16.1% 79.5% 11.3% 74.1% 18.8%
At least once/year 81.8% 12.7% 84.6% 8.8% 74.7% 18.2%
At least once/month 79.2% 10.8% 82.5% 10.4% 73.4% 21.2%
At least once/week 80.9% 14.5% 83.5% 8.6% 75.2% 19.0%
Note:
Academic/Faculty = Faculty, postdoctoral fellows, and other academic and research personnel.
% Agr = ‘Somewhat agree’, ‘Agree’, or ‘Strongly agree’. % Dis = ‘Somewhat disagree’, ‘Disagree’, or ‘Strongly disagree’. % Agree and % Disagree columns do
not sum to 100%. The remainder is % ‘Neither agree nor disagree.’
Cells with fewer than 30 observations concealed (c). In addition, response categories with fewer than 30 observations within any role were aggregated as
described below.
* ‘Transgender’, ‘Unsure’ or ‘Another gender identity’
† ‘American Indian or Alaska Native’, ‘Native Hawaiian or other Pacific Islander’, or ‘Another race/ethnicity’
‡ ‘Unsure’ or ‘Another orientation’
§ ‘Very conservative’, ‘Conservative’, or ‘Slightly conservative’
¶ ‘Very liberal’, ‘Liberal’, or ‘Slightly liberal’
** ‘Mormon’ or ‘Another preference’
2 |