Her Home
HOUSING FINANCE FOR WOMENACKNOWLEDGEMENTS
This report was supported by the Umbrella Facility for Gender Equality (UFGE), a multi-donor trust fund administeredby the World Bank to advance gender equality and women’s empowerment through experimentation and knowledge
creation to help governments and the private sector focus policy and programs on scalable solutions with sustainableoutcomes. The UFGE is supported with generous contributions from Australia, Canada, Denmark, Finland, Germany,
Iceland, Latvia, the Netherlands, Norway, Spain, Sweden, Switzerland, United Kingdom, United States, and the Bill &Melinda Gates Foundation.
This publication was prepared by an International Finance Corporation and World Bank team led by Henriette Kolb,
Nathalie Hoffmann, William Britt Gwinner, Jessica Schnabel, Montserrat Ganuza, Friedemann Roy, Jose Felix Etchegoyen,
Zahia Msuya Lolila, Carol Tejero, Roshin Mathai Joseph, Joanna Romero, Heather Mae Kipnis, Aphichoke Kotikula, Sharmila
Hardi, Henry Pulizzi, Rob Wright, Bhattiprolu Balachandra Murti, and by the A2F Consulting team consisting of Modibo
Camara, Kate Ivey, Rebati Mendali, Alex Proaño.
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November 2019

Table of Contents
FOREWORD . .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  . 11.	 EXECUTIVE SUMMARY .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  . 2Overall Findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Insights At-a-glance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.	INTRODUCTION .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  . 9The Challenge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Overall Findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  11

3. COLOMBIA.  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  . 14
Key Findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Market Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Current Access to Housing Finance and Supply. . . . . . . . . . . . . . . 18
Barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Market Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

4.	INDIA.  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  . 24
Key Findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Market Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Current Access to Housing Finance and Supply. . . . . . . . . . . . . . . 27
Barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Market Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

5.	KENYA.  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  . 34
Key Findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Market Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Current Access to Housing Finance and Supply. . . . . . . . . . . . . . . 38
Barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Market Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

6.	 THE BUSINESS CASE FOR WOMEN’S HOUSING .  .  .  .  .  .  .  .  .  .  .  .
FINANCE PROGRAMS .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  . 45.
Current Barriers to Women’s Housing Finance . . . . . . . . . . . . . . . 45
Despite Barriers, This is a Market Worth Addressing. . . . . . . . . . 47
Lessons Learned: The Results of Current. . . . . . . . . . . . . . . . . . . . . . .
		
Women-Focused Banking Initiatives. . . . . . . . . . . . . . . . . . .  49
Moving Forward: Addressing the Needs of. . . . . . . . . . . . . . . . . . . . .
		
Women in Housing Finance. . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

NOTES .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  . 55i

ii

Foreword
Women represent half of the world’s population—and half of its economic potential.
But they are far less likely than men to own a home. That’s because women too often
work in informal jobs, are unfamiliar with formal loan application procedures, or are
stifled by traditional cultural norms.
The development of new public policies and financial products and services that increase
women’s access to housing finance can yield benefits to local and national economies.
Women who own their homes enjoy greater financial stability and independence andcontribute more to their community’s economies. At the same time, financial institutions
that offer housing finance services focused on women are better positioned to seize on
opportunities in a growing market.
IFC’s new market study, Her Home: Housing Finance for Women, sheds light on thewomen’s housing finance market in three countries: Colombia, India, and Kenya.
These countries have implemented a variety of policies to increase women’s access tohousing and housing finance.
Her Home provides country-specific insights into the barriers women currently facein obtaining housing finance, details the size and nature of women’s housing financemarkets, and offers recommendations for policymakers and financial institutions to
overcome barriers, improve women’s access to finance, and ultimately improve thelives of millions of women and their families around the world.
A few of the study’s more noteworthy findings:• Women who are self-employed or work in the informal job sector often do nothave income levels and income documentation that meet financial institutions’lending requirements.
• Women frequently lack house titles in their names, which is currently required byfinancial institutions to serve as collateral.
• The estimated market size for women’s housing loans is $23 billion in Colombia,$32.3 billion in India, and $14.8 billion in Kenya—despite the hurdles women face.
• Policies and financial products that address the specific needs of the women’s
housing finance market exist, but on a very small scale.
We hope this report spearheads further innovation, collaboration, and conversationin the housing finance industry to better serve women customers, improve their lives,and support sustainable economic growth around the world.

Paulo de Bolle
Senior Director, Financial Institutions Group, IFC

1

1. Executive Summary
IFC conducted a market study of housing finance for women in three countries where cultural,institutional, and policy barriers to women’s access to housing finance have been identified, as
have opportunities for financial institutions to tap this potential market. The three countries are
Colombia (GDP per capita $14,999), India (GDP per capita $7,761), and Kenya (GDP per capita $3,461)(Source: World Bank International Comparison Program database, 2018).
The study’s conclusions include recommendations for lenders to develop tailored housing financeofferings for women customers. Also included are recommendations for policymakers to develop
reforms geared to improve market conditions and ease women’s access to housing loans.
The study includes interviews with 2,000 low- and middle-income households in these three
countries. The purpose of the interviews was to assess the demand pattern for housing andhousing finance. In addition, interviews with major financial institutions active in housing financewere carried out, as were meetings with government officials and policy stakeholders.
*All denominations are in US dollars.

COLOMBIA

23

16

77

25,92763

BILLION US$PERCENTPERCENTUS$PERCENT

Estimated market

of women usedof women’s housing

Average cost ofloan-to-disposable-

size for women

formal loans toloans were funded

home purchase forincome ratio for

housing loans

purchase housing

by banks

women

women

There is high demand for housing loans among women

77 percent of women, and houses are the preferred dwellingin Colombia, but they remain constrained by unstable

type (73 percent). The market for women in Colombia is

income and by being unable to fulfill loan approval

estimated at approximately $23 billion, yet women remainrequirements. In all, 20 percent of female-headed

disadvantaged in obtaining housing loans becausehouseholds (FHH) and 44 percent of jointof economic inequalities, including lower income

decision-making households plan to purchaseand fewer formal employment opportunities.

a home in the next five years and 23 percent
plan to make home improvements. Banks are
the main source of housing loans preferred by2

INDIA

32.3

13

83

11,71050

BILLION US$PERCENTPERCENTUS$PERCENT

Estimated market

of women usedof women’s housing

Average cost ofloan-to-disposable-

size for women

formal loans toloans were funded

home purchase forincome ratio for

housing loans: US$purchase housing

by banks

women

women

billionThe estimated demand for women housing loans inhouseholds had no female involvement in decision-making.

India totals $32.3 billion. This demand is largely for

The government’s Credit Linked Subsidy Scheme provides

apartments (84 percent), rather than houses.

a subsidized interest rate on housing loans if a

Women chiefly prefer banks (83 percent)woman will hold the title to the new property.

to other financial institutions for housing

The program, although bringing more womenfinance. The main barriers to women’s

into the housing finance market, is only able toaccess to housing finance are insufficientreach a small portion of the potential female

income and traditional gender norms. For

borrowers. Thus, a gap remains.

instance, in the demand survey, 52 percent of

KENYA

14.8

4

57

24,80850

BILLION US$PERCENTPERCENTUS$PERCENT

Estimated market

of women usedof women’s housing

Average cost of homeloan-to-disposable-

size for women

formal loans toloans were fundedpurchase for women:

income ratio for

housing loans: US$purchase housing

by SACCOs

womenbillionKenya has a relatively untapped housing financeoverwhelming majority of women want to purchase amarket with significant unmet demand for housing

house (91 percent), rather than an apartment. Yet, despite

finance among women. There is high demand amonghigh demand, women remain constrained by low income

women in Kenya for housing finance products.

and inability to meet bank requirements. The majority

Thirty-three percent of female-headedof women use Savings and Credit Cooperative

households and 66 percent of joint-decision-

Societies (SACCOs) for housing finance needs,

making households intend to purchaseprimarily because they cannot meet the down

housing in the next five years and 25 percent

payment or provide documents required byplan to make home improvements. The

banks. Traditional roles also contribute to

demand for housing finance among women

women not having equal access to housing

in Kenya is estimated at $14.8 billion. The

finance.

3

EXECUTIVE SUMMARY CONTINUED

Overall Findings

Facilitating women’s access to housing finance could

Lack of appropriate financial means to obtainbeing. Higher quality housing can connect women to new

adequate housing is a wide economic problem in theemployment opportunities, as well as increase their safety

developing world. In addition to supply and demandand security. Policies and programs that encourage housing

issues, macroeconomic instability, insufficient regulatory

finance for women can thus trigger an upward spiral offramework, and limited capital market development affectcommunity development, household income, and overall

the availability of adequate housing finance. Women arestability.

potentially improve their economic and social well-relatively disadvantaged in accessing property and quality
housing due to socioeconomic and cultural practices, as

Developing housing finance value propositions forwell as less favorable gender policies and regulations.

women also could benefit financial institutions.
While FIs report that internal policies and practices are

Female-headed households, or those in which a woman

gender neutral, these gender-neutral processes may

is the primary income earner or decision-maker,

themselves inherently disadvantage women. Income

represent a large, unserved market in each of thedisparities, less formal income sources, less access tostudy countries. These households constitute 26 percent

property titling documentation, and other issues rooted inof households in Colombia, 25 percent in Kenya, and 9

tradition make it more difficult for women to meet loan

percent in India. In each of these countries, female-headed

approval requirements. However, if banks and financial

households are the most disadvantaged group in terms of

institutions can tailor products, services and perhaps

income, income documentation, property ownership andprocesses that consider women’s needs, they can tap

titling, past experience with banks, and other factors that

into this large market, adding value to their bottom line.

affect access to housing finance. Overall, self-employment

Evidence supporting these potential results is already in theis the most common source of employment for female-marketplace. Financial institutions that have tailored value

headed households, though this differs by country and bypropositions to women-owned small- and medium-size

income level. In Colombia 45 percent of women in female-businesses, for example, report business growth coupledheaded households are self-employed or permanent

with a low rate of non-performing loans (NPLs).

employees. In Kenya, that figure stands at 31 percent. In
India, 48 percent of women do not work, while 36 percent

Financial institutions can adopt marketing strategies

are mainly permanent employees.

as well as new housing finance products and services
geared to women, while public policies support

Despite barriers, a relatively large number of women

women’s access to housing finance in general. In termsin female-headed households plan to apply for housingof products, female-headed households and joint decision-loans in the next five years. While only a small percentage

making households display a need for home improvementof female-headed households have applied for housing

loans, incremental construction loans, and home purchaseloans in the past (eight percent in Colombia, six percent

loans. Credit enhancement programs, such as risk sharingin Kenya, and five percent in India), a significantly larger

and credit lines, could help women meet down payment

portion expects to do so in the next five years (20 percent inrequirements. In terms of developing their “women’s

Colombia, 33 percent in Kenya, and five percent in India).

market” strategy, financial institutions could initiate
gender sensitivity training and communications, as well
as develop gender-specific marketing. Research indicatesthat women respond to “relationship” marketing, whether
word-of-mouth endorsements from people they know orinformation offered directly by financial institutions thatthey have come to know and trust.

4

5

10 Key Insights
About Women And
Housing Finance

INSIGHTS AT-A-GLANCE
The market for financial services to help women purchaseand renovate their homes is large and growing indeveloping countries. It represents a significant business
opportunity for financial institutions and policymakers
who are willing to address patriarchal biases and pursue
gender equity. Women comprise half of the population of
the world but are only a fraction of home and property

1owners even as they command significant economic
influence and are prominent household decision makers.

UNEQUAL REPRESENTATIONThis report looks at the market for women’s housing
finance in Colombia, India, and Kenya — each of which

Women comprise half of the population but only a

is valued in the tens of billions of dollars — and identifies

small fraction of property owners.

specific, practical steps that can be taken to mollify

2practices that have handicapped women’s accessto financial services. The report explores the social,economic, and business benefits that accrue from a

UNDERSERVED AND
DISADVANTAGED

more equitable lending environment, including selfsufficiency and personal responsibility. Lastly, it offers
recommendations for attracting and retaining women as

Female-headed households and households where

financial services customers and as vital contributors towomen are primary income earners and decisionmakers constitute 26 percent of households inthe broad economy and their local communities.

Colombia, 25 percent in Kenya, and 9 percent in India,
and are largely unserved by financial institutions.

3
LOW INCOME/LOW ACCESS
Female-headed households often work in theinformal economy and have lower household income
levels than those headed by men or by joint-decision
making households. As a result, women with informal
employment often do not meet the requirements toborrow money and access financial services.

6

4

8

THE DOCUMENTATIONDISADVANTAGE

AN UPWARD SPIRAL
Initiatives that encourage housing finance for women

In each of the three study countries, female-headed

can invigorate community development, encourage

households frequently lack income documentationsafer neighborhoods, bolster incomes, and potentiallyand other paperwork required to access financial

lead to employment opportunities and greater

services.

financial stability.

5

9

LACK OF COLLATERALCLOSES DOORSCUSTOMIZING WORKS
Women face different obstacles and have different

Access to housing finance requires collateral such asneeds. If banks and financial institutions train

land title, property rights, and other large assets, which

staff and tailor products, services, and processes

women lack. In addition, lower levels of education

to consider women’s needs, they can tap into aand limited financial literacy can restrain women fromlarge market and add value to their bottom line.
Female-headed households show a need for homeaccessing housing finance and, in turn, quality housing.

improvement loans, incremental construction loans,6and home purchase loans.

10

SCARCE RESOURCES TO
FINANCE HOUSING

FEWER NPLSIn addition to supply and demand issues that

Financial institutions that have tailored value

disproportionately encumber women’s accesspropositions to women-owned small- and medium-to financial services, macroeconomic instability,

size businesses report business growth coupled withinsufficient regulations, and limited capital market

a low rate of non-performing loans (NPLs).

maturity in developing countries affect the availabilityof adequate housing finances.

7
OPTIMISM IN THE FACE
OF OBSTACLES
Though only a small percentage of female-headedhouseholds have applied for housing loans in the past(eight percent in Colombia, six percent in Kenya, and five
percent in India), a significantly larger portion expect todo so in the next five years (20 percent in Colombia, 33
percent in Kenya, and five percent in India).

7

8

2. Introduction
The Challenge

low ownership rate include socioeconomic circumstances,

Lack of affordable housing is a worldwide economic

policies and regulations, and lack of political commitment

problem. A recent McKinsey study (2016) estimated that

(Source: UN Habitat, 2012, Gender Issue Guide: Housing andapproximately 330 million urban households around theSlum Upgrading). To date, several countries have adopted

world lack the appropriate financial means to obtainstatutory rights and constitutional equality clauses toadequate housing (Source: McKinsey Global Institute, 2014,

challenge the disadvantages women face (Source: United

A Blueprint for Addressing the Global Affordable Housing

Nations, 2012, Women and the Right to Adequate Housing).

Challenge). Several factors including the high cost of

Yet social and cultural norms favoring male ownership andinfrastructure, low level of investment, difficulties accessing

lack of political commitment impede the enforcement andfinancial resources, and increasing costs of building materials

practice of the new laws.

patriarchal attitudes, cultural practices, less favorable

make it difficult for poor and middle-income households toafford a house. Due to increasing population and rural-urban

Women’s access to housing finance is further limited in

migration, an affordable housing shortage has been moredeveloping countries. Housing finance requires collateralsevere in urban areas compared to rural areas.

such as land title, property rights, and other large assets,
which women lack. In addition, lower levels of education,

Women are typically disadvantaged in terms of accesslimited financial literacy, and lower income levels, combined

to property and quality housing. Several studies showwith mobility constraints and limited access to information,that women own less than two percent of titled property

often restrain women from accessing housing finance and,in the developing world (Source: Food and Agriculture

in turn, quality housing. What’s more, women are less able

Organization of the United Nations, FAO, 2002, Women’sto access adequate financial services because of unfavorable

Right to Land: A Human Right). Factors contributing to thelegal and customary practices.

Defining Female-Headed Households
There is no one standard definition of female-headed households. Following standardpractice for survey analysis, the study defines a female-headed household as a householdin which a woman is the primary decision-maker or income earner. The traditionalclassification of household headship is the “breadwinner” definition that defines thehousehold head as the one who contributes the most to household income. Based on
this definition, female-headed households were mainly defined by the absence of aman (due to divorce, death, migration, etc.). In recent years, this definition has beenrecognized as insufficient to capture the role of women within the household. It isestimated that, globally, women make up to 80 percent of purchasing decisions (Source:
The Economist. A Guide to Womenomics: Women and the World Economy). Thus, surveybased analysis typically classifies households according to both income contribution anddecision-making authority, as is done in this study. Relevant studies cited follow a similar
definition. For instance, the Indian Population and Household Census considers a female
household head if “she bears the chief responsibility for managing the affairs of thehousehold and takes decision on behalf of the household” (Source: Government of India
Population and Housing Census 2011).

9

INTRODUCTION CONTINUED

DEMANDPATTERNANALYSIS• Data mining and data analysis to estimate
market size
• Survey of clients and non-clients of financial
sector institutions• Market Segmentation

SUPPLY SIDECONSTRAINTANALYSIS• Semi-structured interviews with financial sector
institutions involved in housing finance• Institutional Assessment: Organizational
set-up, tools, MIS

ANALYSIS OF
THE ENABLINGENVIRONMENT• Semi-structured interviews with government
stakeholders• Assessment of the impact of legislation
on housing finance• Assessment of existing policies and strategies andtheir impact

PURPOSE OF THE STUDY
The study on which this report is based examines the
housing finance market for women and provides guidanceon specific barriers to women’s access to housing
finance, the market size that women borrowers mightpresent to the industry, and the possible need for specificgender-related housing finance products and services(e.g. mortgage, home improvement loans, incremental
construction loans, financial literacy training etc.). Theseissues are explored in the specific contexts of Colombia,
India, and Kenya.

OVERALL RESEARCHMETHODOLOGY
The research methodology consists of three modules:
an Analysis of Patterns of Demand for Housing Finance,a Supply-Side Constraints Analysis, and an Assessmentof the Enabling Environment. The demand assessment
focused on understanding the patterns of demand for
housing and housing finance for women in the three
countries. Data was collected on both access to housing
ownership (construction and/or purchase) and access

ImpactDesign ofPotential
Product
Concepts

Short Term
ImpactAccess to
Housing FinanceLong Term
Impact
Women Economic
Empowerment

to finance for home purchase and home improvement,
because groups of women may need housing financing
for several reasons, including purchasing houses, home
improvement, and construction. The purpose of the
supply-side analysis was to better understand operational
aspects of housing finance from the perspective of financial
institutions (i.e., their market positioning, target clientele,
product mix), and to obtain information on challenges inmortgage lending and financing women borrowers. Existinglegislation and other enabling factors were reviewed tounderstand their effect on housing finance. In this context,
an assessment of government programs to encourage
housing finance for women was also conducted.
A total of 2,000 low- and middle-income households
were surveyed to assess the demand pattern for
housing and housing finance. Households were surveyed
in Bogota and Cartagena in Colombia, Mumbai and Pune in
India, and Nairobi and Nakuru in Kenya. The survey collected
information on housing needs and housing finance needs
and identified gender gaps in obtaining housing finance.
The survey also collected information on challenges andconstraints facing women in accessing housing finance. The

10

Overall Findings

collected data was used to estimate the potential market
demand for housing and housing finance for women in thethree countries. The study primarily focused on urban and

CHARACTERISTICS AND
SEGMENTS WITHIN FEMALEHEADED HOUSEHOLDS

peri-urban areas where there is the highest concentrationof major financial institutions and where demand for
housing finance is highest.

Female-headed households, those in which a woman

For the supply-side research, major financial

is the primary income earner or decision-maker,

institutions offering housing finance were interviewed.

constitute 26 percent of households in Colombia,

The institutions included a mix of commercial banks,nine percent in India, and 25 percent in Kenya. In eachmicrofinance institutions, and other non-bank financialof these countries, male-headed households and joint

institutions. Semi-structured interviews were carried out

decision-making households have more access to bankswith top management in the housing market department

and other formal sources of finance than female-headed

and/or the fiduciary department of these institutions.

households. Female-headed households have lower

Unfortunately, a customer-journey analysis of loan

household income levels than those headed by men or byprocesses was not possible due to confidentiality concerns

joint-decision making households. This is particularly trueof the financial institutions.

in the lower income brackets, as in India where 90 percent
of female-headed households earn less than $620 per

Meetings also were held with government and policy

month. In Kenya and Colombia, a quarter of female-headed

stakeholders involved in enabling housing and housing

households earn more than $900 per month.

finance. The objective of these meetings was to understandwhether the current market environment is conducive for

Overall, self-employment is the most common source

promoting gender-housing finance and to identify housingof women’s employment, but this differs by country

initiatives that would benefit women.

and by income level. In Colombia, for example, 45 percent
of women in female-headed households are self-employed
and 20 percent are permanent employees. In Kenya, 		Impact of Woman-Focused Housing Finance

Goal

VehiclesOutcomes

Access to
Housing FinanceTargeted Financial and
Non-Financial Products
and Services

Asset Ownership
Reduced Vulnerability
Enhanced Productivity
Access to Economic
Opportunities

11

INTRODUCTION CONTINUED

Employment Status of FHHs

Although a small percentage of female-headedn Colombia

significantly larger proportion plan to apply for an Indiahouseholds have previously taken housing loans, a

n Kenyahousing loan in the next five years. Among femaleheaded households, eight percent in Colombia, six percent

Permanent employee

in Kenya, and five percent in India had applied for a housing
loan in the past five years. Those with higher monthly

Self-employedincomes are most likely to have previously applied for aPart-time employee

housing loan, with the highest level of previous experience
being in the income category of $621-900 per month. WhenDo not work

asked whether they are planning to purchase or build ahome in the next five years, female-headed households

Other

in Colombia and Kenya largely reported they were
0%

20%

40%

60%

planning to do so. Their demand did not differ significantly
across different income levels. In India, where levels of
homeownership are higher to begin with, a much smaller

46 percent are self-employed and 31 percent are permanent

proportion reported that they intend to buy or build. In

employees. However, in India, almost half of women in

India, demand is most concentrated in the lowest income

female-headed households do not work, and 36 percent arebracket (those making $310 or less per month), thoughmainly permanent employees. Female-headed households

the difference between income brackets is statisticallythat fall into the highest income bracket are generally

insignificant.

permanent employees, while in Colombia and Kenya, thosein the middle- and lowest-income brackets are mostly self-

Personal savings, followed by formal loans, are theemployed.

preferred source of housing finance among femaleheaded households. In Colombia, 62 percent of femaleheaded households turn to personal savings to purchase

Percentage of FHHs that have applied for
housing loan in previous 5 years

Percentage of FHHs planning to purchase orbuild housing in next 5 years

n Colombia

n Colombia

n Indian Kenya

40%

100%

20%

50%

0%

0%
USD 310or less

USD 311–620

USD 621–900

USD 901
or moren India

USD 310or less12

n Kenya

USD 311–620

USD 621–900

USD 901
or morePreferred Source of Funds for Housing Among FHHs by Monthly Income Bracket
n Formal loann Informal loann Personal savingsn Friends & family

Colombia
More than USD 900

50%

n Government subsidy

India

Kenya

50%

USD 621–900

33%

USD 311–620

22%

34%

USD 311 or less

25%

25% 13%

33%

36%

7%

57%

38%

13%

50%

30%

39%

6%

56%

10%10%10%

26% 9%

33%

22%

22%
38%

30%
10%

20% 20%60%

66%

housing; in India 37 percent; and in Kenya 22 percent. The

housing needs. Among lower income brackets, female-

highest proportion of female-headed households that plan

headed households in India show the highest level ofto use formal loans is found in the top income brackets.

household savings. Their monthly savings for the purpose

In Colombia and India, female-headed households in theof housing is approximately 20 percent of their monthly

lowest income bracket are using the greatest variety

income. This likely reflects India’s culture of saving andof fund sources to meet their housing finance needs. In

preference to use less of formal loans, which encourages

contrast, the upper income brackets can largely financeindividuals and households to save the maximum amounthousing needs through loans and personal savings alone. In

from income, particularly among older generations.

Kenya, the use of personal savings increases as income level
decreases. Female-headed households in the lowest income
bracket must save the most to finance housing purchases,

Female-headed households savings for housing

while in the upper income brackets they are better able toMedian monthly household savings for the purpose of
housing

access alternative sources of funds, including formal loans
and informal loans.
Median monthly savings for the purpose of housing

Monthly
IncomeBracket$311-620$621-900$900
or moreColombia $0

$47

$47

$126

month. In Kenya, where housing finance is largely not

India

$55

$69

-

-

available to low- and middle-income households, even the

Kenya

$19

$34

$34

$146

increases as monthly income increases. In Colombia, thelowest income bracket is currently not saving, on average,
while the highest income bracket is able to save $126 eachlowest income bracket is saving $19 each month. In India,
the highest income brackets generally already own theirhomes and are therefore not currently saving explicitly for

13

$310
or less

COLOMBIA Key Findings$23 billion
Estimated size of market for women’s housing loans
Market profile

67% of households have a woman

64% of female-headed

involved in financial decision-making

households use personal savings toacquire their housing; only 27% used

8% of female-headed households

a formal loan

applied for a housing loan in theprevious 5 years

The median loan amount that joint
decision-making households expect

Female-headed households
save

to borrow is

100% more, on average, than

$9,462male-headed households

Current access to housing financeare the source of 77%• ofBanks
housing finance loans obtained by womenfrom cooperatives
• 18%
5%
from
informal financing•

Opportunity

20% of female-headed

23% of female-headedhouseholds plan to take ahouseholds are planning

73% of women wholoan for housing finance inhome improvements

plan to purchase housing

the next 5 years

Houses are preferred by(27% prefer apartment)

14

3. Colombia
There is high demand for housing loans among womenInside the findings: While 33 percent of female-in Colombia, but they remain constrained by unstable

headed households inherited, compared to 17 percent ofincome. In all, 20 percent of female-headed households

male-headed households and 10 percent of household

and 44 percent of joint decision-making householdswith joint decision-making, approximately 50 percent ofplan to purchase a home in the next five years, and 23

households with female decision-makers did purchasepercent plan to make home improvements. Banks are

their housing. This compares with 69 percent of male-the main source of housing loans preferred by 77 percent

headed households and 67 percent of joint decision-of women, and houses are the preferred dwelling typemaking households who purchased their housing.

(73 percent). The market for women in Colombia isestimated at approximately $23 billion. Yet, women remain
disadvantaged in obtaining housing loans because ofForm of Acquisition of Houseeconomic inequalities, including lower income and fewer

n Men

n Womenn Joint

formal employment opportunities.
80%

Market Profile

60%

Home ownership in Colombia is among the lowest

20%

40%

in Latin America. Colombia’s National Statistics Office0

defines a housing deficit as a lack of adequate housing,

Boughteither a qualitative housing deficit or a quantitative housing

Inherited

Constructed

deficit. Even though the housing deficit across Colombia has
been steadily declining over time, home ownership remains

Regardless of decision-maker gender, home ownershiplow by regional standards.

is driven by income and age, according to IFC’s
research. With age, households accumulate more income

Gender does not appear to be a significant driver ofand wealth, and so are more likely and able to buy a housequantitative housing deficits. When disaggregated byand less likely to rent. However, households with a male-gender, Colombia’s National Statistics Office study founddecision maker are more likely to own a house across allthat quantitative housing deficit statistics show only atypes of family structure (for nuclear family, joint/extended

small variation between male-headed and female-headed

family, or for single adults) compared to households with ahouseholds across Colombia’s departments. The only

female decision-maker. Households with female decision-

exceptions are Córdoba and Santander. In Córdoba, themakers rent more than their male-counterparts across allquantitative deficit for male-headed households is estimatedtypes of family structures.

to be about nine percent compared to 5.5 percent of femaleheaded households. In contrast, in Santander, the quantitative

Sixty-four percent of female-headed households used

deficit for female-headed households is 12.6 percent,personal savings to acquire their housing; only 27

compared with 9.8 percent for male-headed households

percent used a formal loan. Among homeowners, maleheaded households were more likely to have used a formal

Female housing owners are more likely than maleloan than female-headed households.

owners to obtain housing through inheritance.
Households with female decision-makers inherit at a higher
rate than their male counterparts.

15

COLOMBIA CONTINUED

Home Ownership

Women

Men

Joint

Home Ownership by Age

Type of Ownership by Family Structuren Womenn Women

n Men

80%

n Men

n Joint

Singles

60%
40%

Joint/Extended Family

20%0%

Nuclear Family
18-24

25-34

35-44

45-54

>55
0% 20% 40% 60% 80%

Home Ownership by Monthly Income
Distribution
n Womenn Menn Joint

60%
40%
20%
0%
		
Less than USD340– USD 510– USD 680- More than		

USD 340

510

680

850

USD 850

NOTE: The above findings derive from IFC’s market study (2018). (A separate study, La Gran Encuesta Integrada de Hogares —GEIH 2017, while composed of a smaller and more specific data set — 140,000 urban households, no ex-urban households —produced similar results.)

16Inside the findings: Overall, 45 percent of homeowners
used formal loans and 45 percent used personal savings to

Use of bank loans for housing is very low inpurchase their housing. Among male-headed households,

Colombia. Only nine percent of men and eight48 percent used formal loans and 44 percent personal

percent of women have previously applied forsavings. For making improvements to housing, thehousing loans. Of these, 67 percent of men and 47

majority of homeowners used personal savings, followed

percent of women had their loans approved.

by formal loans, with no significant gender variation. Useof informal loans and borrowing from friends and family
is extremely limited for housing acquisition or home
improvement.

Inside the findings: Fifty-three percent of loan
applications were for the purchase of new housing. While

Source of Funds for Housing Acquisition andHome Improvement

only a few survey respondents applied for housing loans,n Womenat savings/credit cooperatives. (It should be noted thatn Men

the data show that men were more likely to be approvedat banks, while women were more likely to be approvedn Joint

these differences are not statistically significant given theHouse
Acquisition

very small sample size.) Additionally, borrowers whose44%

Formal Loan
Friends/Family
Informal Loanloans were approved had been clients of the bank for

38%

Personal Savings
27%

62%

more than two years.

56%
48%

In general, both on a monthly basis and in terms of0%

total current savings, women have higher savings

8%
6%
3%
4%
2%

than men. While female-headed households have a lower
median monthly income than male-headed households andjoint decision-making households, monthly expenses are

Home
Improvement

similar for female- and male-headed households and higher

Personal Savings

Employer Loan

Informal Loan
Other

by women are saving more than their male counterparts.

24%
21%
19%

Formal Loan

Friends/Family

for joint-decision-making households. Households headed

57%
63%
65%

10%

Median Income, Expenses and Savings

11%

Head of
Monthly Monthly
Household income
expenses

Monthly Totalsavings Savings

Woman

$520

$312

$35

$139

Man

$555

$312

$0

$0

Joint

$694

$347

$35

$121

2%
5%
2%

3%
5%
5%
8%

0% 10% 20% 30% 40% 50% 60% 70%

17COLOMBIA CONTINUED

Current Access to Housing
Finance and Supply

Barriers

Colombian financial institutions have been steadily

to be a result of unstable income and difficulties

increasing their mortgage portfolio since the crisis

qualifying for a loan. A lack of money was the primaryof the late 1990s. Between May 2016 and 2017 alone, thereason non-homeowners gave for not wanting to purchasecombined outstanding real estate loan portfolios of financial

housing within the next five years. Only about 12 percent ofinstitutions increased by 13 percent, reaching $20.6 billion.

women reported not qualifying for a loan as the reason not

Bancolombia, BBVA, and Davivienda are the largest lenders.

to purchase housing as compared to 32 percent of men.

The main barriers to housing finance are largely foundRent-to-own arrangements represent approximately 23
percent of residential loan portfolios; 58 percent of these

Inside the findings: While both women and men

arrangements are held by Davivienda.

reported a lack of money as the primary obstacle topurchasing housing, 50 percent of women cited thisGovernment-supported programs represent a large

compared to 41 percent of men.

part of the housing finance market. The two main
programs are the vivienda de interés social (affordable

Reasons for Not Planning to Buy a Home
(LHS)/Perceptions of Equal Access to
Housing Finance (RHS)

housing —VIS) and the vivienda de interés prioritario (priority
social housing — VIP). Both programs involve subsidized
interest rates for lower income segments of the population.
However, VIP targets the most vulnerable groups, includingn Womenfemale-headed households.

n Men

		

I don’t have money		41%

The satisfaction rate among men and women receiving
loans was 75 percent. While taking into account that only3%
Gender barriers		a very low percentage actually applied for formal loans,satisfaction was based largely on the fact that clients were39
		I don’t need it		36%

able to receive their loans quickly, followed by a perception12%			
I don’t qualify for a loanof favorable terms and conditions. The dissatisfied clientscomplained mostly about not receiving the desired amounts
and interest rates.

Other

50%

%

32%

9%

		
0% 10% 20% 30% 40% 50%

Survey respondents also reported requirements frombanks as significant challenges to obtaining housing
finance. A lack of credit records, low income, and highinterest rates were also commonly cited as challenges toobtaining housing finance.

18

ADDITIONAL INSIGHTS INTOBARRIERS TO HOUSING FINANCE
ACCESS

Women loan applicants might be disadvantaged due totheir generally lower level of income and more common
employment in the informal sector. When two or moreindividuals apply for a loan together, the first debtor toappear on the loan contract is the person with the highest

The following insights derive from a series of logistic

income. Typically, this is the male partner. In addition,

regressions (see Notes for a detailed explanation and amost of the financial institutions that were interviewed

chart of results) that identify potential factors affecting

reported that they focus their efforts on applicants withwomen’s demand for housing and loans. Model One

formal employment and proper income justification. A

identifies the predictors of planning to buy a house orlarger proportion of women are employed in the informal

making improvements to a current dwelling in the next fivesector, and thus unable to fulfill the lending requirements ofyears. Model Two identifies the determinant factors related

financial institutions.

to existing demand (i.e., having used a loan in the purchaseof the current home). Comparing the two models provided
preliminary findings on the Colombia housing market.

Inside the findings: The above disparities between(Please note that the sample is distorted towards urban

male and female loan applicants are in line with statistics

and peri-urban men and women, and does not include rural

showing that 7.3 percent of Colombian women have

respondents.)

outstanding mortgages compared to 12.3 percent for men(2014). Source: Findex Database.

Being a woman decreases the probability of being
employed by 35 percentage points, all other factors

Loan Approval Ratebeing equal. A logistic regression fitted to identify

n Womenkey independent variables, including gender, age, civil

the determinants of employment identified severaln Menstatus, and having a bank account. The results indicatethat traditional socio-cultural norms still play a role in

Savings/Credit
Cooperative

Colombian society, particularly regarding employment, thus
contributing to women’s economic disadvantages.
Economic disadvantages put a disproportionate strain

Bankon women’s ability to access housing finance. The
0%

20%

40%

60%

majority of respondents reported that women and men

80%

enjoy equal rights, and that they did not see gender itself
as a significant barrier to obtaining housing finance. Yet,

Respondents perceive gender-specific economic factors

women cited insufficient income and resources as the main

drive inequalities in access to housing finance. The

barrier to accessing housing finance. Among women who

majority of both men (81 percent) and women respondents

would like to be able to purchase housing, 68 percent of(68 percent) reported that women and men enjoy equal

those not planning to purchase cite not having enoughaccess to housing finance. However, respondents perceived

money as the biggest barrier to doing so. This suggests that

opportunities between genders to be unequal. Thosethe gender and socio-cultural norms that impact the ability

respondents who think women do not have equal accessof women to participate fully in economic life also have an

to housing finance as men cited less favorable employment

adverse effect on their ability to access housing finance.

opportunities and income gaps as the main barriers towomen’s access to housing finance.

19

COLOMBIA CONTINUED

Female-headed households are less likely to participate

ACCESSING INSTITUTIONS

in the housing and housing finance markets. Even after

1. Are wives required to obey theirhusbands?

controlling for income and socio-economic differences,
households in which a woman is the household head areNo

2. Can a woman legally get a job in the same Yes
way as a man?

significantly less likely to be planning to purchase a homeor make improvements to their current home.

3. Can a woman sign a contract in the same
way as a man?

Yes

ADDRESSING BARRIERS: LEGAL,REGULATORY AND FINANCIAL
INSTITUTIONS FRAMEWORKS

4. Can a woman open a bank account in thesame way as a man?

Yes

5. Can a woman choose where to live in thesame way as a man?

Yes

6. Can a woman be “head of household” inthe same way as a man?

N/A

In Colombia, policies, regulatory framework, and laws
treat men and women the same. Similarly, there are
no practices in financial institutions that explicitly

USING PROPERTY

distinguish between men and women. This was

1. Who legally administers marital property?

Originalowner

2. Does the law provide for valuation of
nonmonetary contributions?

Yes

opportunities reported in the demand survey.

3. Do men and women have equal
ownership rights to immovable property?

Yes

Women, Business and the Law

4. Do sons and daughters have equal
inheritance rights?

Yes

5. Do female and male surviving spouses
have equal inheritance rights?

Yes

confirmed in interviews with stakeholders in government
agencies and financial institutions. Moreover, there was no
indication of institutional discrimination causing unequal

Women, Business and the Law is a World Bank Groupproject collecting unique data on the laws andregulations that restrict women’s economic

GOING TO COURT

opportunities. The following findings for Colombia are

1. Does a woman’s testimony carry thesame evidentiary weight in court as aman’s?

relevant to women’s access to housing finance.

Yes

BUILDING CREDIT

20

1. Do retailers provide information to credit
agencies?

Yes

2. Do utility companies provide information
to credit agencies?

Yes

3. Is discrimination based on genderprohibited in access to credit?

No

4. Is discrimination based on marital statusprohibited in access to credit?

NoGovernment Programs

Financial Institutions

Vivienda de interés social (VIS — affordable housing) and theNone of the financial institutions that werevivienda de interés prioritario (VIP — most vulnerable groupsinterviewed used different loan approval criteria forincluding female-headed households) are the government’s

men and women.

two social housing programs. Davivienda is the main lenderunder social housing programs followed by Fondo Nacional

Inside the findings: Meetings were held with 16

del Ahorro, Bancolombia, and Banco Caja Social.

financial institutions, including all the main lenders inhousing finance. According to interviewed stakeholders,Within this context, the Colombian Government has

financial institutions use gender-neutral approaches andbeen increasing efforts to encourage marginalized

policies in their day-to-day-business.

women to facilitate ownership of their own housing.
According to the Ministry of Housing, more than 238,000
women from low-income households have become

Financial institutions do not keep gender-

owners of their proper houses since 2010. An additional

disaggregated statistics on client applications or

51,268 women in the poorest neighborhoods have obtained

rejections. Because of this, financial institutions are

housing through “Mi Casa Ya — Ahorradores,” and 169,368

not able to track potential gender-based distinctions

women in extreme poverty are benefitting from the freethroughout the loan application process and have limited

housing program. (Source: http://www.minvivienda.gov.

ability to understand the characteristics and financial

co/sala-de-prensa/noticias/2016/noviembre/el-70-de-

behavior of their customers by gender. The Superintendencia

propietarios-de-vivienda-en-colombia-son-mujeres-

Financiera de Colombia, which supervises the main actors inministra-elsa-noguera)

housing finance, also does not track gender-disaggregatedinformation.

21

COLOMBIA CONTINUED

Market Opportunities

The potential demand for housing, based on

Approximately 43 percent of women living in rented

higher for men than women. About 56 percent of

housing plan to purchase housing within the next

women expect to seek funding from banks as opposed toyear. According to the demand survey, about half of

60 percent of men.

respondents planning to purchase, is only four percent

respondents overall plan to purchase housing within thenext five years. About 65 percent of men respondents planto purchase a house.

Non-homeowners Median Expected Costof New Home Purchase

Approximately 26 percent of current homeowners plan
Cost ofpurchasing

Loan
amountneededExpectedMonthly
payment

Woman$27,200$17,179$136

Man$23,800$19,550

$187

Joint

$26,500$16,563$133

to move to or construct another house. This percentage
is only slightly lower for women than it is for men.
Another 30 percent of homeowners plan to make
improvements to their current home. Male-headedhouseholds are significantly more likely to plan to make
improvements than female-headed households, but slightly
less likely than joint decision-maker households.
The plan to purchase varies by income levels. Middle/
low-income households earning between $340-680 amonth are most likely to have plans to purchase housing as
compared to households with other income ranges.

Cluster Analysis identified opportunities for tailoring
housing products and services to specific groups
who plan to purchase housing in the next five years.
The analysis of demand survey responses (see Notes formore detail on Cluster Analysis) identified homogenous
subgroups of potential customers that have similar needs
and attributes, and thus represent sub-markets for targeted

Non-homeowners and Homeowners Who Plan
to Purchase or Make Housing Improvements

products and services. As indicated in the chart below, itn Womenhousing among four major sub-segments of urban and peri-n Menn Joint

studied variables of employment, type of current dwelling,
income, and the expected loan amount needed to purchaseurban men and women (thus this study did not cover rural
men and women).

Purchase/build[non-owners]

The total size of the urban market for women’s housing
loans in Colombia is estimated at approximately

Move/construct[owners]$23 billion. This total market size represents the total
estimated amount of loans needed from urban women in
Colombia who currently have plans to purchase a home. It was

Improvements[owners]

estimated from values including number of urban households,
percentage of female-headed households, percentage of0%

10% 20%30% 40% 50%

60%

women who reported they would use a loan to pay forthe purchase of housing in the next five years, and median
expected loan amount, relying on figures from the demand
survey and census data. More detail on this calculation
appears in the Notes section at the end of this report.

22

Cluster Analysis of Potential Housing Finance Market
Segment 1

Segment 2

Segment 3

Segment 4

MarriedEmployee

Self-employed/
Entrepreneur

Non-married
Employee

Self-employed/
Entrepreneur

House

Apartment

House

Apartment$1,189

$509

$408

$408

$33,961$23,773$20,378$27,169

Variables Used in Clustering:
Employment (of respondent)

Type of dwellingMedian Household Income(from all contributing family
members)*

Loan Amount Desired†

Other Key Variables:
Sector of Employment
Commerce
Commerce
Manufacturing/
			Construction
Average Age

31

39

34

Services
34

Marital status

69% Married
42% Married
60% Single
36% Married
19% Cohabitating
35% Single
34% Separated/
31% Single
12% Separated/
23% Cohabitating		
Divorced
25% Cohabitating
		Divorced			
6% Widowed
8% Separated/								Divorced
Average Number of family members
contributing to household income
Percentage of Households with
Female Household Head
Percentage of Households with
Woman Involved in Decision-making
Percentage of Households withBank Account
Percentage Applied for Housing
Loan Previously

2.25

2.06

0.95

1.65

24%

48%

41%

66%

58%

70%

68%

76%

65%

56%

41%

45%

6%

29%

6%

7%

*Median household income is the median income brought in for the household by all family members. If the respondent does not work and is notbringing income, the household can still have income from a spouse, parents, adult children, etc.
† Loan amount desired is based on respondent’s own evaluation of amount needed for home purchase or construction and not a reflection offinancial analysis of repayment capacity

23

INDIA Key Findings$32.3 billion
Estimated size of market for women’s housing loans
Market profile

48% of households have a woman

Female-headed households save

20% more, on average, thaninvolved in financial decision-making

male-headed households

6% of female-headed households

The median amount that joint

applied for a housing loan in thedecision-making households expect

previous 5 years

to borrow for home purchase is$16,563

Current access to housing finance loans obtained by women• Banks 83%• Mutuals 8%• Cooperatives 5%
Opportunity

5% of female-

18% of female-

Apartments are

49% of joint

headed households

headed households

preferred bydecision-making

plan to take a loan

are planning home

for housing financeimprovements

84% of womenin the next 5 years

apartmentspurchase housing(29% houses)(16% prefer houses)

24

households live in

who plan to4. India
The estimated demand for women housing loans

An estimated 65 percent of female-headed households

in India totals $32.3 billion. This demand is largely forand 63 percent of male-headed households live inapartments (84 percent), rather than houses. Eighty-

houses..

three percent of women prefer banks to other financial
institutions for housing finance. The main barriers to

Inside the findings: In joint decision-making

women’s access to housing finance are found to behouseholds, apartments are most common (49 percent),

insufficient income and traditional gender norms. For

followed by houses (29 percent) and chawls (22 percent).

instance, in the demand survey, 52 percent of households

Chawls are buildings with one room or two room units

had no female involvement in decision-making. The

of not more than two hundred square feet attached by agovernment’s Credit Linked Subsidy Scheme provides acommon corridor with shared toilets on each floor.

subsidized interest rate on housing loans if a woman willhold the title to the new property. The program, althoughbringing more women into the housing finance market, isSignificant drivers of home ownership include age,

only able to reach a small portion of the potential female

education, income, length of occupancy, and city.

borrowers. Thus, a gap remains.

According to results of the demand survey, respondents’age and education and their household’s income affectthe likelihood the household owns rather than rents theirMarket Profile

housing. Additionally, the more years a household has
resided in the current dwelling, the greater the probability

Home ownership is relatively high in India. Seventy-

they own their home.

seven percent of households own their homes, rather thanrent. This percentage is the same for households headed

Households headed by women have similar income andby a man, woman, or joint decision-makers. Of those who

expenses, but higher monthly savings than households

own, 93 percent have a registered title deed.

headed by men (Source: demand survey). Female-headedhouseholds are saving more than their male counterparts,

Inside the findings: The 77 percent figure is consistentand also at similar levels as joint decision-making

with findings from the most recent census collected byhouseholds, although the income and expenses of joint

the government in 2011 (Source: Government of India

decision-making households are higher than female-headed

Population and Housing Census 2011), which found thathouseholds.

87 percent of households own their own home. The 10
percent difference is due to this study’s focus on low- andMedian Income, Expenses and Savings

middle-income households, which are less likely thanhigh-income households to own their homes.

25

Monthly
incomeMonthly
expenses

Monthly
Savings

Total
Savings

Woman

$364

$218

$73

$1,456

Man

$364

$218

$58

$1,165

Joint

$437

$291

$73

$1,456

INDIA CONTINUED

Female legal ownership of homes is rare. Only nine

Across home purchasers, use of formal loans

percent of households in the demand survey sample

remains low overall. Among survey homeownerhave a female head of household. (This is consistent

respondents, joint decision-making householdswith the 2011 census, in which only 10 percent

were more likely to use formal loans (33 percent)of households had a female head of household.)and informal loans (22 percent) than female-headed

Additionally, among households that own, 81 percent

households and male-headed households, whichhave a man as the sole legal owner of the house,primarily used personal savings. However, female-nine percent are legally owned by a woman, and 10

headed households were more likely than male-percent are jointly owned. This indicates that evenheaded households to use formal loans. For housing

among joint heads of households (38 percent), theimprovements, the majority of households, regardlesslegal owner of the house is generally a man.

of gender, relied on personal savings.

Purchase is the most common form of acquisition,

Inside the findings: These low levels of housing loan

but inheritance is highest among female-headed

usage are consistent with statistics from Findex, whichhouseholds and joint decision-making households.

shows that only three percent of women and six percent

Thirty-seven percent of female-headed households,of men currently have outstanding mortgages. (Source:

44 percent of joint decision-making households, andWorld Bank Global Financial Inclusion — Findex —only 18 percent of male-head of households own their

Database.)home via inheritance.

Source of Funds for Home Acquisition
Household Head		Legal Ownern Womenn Joint

9% 10%

10%

Personalsavings

38%
52%

81%

n Womenn Men

Formal loann Joint

Informal loan

Borrow fromfriends/family

Means of Home Acquisitionn Women

n Men

n Men

n Joint

		0% 10% 20% 30% 40% 50% 60% 70%

80%
60%
40%
20%
0%
Bought

Built

Inherited

26

The recent rise in dual-income households, particularly

HFCs. However, commercial banks are targeting more inin urban areas, has increased the demand for housing

the urban areas, whereas HFCs are targeting in urban andfinance loans among joint decision-makers.

semi-urban areas. Rural areas are largely excluded by thesefinancial institutions.

Inside the findings: The Demand Survey indicated that

Most of the financial institutions that werewhile all female-headed households and 91 percent ofinterviewed do not have specific gender products

male-headed households applied to banks, 67 percent ofor services targeting women as a differentiatedjoint households applied to banks as well as to mutual

segment. However, a few exceptions exist such as the(17 percent), cooperatives (8 percent), and microfinanceState Bank of India (SBI), SEWA, and Aspire Home Finance.

institutions (8 percent).

SBI’s Her Ghar loan is offered to female customers at aconcessional interest rate. SEWA Grih Rin Ltd. (SGRL)
only lends to women for the explicit purpose of house

Current Access to Housing
Finance and Supply

purchase, construction, upgrading, or home improvement.
Aspire Home Finance has a product entitled “Mahila Awaas(MALA),” which offers housing loans to low-income women

Housing finance has traditionally been dominated byat a lower interest rate.

banking institutions, but housing finance companies
are playing an increasingly larger role. In 2015, banks

Financial institutions do not use different loan approval

controlled 63 percent of the total volume of the housing

criteria for men and women applicants. FIs reported

finance market, with the rest of the market served bythat internal policies, regulations, and practices are gendernon-bank financial institutions (NBFIs), primarily Housing

neutral. The FIs largely reported that the loan origination

Finance Corporations (HFC). Estimates from 2017, however,process is the same for male and female borrowers and thatsuggest HFC’s market share has grown to over 40 percent.

loan decisions are based on eligibility criteria such as income
and repayment capacity. However, gender-disaggregated

Affordable housing loans are provided by the majority

statistics or data on client applications or rejections are notof banks that are involved in housing finance and by

being kept.

Inside the findings: The historic gap between the market share of banks and non-bank financial institutions is primarily
due to banks’ access to Current Account and Savings Account funds, which come at a very low cost. In contrast, NBFIs— including Housing Finance Corporations — primarily have had to rely on costlier bank funding, and thus charge higher
interest rates to customers. However, in recent years, the average interest rates charged by banks and major HFCs have
converged. As a result, HFCs are becoming an increasingly important element of the housing finance sector, accounting fortheir increased market share as of 2017.

Housing Finance Market Share of Major Housing Finance Providers
SBI Group

19%

HDFC

18%

LIC HFL

9%

ICICI

9%

Source: ICRA 2016 Estimates

27

Axis Bank

5%

Dewan

4%

Canara

3%

PNB

3%

INDIA CONTINUED

Reasons for Not Planning to Buy a Home
Most FI mortgages are given to married couples.

n Womenn MenAmong those who have applied for a loan recently,
joint decision-making households were approved

I don’t have moneyat a rate of 83 percent, compared to 66 percent for

I don’t need it

male-headed households and 57 percent for femaleheaded households.

I don’t quality for a loan/program
Gender barriers
Other
		0%

FIs interviewed for this study believe that loan

20%

30%

60%

repayment is enhanced when women are co-borrowers.
While no data was available to justify the following
statement, FIs reported that their loans’ delinquency
significantly declines when a woman is a co-applicant
because it increases the likelihood that the loan will be
repaid.
The satisfaction rate was very high among survey
respondents and did not show any difference by gender.
The satisfaction rate was 96 percent, and based largelyon the fact that clients perceive terms and conditions as
being favorable, followed by the fact that clients wereable to receive their loans quickly. As suggestions, most
respondents recommended reducing the interest rate
charged.

However, women still remain disadvantaged becauseof their lack of formal and stable income. Although
the government’s Credit Linked Subsidy Scheme programis helping, the share of loans with a woman as the main
applicant is very low compared to loans with a man as themain applicant.
Traditional gender norms also limit women’s ability
to access housing finance Single women applicants.
Financial institutions, despite having gender neutral
processes reported they would likely use a higher level ofscrutiny in evaluating a single woman’s application than asingle man’s application because cultural norms suggest asingle woman should not need to purchase a home, doing
so with her husband once she is married.

Barriers

Formal and stable income. Only 15 percent of women

Fifty-four percent of respondents believe financial

are the main contributors to household income, compareddecisions should be made by men, or were unsure

to 89 percent of men. As a large segment of population

whether financial decisions should be made only by

including women is still found in the informal sector.

men. Only 15 percent of women are the main contributors
to household income, compared to 89 percent of men.

Too many requirements make it difficult to accessloans. Survey respondents who plan to purchase in the

For men and women, the main barriers to accessnext five years plan to use informal rather than formal loans

housing finance are largely found to be a result of

because of such requirements as identification, income

insufficient income. While both women and men reported

statements, and credit history. The next most common

a lack of money as the primary hindrance, a greater sharereason for using informal loans was that respondents couldof women (55 percent) cited this compared to men (47not offer collateral.

percent). Another 20 percent of women and 27 percent ofmen mentioned not qualifying for a loan or program as thereason not to purchase.

28

ADDITIONAL INSIGHTS INTOBARRIERS TO HOUSING FINANCE
ACCESS

Inside the findings: Sixty-seven percent of femaleheaded households, 65 percent of male-headedhouseholds and 72 percent of joint decision-making
households reported they would use an informal loan.
Formal loans and personal cash/savings are the next

To provide additional insight into potential factors driving

most frequently mentioned. Thirty-three percent

women’s demand for housing and for loans, a series ofof female-headed households also planned to use alogistic regressions were fitted. The first logistic regression

government subsidy.

(Model 1) aimed to identify the predictors of planning tobuy a house or make improvements to a current dwellingin the next five years. The second logistic regression (Model

What Is Your Reason for Using an Informal,
Rather Than Formal Loan?

2) aimed to identify the determinant factors related toexisting demand (i.e. having used a loan in the purchase of
the current home). Comparing the two models provides
additional insight into the Indian housing market. (SeeToo many requirements

Notes for a detailed explanation and a chart of results.)

Lack of collateral

Women are seen as main caretakers of the home andHigh interest ratefamily. Analysis results indicate that being a woman

Lack of title

decreases the probability of being employed by 38
percentage points, all else equal.

		 0% 20% 40% 60% 80% 100%

Women’s lower socioeconomic status plays a role inThis lack of applicant documentation hampers financial

determining whether and where they find employment,

institutions’ ability to lend. A lack of clear property

how much income they generate, and therefore theirtitles of potential borrowers — essential for the purpose ofability to access housing finance. According to the World

collateral — makes it difficult for financial institutions to

Values Survey 2012, almost 80 percent of respondents inprocess the loan.

India agreed that when jobs are scarce, men should havemore right to a job than women. As a result, women are

Inside the findings: These factors contribute to thesignificantly more likely to not work or to work from homechallenge of meeting document requirements: 1) In India,

than their male counterparts. This makes it more likely thatland is a state subject, and each state has its own set of

women will not have enough money to purchase housing orlaws governing property titles; 2) Households working

qualify for a loan.

in the informal labor sector or daily jobs are not able toproduce proper income documentation.

Women’s labor force participation in India is very low.
Since its decline in recent years from 35 percent in 2005

Limited funding is another constraint for financial

to its current 27 percent (World Bank World Development

institutions. This is especially true for small Housing

Indicators), India’s female labor force is the lowest among

Finance Corporations and Microfinance Institutions, which

G20 countries with the exception of Saudi Arabia.

rely on commercial banks for capital funds.

Female-headed households are significantly less likely
than male-headed households to plan to purchase ahome in the next five years. They also are less likely tohave previously used a formal loan to acquire housing.

29

INDIA CONTINUEDADDRESSING BARRIERS: LEGAL,REGULATORY AND FINANCIAL
INSTITUTIONS FRAMEWORKS

Inside the findings: Over the medium- and long-

The government of India’s focus on “housing for all” by

As result, a large number of institutions have recently

2022 has increased the attractiveness and the size ofentered the market. Banks also have increased their focus

this sector; continued growth is expected. The housing

on retail housing finance, increasing competition within

finance industry has achieved a cumulative 17-18 percent

the roughly $36,000-to-$1,086,000 (Rs. 25-to-75 Lakhs)

annual growth rate over the last five years. Total housing

housing market. HFCs operating in the affordable housing

credit outstanding in India stood at roughly $198.5 billion

space ($36,000 or Rs. 25 Lakhs loan category) have been(Rs. 13.7 trillion) as of December 31, 2016, up from roughly

growing and are expected to register a compound annual$179.6 billion (Rs. 12.4 trillion) in March 2016.

growth rate of 30-to-50 percent over the next three-to-term, it is expected that the industry will grow 18-to-20
percent, driven by the growth in affordable housing space
and increased support from the central government.

five year period, outpacing the industry average.

30

The Government of India’s Pradhan Mantri Awas Yojana

ACCESSING INSTITUTIONS(PMAY) initiative is designed to provide affordable

1. Are wives required to obey theirhusbands?

housing to the urban and rural poor, with a specificfocus on female empowerment. Under the PMAY’s Credit-No

2. Can a woman legally get a job in the same Yes
way as a man?

Linked Subsidy Scheme for the urban poor, the government
grants a subsidized interest rate of up to 6.5 percent forindividuals within the Economically Weaker Section anda Low Income Group who are seeking housing loans frombanks, housing finance companies, and other financial
institutions. To obtain the subsidy, the title must include
at least one woman, which can be the female household
head or any relative of the male household head including awife, mother, sister, etc. This program has been successfully

3. Can a woman sign a contract in the same
way as a man?

Yes

4. Can a woman open a bank account in thesame way as a man?

Yes

5. Can a woman choose where to live in thesame way as a man?

Yes

6. Can a woman be “head of household” inthe same way as a man?

N/A

USING PROPERTY

attracting women as co-applicants for housing loans.

1. Who legally administers marital property?

Original
owner

Inside the findings: Financial institutions that wereinterviewed for this study had positive perceptionsof the PMAY program and believed it was improving
women’s access to housing finance and access to housing
ownership.
To improve the flow of formal housing finance to womenin urban areas, the National Housing Bank launched a

2. Does the law provide for valuation of
nonmonetary contributions?

No

3. Do men and women have equal
ownership rights to immovable property?

Yes

4. Do sons and daughters have equal
inheritance rights?

Yes

5. Do female and male surviving spouses
have equal inheritance rights?

Yes

Special Refinance Scheme for Women for retail-lending

GOING TO COURT

institutions. The program provides refinance assistance to

1. Does a woman’s testimony carry thesame evidentiary weight in court as aman’s?

primary lending institutions at concessional rates where theprimary borrower is a woman and the property is solely or
jointly owned by women. Its purpose is both to encourage

Yes

BUILDING CREDIT

women to acquire residential property in their own name

1. Do retailers provide information to credit
agencies?

Nothrough eligible primary lending institutions.

2. Do utility companies provide information
to credit agencies?

No

Women Business and the Law

3. Is discrimination based on genderprohibited in access to credit?

No

4. Is discrimination based on marital statusprohibited in access to credit?

Noand retail-lending institutions to improve their housing
finance to women borrowers. The program is implemented

Women, Business and the Law is a World Bank Groupproject collecting unique data on the laws andregulations that restrict women’s economic
opportunities. The following findings for India are relevant
to women’s access to housing finance31

INDIA CONTINUED

Market Opportunities
While the decision of where to apply for a

About five percent of women expect to make a homehousing loan varies by gender, 47 percent ofpurchase in the next five years using a formal loan

women respondents to the demand survey

compared to 13 percent of men. The median expected loan

based their decision on an advertisement andamount for male-headed households is $8,734 compared with

29 percent on a reference from a friend. No$7,279 for female-headed households and $9,462 for joint

female-headed households reported that theirdecision-making households.

decision was based on the best interest rate or
terms.

Female-headed households are more likely to be planning
improvements to their homes than those headed by men.

Inside the findings: In contrast, reference from afriend is the most common basis for a decision

Inside the findings: Eighteen percent of female-among 51 percent of male-headed and 54

headed households are planning improvements, more

percent of joint decision-making households) but

than both male-headed households (13 percent) and joint

best interest rate or terms is the second mostdecision-making households (12 percent). Twelve percent

commonly mentioned reason (mentioned by 43of female-headed households and 11 percent of joint

percent of male headed and 46 percent of joint

decision-making households are planning to purchase ahouseholds)..

new home in the next five years, compared to 16 percent
of male-headed households.

Households Planning to Purchase or Make
Improvements in Next 5 Yearsn Womenn Menn Joint

Purchase/build(non-owners)
Move/construct(owners)

47%

29%

Women’s decision
based on an
advertisement

Women’s decision
based on areferenceand thus represent sub-segments for tailored products andservices. (Because the demand survey focused on urban
and peri-urban men and women, these results do not coverrural men and women.)

Improvements(owners)

The total size of the urban market for women’s housing
loans in India is estimated at approximately $32.3

		0% 5% 10% 15% 20% 25% 30% 35% 40%

billion. The total market size represents the total estimatedamount of loans needed from urban women in India whocurrently have plans to purchase a home. It was calculated

Cluster Analysis identified opportunities for tailoringfrom values including number of urban households,

products and services to specific groups who plan topercentage of female-headed households, percentage

purchase housing in the next five years. The analysis

demand, and median expected loan amount, relying onof demand survey responses (see Notes for more detailfigures from the demand survey and census data. Moreon Cluster Analysis) identified homogenous subgroups ofdetail on this calculation appears in the Notes section at thepotential customers that have similar needs and attributes,

end of this report.

32

Cluster Analysis of Potential Housing Finance Market

Segment 1

Segment 2

Segment 3

Segment 4

Variables Used in Clustering:
Employment (of respondent)
100% Does not
100% Does
47% Part-time
31% Self-employed		
work		
not work 		
employee
28% Permanent					
33% Permanent		
employee						
employee
28% Part-time					
15% Self-employed		 employee
					
5% Non-contract 14% Non-contract
Home ownershipMedian Household Income(from all contributing family
members)*

Rent

Own

Own

Rent

$291

$364

$437

$291

$14,557$6,046$9,462$6,551

Loan Amount Desired†

Other Key Variables:
Sector of Employment
Commerce
Commerce
Manufacturing/
			Construction
Average Age

34

37

34

Marital status
100% Married
90% Married
73% Married		
7% Single
23% Single
			
3% Widowed
4% Widowed/						 Divorced
Percentage of Households with
Female Household Head

Percentage of Households withBank Account
Percentage Applied for Housing
Loan Previously

Services
36
100% Married

12%

19%

23%

25%

97%

95%

98%

100%

12%

5%

32%

11%

*Median household income is the median income brought in for the household by all family members. If the respondent does not work and is notbringing income, the household can still have income from a spouse, parents, adult children, etc.
† Loan amount desired is based on respondent’s own evaluation of amount needed for home purchase or construction and not a reflection offinancial analysis of repayment capacity

33

KENYA Key Findings$14.8 billion
Estimated size of market for women’s housing loans
Market profile

59% of households have a woman

Female-headed households save

31% more, on average, thaninvolved in financial decision-making

male-headed households

6% of female-headed households

The Median amount that Joint

applied for a housing loan in thedecision-making households expect

previous 5 years

to borrow for home purchase is$24,844

Current access to housing finance loans obtained by women• Savings and Credit Cooperative Societies (SACCOs) 57%• Banks 29%• Government 7%• Informal chamas 7%
Opportunity

33% of female-headed

25% of female-headedhouseholds plan to take ahouseholds are planningloan for housing finance inhome improvements

the next 5 years

34

Houses are preferred by

91% of women who

plan to purchase housing5. Kenya
Ownership Status

Kenya has a relatively untapped housing financemarket with significant unmet demand for housing

n Womenfinance among women. There is high demand amongn Menn Joint

20%

40%

women in Kenya for housing finance products. Thirty-three
percent of female-headed households and 66 percent of

Rent

joint-decision-making households intend to purchasehousing in the next five years and 25 percent plan to makeOwnhome improvements. The demand for housing financeamong women in Kenya is estimated at $14.8 billion. The

0%

overwhelming majority of women want to purchase a

60%

80%

100%

house (91 percent), rather than an apartment. Yet, despitehigh demand, women remain constrained by low income

While gender is not a significant driver of home

and inability to meet bank requirements. The majority

ownership, age, family size, education, income,of women use Savings and Credit Cooperative Societies

length of occupancy, and city are. A regression analysis

for housing finance needs, primarily because they cannot

explored the impact of these various factors, confirming

meet the down payment or provide documents required

findings from the demand survey. The analysis found one

by banks. Traditional roles also contribute to women notexception to the positive impact of “length of occupancy”

having equal access to housing finance.

on home ownership, living in Nairobi. Perhaps because ofhigher property prices and limited supply of houses, living
in Nairobi decreases the probability of ownership by nine

Market Profile

percent.

Home ownership is very low for women and men

Ownership by Age and Income

in Kenya. According to “Housing: Unavailable andUnaffordable,” World Bank Kenya Economic Update 2017,

n Men

Kenya has an estimated accumulated housing deficit of two
million units, and the deficit is estimated to grow 200,000

n Women80%

units each year. In IFC’s demand survey, only 16 percent own

60%

their home.

40%
20%

Inside the findings: This is consistent with findings0%

from the Kenya Integrated Household Budget Survey

18-24

25-34

35-44

45-54

>54

(KIHBS) 2015-2016, which found that 22 percent of urbanhouseholds own their home. The demand survey’s slightly

40%

lower number is due to its focus on low- and middle-

30%

income households, which are less likely than high-20%

income households to own their home..

10%
0%
		
Less thanHouseholds headed by a woman are only slightly more		likely to be renting than those headed by men or joint
decision-making households. Among households that
own, 92 percent have a registered title deed.

35

150 USD

150–300
USD

301–600
USD

More than
600 USD

KENYA CONTINUED

However, the legal owner of the home is mostPurchasing and building a home are the most common

commonly the man.

ways to acquire a home. Among women, inheritance is amore common means of home acquisition than among bothmale-headed and joint households. A quarter of female-

Overall Legal Ownershipn Womenn Menn Joint

headed households inherited.
13%

Acquisition of Housing Among
Homeowners

18%
69%

n Womenn Menn Joint

Ownership by head of household gender
BoughtFemale-headed households:
58% female sole owner(8% joint owner)

Built

Male-headed households:
81% man sole legal owner
Joint decision-making
households: 74% male sole
legal owner

Inherited

0%

25%

50%

0%

75%

36

10%

20%

30%

40%

50%

60%

Median Income, Expenses and Savings by Gender of Household HeadMonthly income
Monthly Expenses
Monthly Savings
Total Savings

Women

Men

Joint

348
248
38
994

497
248
29
398

696
398
50
1,988

In terms of means to purchase, women have higher

Inside the findings: These findings were consistentsavings than households headed by men, despitewith statistics from the World Bank Global Financial

their lower income and similar expenses. Joint heads

Indicators (Findex) Database, which show that only sevenof household, which have a higher monthly income, also

percent of women and 10 percent of men currently have

have the highest monthly and cumulative, despite higher

outstanding loans.

monthly expenses.

Institutions to Which Men and Women
AppliedUse of bank loans for housing is very low. Of the demand
survey respondents, only seven percent of men and four
percent of women had previously applied for housing loans.

n Women

Savings and Credit Cooperative Societies and banks werethe most common institutions to which both men and

n Men

Savings/credit
cooperative

women applied.

Bank

Most loans were sought to build a house (37 percent)or purchase land on which to build (37 percent). The

Government
programs

purpose of the remainder of loan applications was tofund the purchase of a house (16 percent) or repairs/

0%

improvements (11 percent).
A greater percentage of women applicants had loans
approved than men. Of those who applied for a loan, 87
percent of women and 60 percent of men were approved.

37

20%

40%

60%

80%

KENYA CONTINUED

Current Access to Housing
Finance and Supply

Commercial banks currently service a small portion of

Savings and Credit Cooperative Societies are theto a population of 48 million. The ratio of outstanding

major providers of home construction loans in Kenya.

mortgages to GDP in 2015 was only three percent. This

According to “Housing: Unavailable and Unaffordable,”

low level of mortgage lending, while comparable to other

World Bank Kenya Economic Update 2017, SACCOs now

Sub-Saharan African countries (e.g., Uganda and Tanzania),

account for more than 90 percent of home loans (overputs Kenya behind emerging markets and more developed

100,000). SACCOs largely rely on member deposits forcountries (e.g., South Africa at more than 30 percent).

capital and lack long-term sources of capital, which limits
their ability to expand.

Inside the findings: The advantages that SACCOs offer

the population in providing mortgages. There are fewer
than 25,000 mortgages outstanding in Kenya, compared

Financial Institutions reported that their processes
are gender neutral. Interviews with three banks,
two Savings and Credit Cooperative Societies, and one
microfinance bank (including the main lenders in housing

to loan applicants include: 1) they package home loans

finance) reported that their internal policies, regulations,as development loans at more affordable interest rates,and practices — including loan origination processes — areusually about 12 percent per annum; 2) they offer small

gender neutral.

formal mortgages through the Kenya Union of Savings
and Credit Co-operatives (Kuscco Housing Fund), and; 3)Commercial banks do not offer gender-specificthey fund unsecured construction loans.

products and services for the women’s segment. In
part, this is because organizations such as the microfinanceMortgages from commercial banks have decreased ininstitution Kenya Women Finance Trust (KWFT) are alreadynumber of accounts but increased in value. According

targeting this segment. They are weary of being perceived

to the Bank of Kenya’s “Bank Supervision Annual Reportas a “woman’s bank” and they see gender-specific products

2016,” from December 2015 to December 2016, the number

and services as outside their traditional realm of business.

of mortgage loan accounts decreased by 1.5 percent from24,458 to 24,085, while the average mortgage size increasedby nine percent from $80,676 (K Sh 8.3 million) to $88,452(K Sh 9.1 million) as property prices rose. During the same
period, the outstanding value of banks’ mortgage loan
assets increased by 8.1 percent from $1.976 billion (K Sh
203.3 billion) to $2.137 billion (K Sh 219.9 billion). (Currency
conversion rate applied: K Sh .0097 per $1.00)

However, financial institutions have a perception thatwomen clients are better payers. Although none of theFIs in this study keep disaggregated data on repayment
behavior, the generally accepted perception is that womenare more emotionally connected to their homes, and as
caretakers of their family, will go to great lengths to ensureloans are repaid.
Demand study respondents agree that women do

Inside the findings: The decrease in number of

not enjoy equal access to housing finance. More thanmortgage loan accounts is partly due to an interest

50 percent of women and approximately 75 percent ofrate cap imposed by the Central Bank. This reduced themen perceive a gender-specific difference in access toaverage interest rate from 18.7 percent in 2015 to 13.5

housing finance.

percent in 2016, and subsequently led to tightened credit
standards and fewer mortgage loan accounts.

38

Do Women Enjoy Equal Access to Housing
Finance? (RHS)

Barriersn Yesmoney. While both men and women reported a lack

The main barrier to housing finance is insufficientn Noof sufficient funds as a major reason for not wanting to

Womenpurchase a home, more 64 percent of women and 45
percent of men cited this reason.

Men
0%

50%

Inside the findings: Other significant, related

100%

challenges to accessing housing finance is inability to
repay, lack of employment opportunities, high interest

The satisfaction rate among men receiving loans

rates, and inability to meet bank requirements forwas 100 percent, and among women was 92 percent.

collateral or a guarantor.

Satisfaction was based largely on whether clients perceive
the terms and conditions of their loan as favorable. For
instance, when asked what aspect of their loan product

For women, another barrier is that big financial

they would change, clients most frequent mentioned lower

decisions, including the purchase of the house, are seeninterest rates.

as the man’s responsibility. For instance, a quarter of thedemand survey respondents responded that they agreed
with this view.
Women are generally disadvantaged in terms ofincome and property ownership. Financial institutions
reported that women are more likely to be self-employedor employed in the informal sector, thus having a lower
income and lacking proof of a stable income. Land titles arealso a challenge. Even though women can inherit property,
the property is held in the name of the man, following
tradition. Thus, women do not have the titles needed tooffer banks collateral.
Those that had been approved for loans by a financial
institution are largely long-term clients. Not
surprisingly, household income positively correlated withthe decision to apply for and receive approval for a loan.
Over time, though, this has resulted in a greater likelihoodof loan approval for existing rather than new customers(which could disadvantage female-headed households).

39

KENYA CONTINUEDADDRESSING BARRIERSMedian Length of Time as a Financial
Institution’s Client

The Kenya Women Finance Trust (KWFT) is an Approved

microfinance bank explicitly established to serven Not approved

women as clients. Approximately 90 percent of its clients
More than
5 years

are women. KWFT is currently working with Habitat for
Humanity to provide housing microfinance loans in rural

2-5 years

areas.

1-2 years
Savings and Credit Cooperative Societies such as the

1 yearor less

United Women SACCO and the Federation of Women
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Entrepreneur Associations (FEWA) SACCO cater
specifically to women clients. However, the majority

ADDITIONAL INSIGHTS INTOBARRIERS TO HOUSING FINANCE
ACCESS
To better understand the role of culture and norms on theemployment status of men and women, a logistic regression
model was fitted to explore how personal characteristics of
respondents impact their likelihood of working. Variables
identified included gender, marital status, and having abank account. (See Notes for a detailed explanation of thisanalysis and a chart of results.)
Results of the analysis indicate that being a woman
decreases the probability of being employed by 12
percentage points, all else equal. Traditional gendernorms dictate that women in Kenya are significantly more
responsible for taking care of the home, limiting whether
and where they find employment, and thus how muchof these institutions’ loans are for personal or businesspurposes. Only a small portion of their loan portfolios is
housing finance.
The Kenya Mortgage Refinance Company (KMRC)
was launched in May 2019, part of the government’s
affordable housing pillar of President Uhura Kenyatta’s“Big Four” strategies. The sole function of KMRC is toprovide long-term lower-cost loans to primary mortgage
lenders, helping housing finance to become more widely
available and more affordable. Another government priority
is the promise of 500,000 new affordable housing units
by 2022, doubling current output. The affordable housing
initiative, KMRC, combined with an increase in affordable
housing may combine to energize housing finance lending
to Kenya’s women.

Women, Business and the Law
Women, Business and the Law is a World Bank Group

money they earn.

project collecting unique data on the laws andAmong women who would like to be able to purchaseregulations that restrict women’s economic

housing, 64 percent of those not planning to purchase

opportunities. The following findings for Kenya arecited not having enough money as the biggest barrier

relevant to women’s access to housing finance.

to home acquisition. Women are more likely than men
to not work at all or work from home, resulting in lower
income.

Post-Harvest
Processing andStorage40

Market Opportunities

ACCESSING INSTITUTIONS
1. Are wives required to obey theirhusbands?

No

Female-headed households are approximately 13

2. Can a woman legally get a job in the same Yes
way as a man?

percentage points more likely to be planning a home

3. Can a woman sign a contract in the same
way as a man?

Yes

results stem from a data mining logistic regression analysis

4. Can a woman open a bank account in thesame way as a man?

Yes

type of employment, etc.

5. Can a woman choose where to live in thesame way as a man?

Yes

Similarly, the demand survey indicated that female-

6. Can a woman be “head of household” inthe same way as a man?

N/A

purchase or renovation in the next five years. Theseof observable characteristics such as gender, age, education,

headed households are more likely to be planning
improvements to their homes than those headed bymen, but slightly less likely to be planning to purchasehouses. Joint decision-making households renting and

USING PROPERTYBoth must
agree

owning have the highest proportion planning to purchase

2. Does the law provide for valuation of
nonmonetary contributions?

Yes

their home.

3. Do men and women have equal
ownership rights to immovable property?

Yes

4. Do sons and daughters have equal
inheritance rights?

Yes

5. Do female and male surviving spouses
have equal inheritance rights?

No

1. Who legally administers marital property?

or construct, and the least likely to make improvements to

Inside the findings: Among households currently living
rented housing, 66 percent of households with a maledecision-maker and 64 percent with a female decisionmaker reported planning to purchase a home in the next
five years. Among homeowners, 38 percent of maleheaded households and 33 percent of female-headed

GOING TO COURT
1. Does a woman’s testimony carry thesame evidentiary weight in court as aman’s?

households plan to move or construct a new home in theYes

next five years.

BUILDING CREDIT
1. Do retailers provide information to credit
agencies?

No

2. Do utility companies provide information
to credit agencies?

Yes

3. Is discrimination based on genderprohibited in access to credit?

No

4. Is discrimination based on marital statusprohibited in access to credit?

No

For purchase or improvements, about 33 percent
of women expect to seek funding from formal
financial institutions, compared to about 25
percent of men. The median expected loan amountis same for female- and male-headed households
at $9,921; the highest is for joint decision-making
households at $24,844.

41

For housing purchases, formal loans are the second-

Cluster Analysis reveals opportunities for tailoring

most common type of funding (after personal cash/

products and services to specific segments who plan tosavings). Loans are substantially more common amongpurchase housing in the next five years. This analysis of

joint decision-making couples than female- or male-headed

demand survey responses (see Notes for more information

households, and of these, married couples are the moston Cluster Analysis methodology) identified homogenous

likely to use a formal loan (53 percent).

groups of potential customers that have similar needs andattributes, and thus represent sub-segments for tailored

Funding Used for Housing Acquisitionn Womenn Menn Joint

products and services. Segment 1 is largely double-income
households. Segment 2 is single-income married couples.
Segment 3 is single-income female-headed households.

Personal/savings

The total size of the urban market for women’s housing

Formalloan

billion. The total market size represents the total estimatedInformalloancurrently have plans to purchase a home. It was calculatedloans in Kenya is estimated at approximately $14.8
amount of loans needed from urban women in Kenya whofrom values including number of urban households,

Acquirematerials

percentage of female head, percentage demand, andmedian expected loan amount, relying on figures fromOther

the demand survey and census data. More detail on this

Govt.
Subsidycalculation appears in the Notes section at the end of thisreport.

Friends orFamily0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Expected Loan Amounts Needed for
New Home Purchase
Cost ofpurchasing

Loan amountneededExpectedMonthly
payment

Woman$22,360$9,921$100

Man$19,876

9,921$

$134

Joint

$29,814$24,844$100

42

Cluster Analysis of Potential Housing Finance Market

Variables Used in Clustering:
Marital status
Household Head

Segment 1

Segment 2

Segment 3

MarriedMarriedSingle

Both

Man

Woman

Employment (of respondent)
55% Self-employed/
57% Does not work
35% Permanent
		entrepreneur
18% Self-employed/		employee
45% Permanent		
entrepreneur
29% Self-employed/		
employee
14% Permanent		
entrepreneur
				
employee
21% Part-time			
6% Part-time 		
employee				
employee
9% Does not work			
5% Non-contract
6% Non-contract				employee		 employee

Median Household Income(from all contributing family
members)*

$645

$495

$396

$26,750$14,860$28,730$5,268$1,972$3,809• Saving/putting money away myself

59%

64%

74%

• Belong to cooperative/savings group

34%

18%

38%

• Purchasing land

18%

10%

9%

Loan Amount Desired†

Savings for Housing

Other Key Variables:
Steps taking to buy/build home:

7%

Structure wanted
House

8%

Apartment

93%

18%
92%

82%

Anticipated monthly repayment amount

$219

$162

$283

Monthly disposable income

$347

$230

$301

*Median household income is the median income brought in for the household by all family members. If the respondent does not work and is notbringing income, the household can still have income from a spouse, parents, adult children, etc.
† Loan amount desired is based on respondent’s own evaluation of amount needed for home purchase or construction and not a reflection offinancial analysis of repayment capacity

43

44

6. The Business Case for Women’s
Housing Finance Programs
Current Barriers to Women’s
Housing Finance

2. W
 OMEN DISPROPORTIONATELYLACK HOME OWNERSHIP AND
TITLING DOCUMENTATION.

1. W
 OMEN TYPICALLY LACKSUFFICIENT INCOME AND
DOCUMENTATION OF THEIRINCOME.

Women are less able to provide home ownership
documentation required by banks as collateral for
housing finance.

Women are less able to meet the level of income andformal income documentation required by financial
institutions to assess credit worthiness.

recognizes women’s equal rights, and protects women’s

Women are less likely to be employed than men.

households own housing, and 43 percent of households

Regression results show that women are significantly lesswith joint decision-makers own housing. In Kenya, where

likely to be employed than men even when controlling for

women’s right to inheritance are protected but with manyother observable characteristics, and that being married

exceptions and rights to marital assets are based on a

reduces the likelihood of women’s employment, but has

woman’s contributions to acquiring the asset, 67 percent

no effect for men. Compared to male respondents, femaleof owned housing have a man as the sole legal owner. In

respondents were 35 percent less likely to be working inIndia, which has no provision protecting women’s rights

Colombia, 38 percent less likely in India, and 12 percent lessto inheritance or rights to marital property, 81 percent oflikely in Kenya.

owned housing have a man as the sole legal owner.

Female-headed households have a lower average

Women are less likely to have registered property

monthly income than for male-headed households, andtitles (and in some cases separate land titles), requiredin married households, men are typically consideredby banks as collateral for housing finance. The legal

the main contributor to the household income. Female-framework in each of the three countries prohibits

headed households make up 26 percent of households indiscrimination based on sex, endorses explicit recognition

Colombia, 9 percent in India, and 25 percent in Kenya. Theseof women’s rights and guarantees equal access to land,

are largely single, divorced or widowed women, many of

housing and property. However, when it comes towhom have children.

inheritance, only Colombia fully recognizes women’s equal

Women are less likely to own property. Colombia fully
equal rights to marital property and marital assets.
However, while half of Colombia’s male-headed households
own their housing, only 37 percent of female-headed

rights. In India, there is no provision regarding women’s
Employed women are more likely to be self-employedrights to inheritance and in Kenya, this right is granted but

or in the informal sector — sectors that do notwith many exceptions. There is a similar situation in terms

generate income statements or tax documentsof women’s rights to marital property. In Colombia, womenrequired by financial institutions. The lack of necessary

have equal rights to marital assets, while in Kenya they

income documentation hinders the ability of FIs to assesshave the right to assets based on their contribution to theapplicants’ repayment capacity.

acquisition of said assets and in India, they have no rights tomarital assets. Therefore, in practice, patriarchal norms that45

THE BUSINESS CASE CONTINUED

constrain women’s right of inheritance and property titling,
continue to prevail in India and Kenya. Because of this,women are less likely to own land or housing, which means

Formal Housing Loans in Colombia, India,
and Kenyan Used formal loan to purchase housingn Applied for formal loan in past 5 years
n Planning to use formal loans in next 5 years

they are less likely to be able to offer registered titles as
collateral. This obstacle is especially complex in India, whereland titles are a state subject, with different states having
different regulatory requirements.

Colombia
Men
Women

3. W
 OMEN HAVE LESS EXPERIENCEWITH FORMAL LOANS

India
Men

Women are less likely to be familiar with the procedures
and requirements for applying for a formal loan and lesslikely to have developed a relationship with a financial
institution.

Women
Kenya
Men

While use of housing loans remains relatively low for

Women

both men and women, female-headed households are,when controlling for other variables, significantly less

0% 5%

10%

15%

20%

25%

30%

35%

likely to have used a formal loan for the purchase of
housing. Only nine percent of men and eight percent of
women in Colombia; seven percent of men and four percent
of women in Kenya; and five percent of men and six percent
of women in India have previously applied for housing loans
in the last five years. Among those households that had
applied in India, joint decision-making households weremost likely to have been approved (83 percent) compared to
male-headed (66 percent) and female-headed (57 percent)households.

4. I NFORMAL CULTURAL BIAS
WORKS AGAINST WOMEN
Although financial institutions have gender-neutral
lending policies, traditional cultural norms can affecthow banks view female loan applicants and how
potential female loan applicants view banks.
Gender norms play a role in whether women willapproach a bank for housing finance. In Kenya, forexample, survey respondents and financial institutions
mentioned that purchase of a home is considered the man’s
responsibility, and a single woman is expected to move into
her husband’s home when she marries. Thus, women are
disincentivized to seek housing finance for themselves.
Financial institutions often do not take housing financeapplicants who are unmarried women as seriously as
they do applicants who are men or married women.
Financial institutions reported that they scrutinize theloan application of single women more than single men or
married women.

46Despite Barriers, This is a Market
Worth Addressing

There is a significant gap between women’s rising

Private-sector solutions and public-sector policies cantransform women’s interest in housing finance into
economic growth.

the scope or breadth to meet the growing demand among

There is a strong demand: many women are planning

Estimated Market Size by Gender ofHousehold Headdemand for housing finance and current FI supply. The
housing finance programs that currently exist do not have
women for housing finance.

to purchase a home or make home improvements inthe next five years. Among women involved as the soledecision-maker or joint decision-maker with their husband,
49 percent in Colombia, 20 percent in India, and 65 percent

Female Headed
Households

Joint Decision-Making
Households

in Kenya are planning to purchase a home or make home

Colombia$5.7 billion$17.3 billion

improvements in the next five years. In Colombia and Kenya,

India$2.8 billion$29.5 billion

Kenya$2.4 billion$12.4 billion

women overwhelmingly prefer to purchase houses, while inIndia, women are largely planning to purchase apartments.
Many women plan to finance their purchases andimprovements through a formal loan. Planned source

Financial institutions consider women to be betterof funds differs by country, but formal loans are mostsavers as well as better payers than men. Financial

common in Colombia and Kenya, while women in India

institutions in India and Kenya reported that they prefer toprefer informal loans. In Colombia, almost half of thehave a woman on housing loans because their emotional

women who plan to make a home purchase plan to use aties to their home ensure repayment to prevent foreclosure;formal loan, a quarter government subsidy, and anotherhowever, no data was provided by the financial institutions

23 percent personal savings. In Kenya, personal savings areto support these statements. From the demand survey,

most common (53 percent), closely followed by formal loans

households in which a woman is involved in financial(40 percent). In contrast, in India, informal loans are mostdecision-making save more than households in which men

common with 47 percent of women expecting to use an

make financial decisions. Despite having lower levels of

informal loan, followed by personal savings (18 percent) andincome, these households find a way to save more eachformal loans (15 percent).

month to purchase a home.

47

THE BUSINESS CASE CONTINUED

Reasons for FIs to Pursue the
Women’s Housing FinanceMarketReasons for Policy
Intervention

Brand Enhancement

Quality of Life• Equal access to property and• Social impact

titling• Differentiation• Equal socioeconomic conditions• New client base

• Improved access to quality• Stronger ties to current

dwellings and public services

clients• Improved safety and security

Profitability

National Economy• Large, untapped market• Increased FI profitability• Better payers, low NPLs

• More stable communities• Stable market —• Growth in housing, homegreater financial

improvement and construction

discipline

sectors

Policy interventions could have a positive effectwomen. Specifically, female-headed households living

on women’s housing finance. Low income, informal

in informal settlements are more vulnerable to forced

employment, unequal property rights, and other structural

displacement and poverty. Displacement and migration

factors can affect women’s access to housing and housingfrom rural to urban areas are the main drivers of informal

finance and be moderated by policy intervention. For

employment for women in urban Colombia, especially forexample, despite available studies on the situation of

women with low education and low socioeconomic status

women suggesting that women have equal rights to(Source: C. Flórez, 2003, Migration and the urban informal

property ownership and inheritance, titles are still largely insector in Colombia, Universidad de los Andes: Bogota). Suchthe name of the men in the family rather than the women,

women live in precarious dwellings that lack basic needs

and inheritance goes first through sons rather thanand adequate public services (Source: UN Habitat, 2005,

daughters. Policy interventions could close this disconnect

Law, Land Tenure and Gender Review: Colombia). In India

between rights and reality.

and Kenya, women’s rights are often compromised due tothe patriarchal nature of the society and their safety and

Policy interventions that support women’s housing

security are compromised due to lack of adequate housing.

finance and home ownership also could affect the
disparate socioeconomic conditions between men and48

Lessons Learned: The results ofcurrent women-focused banking
initiatives

housing — VIS) and vivienda de interés prioritario (Priority

Housing finance programs and policies tailored to
women in this study’s target countries, as well as
significant FI experience lending to women-led Smalland Medium Enterprises worldwide, have produced
positive results.

India’s “Housing for All,” a Credit Link Subsidy program,

Social Housing — VIP) programs involve subsidized interest
rates for a lower income segment of the population, which
includes female-headed households (more detail below).
provides a subsidy if a woman is on the registered title.
Institutions active in women-led Small and Medium
Enterprise lending specifically reported businessgrowth and low non-performing loans.

A few institutions and government policies in

Dominican Republic’s Banco BHD León (BHDL). Within its

Colombia, Kenya, and India already have housing

first year, BHDL’s Mujer Mujer program produced an internalfinance programs tailored to women. In India, SEWA

rate of return of over 35 percent, along with a return on

Grih Rin Ltd. provides housing loans specifically for low-

assets of 20 percent for individuals, 14 percent for small

income women (more detail below). In Kenya, Kenya

enterprises, and 12 percent for medium-sized businesses. In

Women Finance Trust is working with Habitat for Humanity

addition, between December 2015 and July 2016, the bank’s

to provide housing microfinance loans for women in rural

credit portfolio grew 26 percent in commercial loans, 19

areas. In Colombia, vivienda de interés social (affordable

percent in car loans, and eight percent in consumer loans.

Colombia’s Leasing Habitacional Program

Begun in 2017 by Fondo Nacional del Ahorro to help

• The money used for the payment of rent is

low-income Colombians who have difficulty saving

credited to the purchase of housing

for a down payment, this program allows people withincome between $262 to $1,572 to access a new home

• Competitive interest rates• No mortgage expenses at the conclusion of theby paying a monthly rental fee for a term of five toleasing term

30 years. After this term, the person may exercise• Term up to 30 years, facilitating acquisition of

his or her purchase option to become the ownerhigher-value housingof the property. This “social leasing” finances up to
100 percent of the value of the property for a newhome, and up to 95 percent for existing construction.

While not explicitly targeted to women, this program

The program finances both Priority Social Housing

disproportionately benefits women, as more female-(VIP) with maximum value of $18,340, and affordable

headed households are in the low-income category.

housing (VIS) with a maximum value of $35,370. For

Such programs could be specifically tailored to

Colombians, additional advantages of the program

improve women’s and female-headed households’

include:access to housing finance.

49

THE BUSINESS CASE CONTINUED

Sewa Grih Rin Limited (SGRL)• Marketing through existing networks and clients.

As part of the Self-Employed Women’s Association(SEWA), Sewa Grih Rin Ltd. provides affordable

SGRL markets through the SEWA Network andhousing finance to the under-served, low-income

its nearly 1.4 million members. Additionally,

households in urban and peri-urban locations of

there are more than 20 sister organizations

India. Their focus is on serving women, especiallyassociated with SEWA involved in housing,those who run micro and small businesses and thosebanking, insurance, research, ecotourism, and

who are paid workers in the informal sector, aother activities. This wide network of women

segment that dominates the Indian urban workforce,throughout India is a ready market for SGRL

but remains unserved by formal lenders due to lack of

products. Banks and other financial institutions

formal title and income verification.

could adapt this approach by marketing toexisting transactional clients.

As of May 2018, Sewa Grih Rin Ltd. had no NPLs and a• Looking beyond formal titles for collateral.

portfolio of approximately $950,000. The average loan
provided by SGRL to clients is approximately $ 3,500.

Because most women will not be able to access

SGRL reduces the high costs of customer acquisition

formal titles, SGRL supports women to obtainand collections by its replicable marketing outreachparalegal titles, including property papers.

methods:

During a home visit, the loan officer assesses not
only family income, but also history of savings,• Door-to-door marketing in target areasborrowing history, equity contribution, and(particularly where there is a strong SEWA

household assets. If a household has made big

presence). SGRL sends loan officers out forpurchases on installment (refrigerator, television,

approximately 1.5 hours a day to meet withetc.), for example, and paid them off, this canpotential customers at their home. Loan officers

increase SGRL’s confidence in the household’s

meet with potential customers, explain thewillingness and ability to repay. Other financial

types of products offered, the process to getting

institutions can carry out similar analyses of aa loan and the requirements for each product.

household’s overall borrowing capacities andThis personal approach combined with someassist with obtaining collateral documents.

elements of financial literacy has contributed
to reduce women’s cultural barriers to lending
and grow SGRL’s customer base. During thevisit, men and women in the household gain
an understanding of the borrowing process
and the importance of a woman as borrower,
information that helps overcome the prevalentcultural bias towards men as borrowers. This
personalized approach can be easily replicatedby other institutions, particularly MFIs.

50

Lebanon’s BLC Bank. In four years of its Women
Empowerment program, BLC increased the number

A survey conducted with a sample of 154 IFC

of its women SME lenders by 82 percent, increased its

banking clients found that their women-owned

women’s outstanding loan portfolio by 121 percent, andor women-led Small and Medium Enterprisegrew women’s total deposits by 65 percent, outpacing its(WSME) loan portfolio contains significantly

portfolio as a whole. The compound annual growth rate

lower non-performing loans than total SME

and return on assets for products launched under theloan portfolios.

Women Empowerment initiative consistently outperformed• Just 3.6 percent of WSME loans were non-those sold to men. The rate of non-performing loans for
women at BLC was 2.45 percent, substantially lower

performing versus 4.5 percent of the total

than the bank’s overall rate.

SME portfolio• The average loan size to WSMEs was

Palestine’s Bank of Palestine. BOP created a mini-MBA$27,708 compared with an average loan ofprogram for women business owners to increase their$43,136 in the total SME portfolio

business financial literacy. The program resulted in• WSME outstanding loans accounted forincreased access to finance and use of financial products

roughly 10 percent of the total volume of

by women business owners. BOP itself developed a special

outstanding SME loans

collateral-free loan to ease restrictions for women who
have limited access to land ownership beyond lending.
Jordan’s Bank Al Etihad. The results of a Bank Al Etihad
study were clear: there were no non-performing loans

Moving forward: Addressing
the needs of women in housing
financefor female SME customers. Because of the overall positive
performance of its women-targeted SME finance business,
Bank Al Etihad will continue to serve women, which it
considers the next emerging market.

Research household incomes and average loan size.
Before creating new products and services to attract

Turkey’s Garanti Bank. Garanti Bank has integrated

the women’s segment of housing finance, banks can

its Women Entrepreneurs business into its entire SME

obtain some valuable baseline information by researching

Banking business line, but has tracked its specific growth.

current borrowers’ income and loan levels. In Colombia,

Currently, WE customers represent a significant portion offor example, 42 percent of households are dual income

its customer base: 21 percent of its profit, 10 percent ofwith an average loan size of $26,000, and 26 percent areits deposits, 11 percent of its customer loans, and 12.5

female-headed with an average loan size of $17,179. In India,

percent of its customers.

38 percent are dual-income with an average loan size of$9,462, and 9 percent are female-headed with an averageloan size of $7,279. In Kenya, 34 percent of households are
dual-income with an average loan size of $24,844, and 25
percent of households are female-headed with an averageloan size of $9,921.

51

THE BUSINESS CASE CONTINUED

Learn the goals women hope to accomplish with

Develop products, terms, and services that meethousing finance. Despite barriers to housing finance,

women’s needs. In India, for example, a housing financethis study revealed significant interest among women

product was designed with a credit-linked subsidy.

to accomplish three categories of housing goals: home

Borrowers receive a concessional rate on the housing loan

improvement, incremental instruction, and purchase.

when the woman’s name is included in the registeredtitle deed. In addition, free financial literacy programs tied

• Home Improvement. An estimated 25 percent of

to housing finance benefit both women consumers andwomen homeowners in Kenya, 18 percent in India,

the financial institutions. Through the programs, womenand 23 percent in Colombia plan to make homebecome more competent and confident borrowers, andimprovement changes in the next five years. An

institutions form a valuable brand-loyalty relationship withestimated five percent of women homeowners inthem.

Kenya, five percent in India and 17 percent in Colombia
plan to use a loan for this purpose. The most common

Simplify procedures to improve the women’s housing

home improvement changes mentioned were

finance environment. Once financial institutions identify

building and improving a kitchen and building andproducts and services to offer, reconsidering loan processing

improving a bathroom. The average loan size for home

procedures can make offerings more accessible. In India,

improvements is $411 in Kenya, $1,340 in India, andfor example, one of the biggest reasons households seek

$2,382 in Colombia.

informal loans is due to the requirements that formal
financial institutions have for obtaining a loan. By reducing• Incremental Construction. Building a home in

the processing time and steps for registering and/or

incremental stages is common practice in theperfecting mortgages, banks can make housing loans moredeveloping world, and constitutes between 50 to 90

accessible to more consumers.

percent of residential construction (Source: Habitatfor Humanity. Step by Step: Supporting Incremental

Train staff on gender awareness. Gender sensitization

Building through Housing Microfinance. Shelter Reporttraining within banks and financial institutions ensures2014). An estimated 64 percent of women in Kenya, 66

that all staff understand the specific barriers women facepercent in India, and 32 percent in Colombia cannot

and their specific financing needs, as well as the financial

afford to purchase even the least expensive housing ininstitution’s specific value proposition for women. Staff

urban areas. For these households, smaller, consecutive

become able to engage women in conversations aboutloans might be more appropriate.

products and services in a way that encourages brandloyalty and new business.

• Purchase. The average loan size to purchase a homein Kenya is $29,290, in India $20,978, and in Colombia

Know how to market to women consumers.

$17,022. In Kenya, an estimated 36 percent of women

Relationships are key to marketing to women, a fact that

can afford the minimum housing price, while six

determines which tactics will be most successful.

percent can afford the median house price; in India,
an estimated 34 percent of women can afford the• Women prefer to obtain advice on housing finance fromminimum, six percent the median; and in Colombia,

friends and family. According to a survey carried out

an estimate 68 percent of women can afford theby Nielsen in emerging markets, across 22 forms ofminimum, 35 percent the median.

advertising measured, “recommendations from people
you know” is the most trusted advertising source forwomen (Source: The Nielsen Company, Women of52

Tomorrow: A Study of Women Around the World,• Women appreciate a sense that their bank understands themJune 2011). Word of mouth is thus a significant driverand their needs, as reflected in their interactions with bankof purchasing decisions, particularly for women.

staff and clear processes for loan application and approval.

IFC’s study also found that friends and family are

A positive customer experience is something women

the preferred sources for financial advice on housing

greatly value. To ensure a continuing positive customer

finance. As a result, the most effective tool to reachexperience, banks can conduct a Voice of the Customer

women is to promote brand and product image

survey to capture feedback from customers about theirthrough personal recommendations between friends,

experience, needs, and requirements. Insights fromfamily, and formal and informal networks.

the survey can be used to develop staff incentives fordifferent levels of interaction with consumers, and• Women also want to receive advice from banks themselves.

pinpoint processes or policies that need improvement.

Fifty-three percent of women in Colombia, 25 percent
in India, and 27 percent in Kenya report that banks are

Ongoing monitoring and analysis of women’s housing

their preferred source of financial advice for buying/finance programs can ensure continuing profitability.

building a house. This suggests the effectiveness of

Gender-disaggregated data provides banks with themarketing techniques such as:

information they need to know about how well they areserving women, and to make strategic decisions that–– Easily accessible in-bank marketing materials

improve performance over time. Gender-specific data can(pamphlets, posters, etc.) to showcase housing

include statistics on applications and rejected applications,finance offerings for women.

the number and value of loans granted by gender andperformance indicators including non-perrforming loans–– Staff engagement of women clients at every

and profit margins.

interaction, using the opportunity to reinforce
marketing and consumer education messaging andstrengthen the bank-client relationship.
–– Protocols and incentives that encourage staff
engagement.

53

54

Colombia

Notes1) PREDICTORS OF HOUSING DEMAND (i.e. Existing or Future)

Variables
Model 1:Model 2:For Colombia, Kenya, and India this study: 1) examined potential factors driving women’s demand for housing andPotential demand for
Used a formal loan tohousing loans; 2) performed a Clusterhousing
Analysis
subgroups
into
thereveal
next 5homogenous
years
purchasehome of potential customers with similarneeds and attributes; and 3) calculated the market size for women housing loans.
GenderFemale factors driving women’s demand-.5573* for housing and housing-.02601) •Potential
loans and housing demand predictors. For
each
Age of the countries, the first logistic regression-.00314 (Model 1) seeks to identify.0029the predictors of planning to buy a house or
make improvements to a current dwelling in the next five years. The second logistic regression (Model 2) seeks to identify
Civil Status
the determinant factors related to existing demand (i.e., having used a loan in the purchase of the current home). Comparing• Married.0096.0825note, raw coefficients in logistic regressions arethetwo models provides additional insight
into the housing market. Please• Separated/Divorced-.2206 ** used to determine probability.
-.0262scaledin terms of log odds; marginal coefficients
Marginal coefficients enable interpretationof•resultsin terms of probability. Charts .2274
of each country’s analysis appear
below.
Civil Union.3145**
Education level2) Cluster Analysis (segmentation) Methodology. In this segmentation exercise to identify market sub-groups, the two• Primary school-.0405-.1764step cluster analysis used an algorithm that first performs sequential clustering on the data to compress dense regions and• Somesecondary-.0878 method to the sub-clusters.
-.0943Quality of cluster analysis is determined by: (1)form
sub-clusters,
and then applied the cluster• Secondary
completed.0135Criterion,a statistical index-.1703
minimizing
Schwarz’s
Bayesian Information
used to measure the goodness of fit of a model; andSome university-.3121(2)• maximizing
variation between clusters
to ensure the model chosen-.0991
shows significant differences between the segments
identified.
Clusteranalysis results appear-.1785
in each country’s section.
• University
complete-.0576

Log income.4266***.0264*
3) Calculation of Market Size. The following equation was used to determine each country’s total market size. The results
represent
the total estimated amount of.8357**
loans needed from urban women
Employment-.0311who currently have plans to purchase a home.
Details and results of each country’s calculations appear below.

total market = urban households * % female head * % demand * exp (amount)

55

NOTES CONTINUED

Gender of Household Head
• Woman-.5785*-.2347**• Both-.1248-.0339• Joint/Extended.1406**.2532**• Singles-.0459Number of Observations

298

Family Structure

342*** P <0.01, ** P<0.05, *p<0.10

563) COLOMBIA’S MARKET SIZE: THE
TOTAL SIZE OF THE URBAN
MARKET FOR WOMEN IN
COLOMBIA IS ESTIMATED AT
APPROXIMATELY $23 BILLION.

of housing in the next 5 years in the demand survey, and exp

The following equation was used where total market is

calculating the average household size in urban areas fromthe calculated total market size, urban households is thethe 2009 census data and assuming the same ratio in 2017.

estimated number of urban households in Colombia inThus, the number of urban households was calculated as2017, % female head is the proportion of households that

follows:(amount) is the median expected loan amount reported by
women in the survey. The total market size thus represents
the total estimated amount of loans needed from urban
women in Colombia who currently have plans to purchasea home. The number of urban households was estimated byhave a woman in decision-making, i.e. either have a female

2017 urban population

household head or have joint decision-making in the

average urban household size.

demand survey, % demand is the proportion of women who

2017 Urban population data are sourced from the World

reported that they would use a loan to pay for the purchase

Bank World Development Indicators.

[total market = u rban households * % female head * % demand * exp (amount)]
Female Headed Households:
5,694,548,303 = 9,841,460 * 25.5% * 13.7% * 16,563
Joint Decision-Making Households:
17,330,155,570 = 9,841,460 * 41.5% * 24.7% * 17,179

57

NOTES CONTINUED

India
1) P
 REDICTORS OF HOUSING DEMAND (i.e. Existing or Future)
Variables

Model 1:Model 2:

Potential demand for
housing in the next 5 years

Used a formal loan topurchase home

0.079

-0.003*-.001.002**• Single-0.0390.049• Separated/Divorced-0.064-• Widow

0.130

0.049

Education.004

0.011*

Log income.067**

0.157***

Employment.061*

0.004*• Woman-0.070**-0.038*• Both-0.045**-0.011• Joint/Extended

0.033*

0.015

Mumbai-0.286***-0.039*Number of Observations

1,238

1,234

Gender• Female
Age
Civil Status

Gender of Household HeadFamily Structure*** P <0.01, ** P<0.05, *p<0.10

583) INDIA’S MARKET SIZE: THE
TOTAL SIZE OF THE URBAN
MARKET FOR WOMEN IN INDIA IS
ESTIMATED AT APPROXIMATELY$32.3 BILLION.

five years in the demand survey, and exp (amount) is themedian expected loan amount reported by women in thesurvey. The number of urban households was estimated by
calculating the average household size in urban areas from2011 census data and assuming the same ratio in 2017, as
follows:

The following equation was used where total market is2017 urban population

the calculated total market size, urban households is theaverage urban household size.

estimated number of urban households in India in 2017,

The number of urban households was estimated by% female head is the proportion of households that havecalculating the average household size in urban areas froma women in decision-making, i.e. either have a female

2011 census data and assuming the same ratio in 2017.

household head or have joint decision-making in the

The total market size thus represents the total estimateddemand survey, % demand is the proportion of women withamount of loans needed from urban women in India who

decision-making authority who reported that they would

currently have plans to purchase a home.

use a loan to pay for the purchase of housing in the next

[total market = u rban households * % female head * % demand * exp (amount)]
Female Headed Households:
2,783,009,881 = 96,330,082 * 9.45% * 4.2% * 7,279
Joint Decision-Making Households:
29,515,803,593 = 96,330,082 * 38.13% * 6.9% * 11,646

59

NOTES CONTINUED

Kenya1) PREDICTORS OF DEMAND
Variables

DemandPotential demand for
housing in the next 5 years

Female household head

0.132*

Age-0.009**Married

0.195***

Education

0.008*

Log income

0.715**

Log income-0.036**

Employment.061*

Type of employment• Self-employed

0.071• Non-contract employee-0.135• Part-time employee

0.168• Permanent employee

0.071

Account

0.262***

Own-0.124*

Made improvements

0.158**Nairobi-0.035

Number of Observations

402*** P <0.01, ** P<0.05, *p<0.10

A dummy variable equal to 1 if the respondent was locatedin Nairobi is also included to control for potential structuraldifferences between Nairobi and Nakuru.

60

3) K
 ENYA’S MARKET SIZE: THE TOTALSIZE OF THE URBAN MARKET FOR
WOMEN IN KENYA IS ESTIMATED AT
APPROXIMATELY $14.8 BILLION.

use a formal loan to pay for the purchase of housing in the

The following equation was used where total market isthe 2009 census data and assuming the same ratio in 2017.

the calculated total market size, urban households is theThus, the number of urban households was calculated as

estimated number of urban households in Kenya in 2017,

follows:

next five years in the demand survey, and exp(amount) is themedian expected loan amount reported by women in thesurvey. The number of urban households was estimated by
calculating the average household size in urban areas from% female head is the proportion of households that have2017 urban population

a woman in decision-making, i.e. either have a female

average urban household size.

household head or have joint decision-making in the

The total market size thus represents the total estimateddemand survey, % demand is the proportion of women withamount of loans needed from urban women in Kenya who

decision-making authority who reported that they would

currently have plans to purchase a home.

[total market = u rban households * % female head * % demand * exp (amount)]
Female Headed Households:
2,393,226,531.80 = 3,592,153 * 25.37% * 26.47% * 9,920.98
Joint Decision-Making Households:
12,433,311,659.36 = 3,592,153 * 34.08% * 40.88% * 24,844

61

PHOTO CREDITS
Cover: Daniel M Ernst/Shutterstock
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Page 8: Philou1000/Shutterstock
Page 21: Dominic Chavez/World Bank
Page 30: Charlotte Kesl/World BankPge 36: Jorge Sanchez Photos/Shutterstock
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Inside Back Cover: Luis Echeverri Urrea/Shutterstock62

Contact Information
IFC
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Washington, DC 20433 USA
BMurti@ifc.org
www.IFC.org/gender@WBG_Gender
ifc.org

November 2019