Are we formal yet? The evolving role of informal lending mechanisms to support
entrepreneurship and poverty alleviation in central Kenya
Abstract: Entrepreneurship has substantially contributed to the economic growth of
Kenya. However, multitudes of the country’s poor have yet to experience the benefits of
this growth due to limited access to capital. Microfinance institutions exist in central
Kenya but serve the needs of only a handful of entrepreneurs that want to engage in small
businesses. Consequently, many Kenyans turn to various informal lending mechanisms to
pursue their entrepreneurial dreams and bolster their livelihoods. This paper examines
how adults in and around the town of Nyeri, Kenya access capital from a wide variety of
formal and informal sources. Several modes of borrowing are identified and reasons for
choosing lenders are analysed. Collectively, this data suggests the gradual expansion and
formalization of informal lending mechanisms. This paper provides insights to
entrepreneurs, lending institutions and development agencies to help develop effective
business and partnership strategies that can empower enterprising individuals in
impoverished communities.
Introduction
The Eastern African region accounts for more than half of microfinance borrowers in
Sub-Saharan Africa. The largest markets are Ethiopia and Kenya, which together serve
45% of borrowers and 43% of depositors (MIX Market and Consultative Group to Assist
the Poor, 2009). Kenya has received the greatest exposure to microfinance as compared
to its Sub-Saharan counterparts dating back as early as the 1980s (Kithinji, 2002).
Despite this, many of the poor have failed to benefit from the significant influx of funds
and programs resulting from the emergence of several microfinance institutions (MFIs).
As a result, those who find themselves excluded from these opportunities turn to, or
continue to use, more traditional informal methods of credit access. Success of informal
methods of credit access is reliant upon the strength of social capital of individuals within
the country’s impoverished communities. These informal and semi-formal lending
mechanisms are a primary source of funding for micro-enterprises. Micro-enterprises are
a common means of creating or supplementing income within Kenyan households
(Daniels and Mead, 1998; Mead and Liedholm, 1998). Understanding the means through
which micro-enterprises can access capital is essential to the successful launch of any
such enterprise. By understanding the changing role of formal channels such as banks,
semi-formal channels like MFIs, and informal channels that include group lending
systems, entrepreneurs can choose the funding options that best suit their circumstances.
The Pennsylvania State University’s Humanitarian Engineering and Social
Entrepreneurship (HESE) program develops socio-economically and environmentally
appropriate technologies for developing communities. The technologies serve to address
specific needs within these communities with the objective of establishing ventures that
will be sustainable beyond student and faculty involvement. Recognizing the role that
micro-enterprise plays in the financial empowerment of impoverished members, HESE
tailors its projects to be comprehensive solutions by creating potential business ventures
out of the technologies it develops. Creating business opportunities while addressing
community needs provides two-fold improvement in the lives of the people. This form of
engagement in social enterprise reflects a larger trend with American universities trying
to address developmental challenges through rigorous academic and extra-curricular
programs.
Ventures championed by the HESE program span several countries. Projects range from
telemedicine and renewable energy systems to affordable agricultural post-harvest
technologies and informal education systems for self-employed women. Students are
challenged to create context-appropriate and socially and financially feasible solutions to
developmental challenges. Students then work with diverse partners in the developing
country to commercialize the venture with an open source philosophy. For example, over
the past three years, low-cost greenhouses have been designed and field-tested in Kenya
and are ready for large-scale dissemination. At a BOM (Bill of Materials) cost of 250
USD, the greenhouses are one-tenth of the price of larger commercial greenhouses
currently in the market. They can directly improve smallholder farmers’ livelihoods and
foster food security. In addition, the farmers can expect a return on their investment in
just two crop cycles. However, a crucial question that needs to be addressed is “how will
the farmers, and other potential customers, get access to the 250 USD they need to
initiate their greenhouse-based enterprise?” Knowledge and understanding of formal and
informal borrowing and lending mechanisms is essential to develop appropriate business
strategies and launch ventures that are economically sustainable and enhance
participants’ livelihoods.
This pilot study attempts to uncover the various sources of access to financial capital in
Nyeri, Kenya that will make entrepreneurial endeavours in this region more successful.
Specifically, the goal of this work is to answer three questions: 1) How can Kenyan
entrepreneurs access credit? 2) How much can they borrow? and, 3) What is the cost of
borrowing? Within the scope of these questions, we explore formal, semi-formal and
informal credit institutions, considering the role of gender, occupation, and social capital
in credit access and cost. While this study is exploratory, it corroborates much of the
literature as well as provides additional insights into why borrowers choose a specific
institution, how much they can borrow, the influence of occupation on borrowing
behaviour, and the relationship between interest rates and social capital. This knowledge
can help entrepreneurs determine potential informal and semi-formal financial partners to
make their products more affordable and accessible to customers. Entrepreneurs and nonprofits can advise the target community members on their financial strategy, specifically
how to save money and access capital from various organizations, leading to a larger
customer base and stronger customer relationships. The findings of this study suggest that
mutually-reinforcing aggregation of social and economic capital is healthy for facilitating
trust and access to capital in a fledgling economy.
Review of Formal Financial Institutions
The banking and formal financial sectors in Kenya are among the most developed in SubSaharan Africa. Currently, there are 45 financial institutions, 43 of which are commercial
banks, and 2 that are mortgage finance companies (MIX Market, 2010). Combined with
the Kenya Post Office Savings Bank, these institutions constitute the formal sector and
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service about 22% of Kenya’s adult population (MIX Market, 2010). A 2009 GALLUP
survey revealed that 70% of adult Kenyans reported not having a bank account
(GALLUP, 2010). One reason for this is that after considering minimum deposit
requirements, recurring fees and various charges, the cost of maintaining a bank account
is very high for many citizens, especially the poorest members of society (FSD Kenya,
2008). Additional non-financial costs are also associated with banking: complicated
banking processes can alienate those that struggle to understand the forms and
requirements; and, socio-economic status can create barriers when dealing with the staff
(FSD Kenya, 2008). As a result, some individuals view the expense of obtaining credit
through formal mechanisms to outweigh the utility (Atieno, 2001).
The nature of formal financial systems presents additional hindrances that prevent the
issuance of credit. Screening and monitoring procedures are underdeveloped, rendering
the bank susceptible to default. Credit issuers are limited in their ability to provide credit
because their knowledge about a potential customer is also limited. Moreover, should
credit be issued, contract enforcement mechanisms are lacking (Atieno, 2001). A thriving
financial market is considered to be crucial to a country’s economic development
(Bohnstedt, 2008). Kenya’s economic success is contingent upon addressing the financial
needs of its adult population who are not receiving service from the formal sector. In
attempts to bridge the gap left by the formal sector, a wave of microfinance and other
semi-formal credit entities has swept through Kenya with the intent of bolstering
economic activity through the creation of credit access and subsequently contributing to
the alleviation of poverty.
Review of MFIs and Semi-Formal Institutions
Microfinance supports the economic endeavours of the poor through the provision of
financial services to low-income households and Micro and Small Enterprises (MSEs)
(Omino, 2005). MSEs account for 17 to 27% of adult employment in Kenya (Daniels and
Mead, 1998). Financial services include cash loans, money transfer, direct deposit,
insurance, and savings services for the poor (Barrett and Osterloh, 2007). Nongovernmental Organizations (NGOs) and Intergovernmental Organizations (IGOs) have
taken on the challenge of poverty alleviation in Sub-Saharan Africa, seeking to bridge the
gap that formal financial mechanisms have created, through the funding of Microfinance
Institutions (MFIs). The World Bank and the United Nations are among the IGOs that
have committed to increasing access to capital as a means of poverty reduction through
the outpouring of money for various projects in Kenya. The World Bank is working with
K-Rep Bank – a provider of microfinance loans – on the Kenya Microfinance for Water
Services Project (The World Bank, 2011) and the United Nations has participated in the
Microstart Kenya partnership with the Equity Building Society in Kenya (Enterprising
Solutions Global Consulting, LLC, 2003). Through the United Nation’s involvement in
the Microstart program, almost 30,000 clients were serviced between its inception in
1997 and 2003 (Enterprising Solutions Global Consulting, LLC, 2004). The Kenya
Microfinance for Water Services Project is on-going, thus the results of the project are
still pending. These however, are just two examples of how IGOs and NGOs use
microfinance to meet poverty and developmental needs.
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With significant international support, the Kenyan government has also developed
policies and programs aimed at improving credit accessibility for the country’s
entrepreneurs. Beginning in the 1950s, the colonial government established the Joint
Loan Board Credit Scheme that provided loans to small, indigenous entrepreneurs
(Kenya Ministry of Trade, 2007). Since then, several acts of Parliament have been
passed pertaining to microfinance institutions: The Kenya Post Office Savings Bank
(KPOSB) Act; The Banking Act; The Companies Act; The Cooperative Societies Act;
The Non-governmental Coordination Act; The Building Societies Act; The Societies Act
and The Trustee Act (Omino, 2005). All these acts served to increase regulation,
coordination and integration of the emerging groups of diverse microfinance institutions.
The Microfinance Act of 2006 was created to provide a legal, regulatory and supervisory
framework for the MFI industry in Kenya (Central Bank of Kenya, 2008). Realizing the
failures of some of these institutions, the Microfinance Act was revised in 2008,
loosening certain requirements in hopes of improving performance (MIX Market, 2010).
As the microfinance industry grows and becomes a more integral part of Kenya’s
economy, increased acknowledgement by the government through the passage of
regulatory laws has provided a sense of validity and security that many have only
associated with banking institutions of the formal sector.
While the Kenyan government has grappled with creating effective oversight frameworks
for the MFI industry, many MFIs have come into existence and failed or have been
established fraudulently and have taken advantage of its clients (Mulama, 2005).
However, among the MFIs that have seen success, major microfinance businesses like
Faulu Kenya and Kenya Women Finance Trust (KWFT) have become prominent
institutions in the community, providing both microfinance and social welfare services
(Omino, 2005), and are currently the only two MFIs licensed to take deposits (MIX
Market, 2010). In 2010, Faulu Kenya serviced 85,226 borrowers, with a loan portfolio
estimated at KES 33,175,452. In the same year, KWFT serviced 413,040 borrowers,
with a loan portfolio of approximately KES 152,136,208 (MIX Market, 2010).
In addition to the outpouring of funding to MFIs, Savings and Credit Cooperative
Organizations (SACCOs) have also received attention as an alternative to the formal
credit sector. Formalized under the Cooperative Societies Act, SACCOs require monthly
payments for shares that members can borrow against (Dondo, 1999). Unlike banks that
also require savings, members are able to borrow two or three times the value of their
savings, provided that other members agree to serve as their guarantor (Dondo, 1999). A
2010 report highlighted that non-deposit-taking MFIs fell under the jurisdiction of
SACCO Societies Regulatory Authority (SASRA) or remained unregulated outside of
NGO licensing requirements (MIX Market, 2010). Problems with restrictive regulation or
no regulation at all factor into MFIs’ inability to effectively serve in-need communities.
MFIs, SACCOs and recently popular mobile phone service providers have bridged the
credit access gap to some degree, meeting an additional 18% of Kenya’s adult
population’s financial needs (MIX Market, 2010). MFIs are often the beneficiaries of
donor intervention (Bohnstedt, 2008). Yet, despite the millions of dollars of funding to
MFIs and other semi-formal credit institutions, Kenya struggles with its goal of
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eradicating poverty (African Economic Outlook, 2011). Rural communities have been
significantly neglected by both banks and MFIs, and are among those with the greatest
need of financial services (Brown et al., 2011). Informal credit groups have provided an
alternative to the formal and semi-formal lending mechanisms, with organizations like
KWFT and National Council of Churches in Kenya (NCCK) establishing a strong
presence in Kenyan towns.
Review of informal institutions
Financial systems are considered to be informal when they operate “outside the
regulation of a central monetary authority,” whereas semi-formal systems display both
formal and informal features. Informal credit systems develop as a result of existing
demand (Atieno, 2001). Consequently, more than 50% of Kenyan adults belong to at
least one informal financial group, with 35% of the population citing informal groups as
their only access to financial services (FSD Kenya, 2009). It is estimated that
approximately KES 1.2 billion (USD 19 million) is being mobilized monthly in such
informal channels, demonstrating the value of informal lending mechanisms to the
Kenyan economy (FSD Kenya, 2008).
Since government-subsidized credit programs have failed to reach targeted groups,
alternative means of administering rural credit have emerged (Atieno, 2001). Rotating
Savings and Credit Associations (ROSCAs), popularly known as merry-go-rounds, have
been in use throughout the world, long before microfinance came around. The names
used among various cultures may be different, but the process remains largely the same;
through voluntary participation, a group agrees to make regular payments to a fund which
is given, in whole or in part to contributing members in rotation (Ardener, 1964).
Rotation order can be determined by, but is not limited to, seniority, age, or ballot (FSD
Kenya, 2009). Payment amounts vary, as do the rules established for self-governance,
but it is this kind of flexibility people appreciate about ROSCAs (FSD Kenya, 2009).
Accumulating Savings and Credit Associations (ASCAs) are similar to ROSCAs in that
they are formed by a group of community members pooling their money together and
taking turns receiving what has been collected. Unlike ROSCAs however, members of
the group are required to pay interest on the money they borrow. This increases the total
amount that the organization can lend out or the number of people that can receive a loan
at one time. It is also common for members of ASCAs to divide a portion of the profits
made from the interest charged among themselves at year’s end (FSD Kenya, 2009).
Participants of ROSCAs and ASCAs have expressed several reasons why they choose to
participate in these borrowing and lending groups, with the leading reason cited as
exclusion from the formal sector (FSD Kenya, 2008). The ability to gain access to money
quickly in the event of an emergency, access to social networks they can tap into for
business expertise, and lower interest rates are other factors that that make participation
in such groups attractive (FSD Kenya, 2009a).
The success of these mechanisms is in part attributed to their flexibility (FSD Kenya,
2009; Bohnstedt, 2008). The relationships that exist between the participants of these
organizations provide more complete information about the lender and borrower, an
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attribute that the formal sector lacks. This creates trust between the actors and leads to
enhanced social capital, a valuable intangible asset that facilitates the acquisition of
monetary assets. Financial transactions that occur between friends, neighbours and
relatives are quite common in the informal sector. Granovetter (1983) describes “strong
ties”, friends and relatives, as being more easily available to the borrower and more
willing to aid those in their own social circle. Ease of access is often the prompt for
borrowing from friends, neighbours or relatives: however, group lending tends to provide
access to greater amounts of capital than borrowing from a single individual.
Although informal credit institutions have seen success in meeting the needs of MSE
operators and entrepreneurial individuals, their limited resources restrict the extent to
which they can provide credit (Atieno, 2001). On one hand, as enterprises grow, or more
entrepreneurs seek credit, these small-scale groups are unable to satisfy needs adequately.
On the other hand, even if the entrepreneurs qualify for credit in the formal sector, the
sizes of the loans they require are often too small for formal credit institutions (Atieno,
2001). Despite their limited resources, informal credit associations and organizations are
omnipresent and play a crucial role in the entrepreneur’s relentless pursuit of capital. In
this paper, we suggest that the pervasiveness and increased reliability of informal credit
mechanisms, and governmental regulatory authorities officially validating and
recognizing the importance of these informal mechanisms, is resulting in the blurring of
boundaries between informal and formal systems. More importantly however, is the fact
that informal systems are beginning to transition into legitimacy and reliability, making
them a competitive option for credit access and entrepreneurial partnerships.
The Role of Trust and Social Capital in access to Economic Capital
Social capital has been studied extensively in relation to how communities work. Putnam,
Leonardi and Nanetti (1993) identify social capital as “features of social organization,
such as trust, norms and networks that can improve the efficiency of society by
facilitating coordinated actions.” In the case of Kenya, and other developing nations, the
coordinated action is the creation of grassroots-based credit groups that provide financial
services that previously were beyond the reach of its members. Godfrey (2008) provides
a variation of social capital, defining it as the resources available to an individual as a
consequence of the strength of relationships that a person has with others. He also defines
it less formally as “who you know” that can help you get “what you need.” This provides
a slightly different interpretation as it implies that it is the strength of the relationship that
brings about beneficial outcomes.
Understanding the role of social capital in the context of lending and borrowing is
important because it is the key element that formal financial institutions lack. This lack of
social capital results in imperfect information about the borrowers and lenders. Inaccurate
assessment of the risk of default can be reduced by strong norms and networks of
reciprocal engagement (Putnam, Leonardi and Nanetti, 1993). Group lending reduces
informational disparity, increasing a borrowers’ willingness to repay as a result of
informal sanctions (Barrett and Osterloh, 2007). Corroborating this idea, Putnam,
Leonardi and Nanetti (1993) state that voluntary cooperation (i.e. willingly repaying a
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loan) is easier in circles where social capital via norms of reciprocity and networks of
civic engagement are present.
A network of reciprocal engagement, also known as a social network, is defined as all of
the people to whom one person is connected through social ties, creating relationships
that serve the needs of those involved (Mehta, 2011). Social networks facilitate the
creation of trust (Putnam, Leonardi, and Nanetti, 1993), a critical element of social
capital. Putnam, Leonardi and Nanetti give the example, “I trust you, because I trust her
and she assures me that she trusts you.” This process addresses the issue of imperfect
information, because trust is a matter of knowledge (Cook, 2001). Individuals that do not
trust each other can only cooperate with one another under rules and regulations
(Fukuyama, 1995). Since informal mechanisms are often unregulated, it is implied that
trust allows group members to successfully collaborate with one another. As a result,
trust, norms, and networks are the foundation for informal lending organizations like
ROSCAs and ASCAs. Group lending through ROSCAs and ASCAs provides
information and monitoring advantages that individual contracts between a bank and a
lender do not provide (Atieno, 2001).
Stiglitz (1990) points out that lending groups have the benefit of peer selection, allowing
them to form groups with those they deem acceptable or of minimal risk. Furthermore,
fear of exclusion from socioeconomic systems creates powerful sanctions (Putnam,
Leonardi and Nenetti, 1993) that encourage individuals to adhere to social expectations,
ensuring enforcement of repayment (Atieno, 2001). This further reduces risk. In lending
groups like ROSCAs, fear of exclusion is the reason that most participants do not drop
out or default on repayment after having received their turn with the loan. Entrepreneurs
striving to launch ventures in developing communities can benefit from identifying and
leveraging the interdependence of social and economic capital found within ROSCAs and
ASCAs.
Role of Gender and Occupation on Access to Capital
Entrepreneurs must also be aware of gender disparities in credit accessibility. Kenya’s
emergent economy has not been exempt from the economic disparities between men and
women. Formal lending and savings institutions have shown an affinity for men and
formal businesses despite the fact that women comprise a large portion of the growing
economy (Srivastava, 2009). To bypass the hurdles associated with borrowing from
formal credit institutions, female entrepreneurs often turn to informal means of acquiring
capital. Organizations like Kenya Women’s Finance Trust (KWFT) have attempted to tap
into this trend through the creation of microfinance institutions that focus on women
(IBRD, 2009). However, coverage is still relatively low (FSD Kenya, 2008). With so
many women seeking financial opportunities, there is significant potential for monetary
gain by these organizations, and women have proven to be profitable clients. Women
own almost 50% of enterprises in Africa and comprise more than 60% of MFI clients
with higher rates of repayment than men (Srivastava, 2009). Studies have revealed that
more than 80% of Kenyan ROSCAs and ASCAs consist of 6 – 10 members, and that
75% of them are women (Dondo, 1999). Although women’s income is less than men’s, it
7
tends to be more consistent, making their income more suitable for ROSCA participation
(FSD Kenya, 2009a).
The credit demands of men are often beyond the capabilities of informal groups due to
the larger amount of credit that men need and because they tend to need the amounts at
the same time due to seasonal responsibilities (FSD Kenya, 2008, 2009a). As a result,
men tend to borrow from the formal sector. This is less of an issue for women because
they tend to require smaller loans at different times. Due to this disparity between men
and women, the World Bank emphasizes the need to structure project rules and
procedures to promote the participation of those who are often excluded based on social
or gender-based traits (World Bank, 2011). Like gender, occupation (or lack thereof) can
also create barriers to credit access because it influences inclusion in financial services
(FSD Kenya, 2008). Government employment reduces the likelihood of exclusion from
banks, and influences the use of banks and SACCOs. Employment in the private sector
follows as the second most influential factor in the use of banks and SACCOs. Access to
credit through formal banking services is most frequent for employees with steady wages
(Bohnstedt, 2008). Research also shows that members of ROSCAs have a greater
likelihood of being employed in the informal sector (FSD Kenya, 2009a). The
International Labour Office has identified young adults as being particularly vulnerable
to unemployment, and as a result they lack skills, assets and access to credit facilities,
which subsequently makes it difficult to engage in self-employment through small and
micro-enterprises in Kenya (International Labour Office, 2007).
Research Methodology
One hundred and four respondents were interviewed in and around Nyeri Town, Gatitu,
and Karatina in central Kenya. Interviews were conducted between the hours of 8 am and
6 pm, on the street or at the interviewee’s place of work. The selection of interviewees
was done at random—the authors travelled along main and side streets and interviewed
nearby workers and pedestrians. Two interviews were also conducted at a respondent’s
home. Interviewers were accompanied by local interpreters and guides to facilitate
communication. Interpreters were fluent in Kiswahili, Kikuyu and English. Survey
questions are included as an appendix to this article. In total, 89 respondents reported
being borrowers or lenders, 82 respondents reported being borrowers, 63 respondents
reported being lenders, and 56 reported being borrowers and lenders.
It may be noted that the sample size is small compared to the overall population of areas
surveyed. The 2010 population of Nyeri County, in the Central District of Kenya,
according to the Kenya National Bureau of Statistics, is 654,818 persons (Kenya National
Bureau of Statistics, 2010). The small sample size for this exploratory study yields
statistically insignificant results but the trends will lead to a more substantial research
endeavour with specific research questions. Since interviews were conducted between the
hours of 8 am and 6 pm, and most often at the respondent’s job, the results are biased
towards employed adults. Several participants were current and aspiring entrepreneurs.
This is important to note because our team intends to continue implementing projects in
these regions, tailored toward potential entrepreneurs.
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Interviewees were read the recruitment script and verbal informed consent was sought.
No personal identifying information was recorded. All survey questions were open-ended
and categorization of the lending and borrowing institutions was inferred from the
participant’s responses. For example, none of the respondents explicitly used the terms
ROSCAs or ASCAs, but used more culturally common descriptions such as “merry-gorounds” to explain these informal organizations. We used the description of the actual
mechanism of borrowing or lending to classify each entity.
Results and Discussion
Means of access to capital
Participants had access to credit from a wide variety of formal and informal lending
institutions. The most popular lending institutions, in descending order, were ASCAs,
banks, family, friends and neighbours (FNRs), ROSCAs, SACCOs and business
associates (BAs). Over twenty-six per cent of borrowers reported having obtained credit
from a bank. However, access to capital from institutions was not equal among males and
females. As shown in figure 1, ROSCAs and ASCAs were dominated by female
borrowers while many more men than women borrowed from banks and SACCOs. A
smaller gender disparity was observed among those who borrowed from FNRs and BAs.
Despite the small sample size, these results appear to agree with the literature and
empirical trends observed by the authors: Informal lending groups are dominated by
female borrowers, while formal lending institutions tend to work more with male
borrowers.
Figure 1: Number of respondents borrowing from each lending institution arranged by gender.
The relationship between occupation and access to credit is not well documented. To test
whether occupation influenced access to formal and informal credit institutions, the
respondents’ reported occupations were classified and juxtaposed with the institutions
from which they borrowed. Jobs were classified according to the US Bureau of Labor
Statistics job classifications. In some cases, inferences were made regarding a
respondent’s occupation based on their open-ended job description. Several categories,
including management, production, sales and services were further subcategorized to
indicate whether the respondent owned his or her business. Street hawkers were also
9
given their own category. As shown in figure 2, several occupations, including
management, sales, services and transportation showed a gender disparity: men
dominated management and transportation while females dominated sales.
Figure 2: Categorized occupations of respondents.
Several patterns were observed when linking occupation to the borrowing institutions
(Figure 3). To reduce complexity, business associates were grouped with FNRs. The
colour of each grid is based on the fraction of borrowers in the given occupation who
borrow from the corresponding institution—the number of each grid corresponds to the
absolute number of respondents. Sixty-four shades of grey were used. The darkest
shade, black, indicates that 100% of respondents in a given job category reported
borrowing from a given institution. The lightest shade, white, indicated that 0% of
respondents in a given job category reported borrowing from a given institution. As
shown in figure 3, banks, ASCAs and FNRs were popular borrowing institutions
regardless of the respondent’s occupation. However, SACCOs appeared related to the
management, sales and transportation sectors and ROSCAs appeared related to farming,
production, sales and transportation sectors. Beyond this, no clear trends were readily
observed. Since the sample size used was small, these findings are preliminary at best. A
larger sample size is likely needed to more firmly assess the relationship between
occupation and borrowing institution.
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Figure 3: Occupation versus reported borrowing institution. The colour of each square on
the grid indicates the percentage of borrowers in each job category borrowing from each
respective institution. The numbers in each square is the number of respondents, in each
job category, borrowing from each respective institution.
In addition to reporting the lending organization, respondents were also queried about
their reasons for choosing that entity. Responses were normalized and categorized into
fifteen categories and are shown in figure 4. Here, business associates were once again
grouped with FNR for simplicity. The results indicated that borrowers chose to borrow
from ROSCAs, ASCAs and FNRs predominantly because they preferred the borrowing
process, trusted the lender or were unable or unwilling to borrow from a bank.
Additionally, borrowers preferred the lower interest rate and the repayment time
associated with ASCAs and SACCOs. SACCOs were also preferred for their simple
borrowing process. Bank borrowers preferred the security, convenience, legitimacy and
reliability of banks. There was a dichotomy between banks and all other financial
institutions with banks perceived as the safest and most able institution to provide credit.
For account holders, banks were also perceived as the most convenient means to obtain
credit. However, for those without a bank account or collateral, borrowing from FNRs,
SACCOs, ASCAs or ROSCAs was perceived as being an easier process. SACCOs were
preferred highly for their process and, together with ROSCAs, considered a good
alternative to banks.
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Figure 4: Reported reason for choosing to borrowing from a respondent’s respective
lending institution.
Amount of Accessed capital
Males had access to larger amounts of capital than females. Figure 5 plots the number of
responses versus the amount generally borrowed from any category, formal or informal.
Since the typically borrowed amount varied by several orders of magnitude, the results
are shown on a semi-logarithmic plot. The responses were grouped in 5,000 KES
increments, starting with (0, 5,000) KES. All multiple responses from a single
respondent, not exceeding three responses, were included. The total numbers of non-zero
data points were 55 for females and 41 for males. All responses were plotted by gender
and normalized. As shown in figure 5, female and male general borrowing habits were
similar up to 100,000 KES. However, for amounts larger than 100,000 KES, the number
of male borrowers was larger than their female counterparts.
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Figure 5: Male versus female general borrowing. The integration width is 5000 KES.
Several modes of borrowing, defined as the borrowing amounts which occurred most
frequently in the data set, were evident in figure 5. To further refine these modes, the data
was plotted in figure 6 in 500 KES increments, starting with (0,500) KES. As shown in
figure 6, between one and ten thousand KES, modes of borrowing for females include
2,000, 5,000, 10,000, 20,000 and 50,000 KES. Male modes of borrowing include 2,000,
20,000, 30,000 and 50,000 KES. We speculate that these values may be perceived to be
thresholds, or typical amounts, for borrowing.
Figure 6: Male versus female general borrowing. The integration width is 500 KES.
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The maximum amount ever borrowed from any person or institution, as reported by
respondents, is plotted in figure 7. As in figure 5, the responses were grouped in
5,000 KES increments and normalized. The results for maximum borrowing reinforce the
same pattern observed in figure 5—males were more likely to borrow larger sums than
females. We concluded that this pattern is closely associated with males’ ability to
borrow from formal institutions at a disproportionate rate, compared to females.
Figure 7: Male versus female maximum borrowing. The integration width is 5,000 KES
This conclusion was further reinforced by analysing the reported amount borrowed from
each institution. A box plot of the reported amount generally borrowed, for each
institution, is shown in figure 8. The median bank borrower was able to borrow almost an
order of magnitude more than from any other formal, semi-formal or informal institution.
Also, borrowers were able to obtain larger loans from ASCAs than, the more formal,
SACCOs. The results also indicated that most borrowers could obtain loans below 10,000
KES from FNRs, BAs, ROSCAs and SACCOs. To obtain loans in excess of
approximately 30,000 KES, borrowers appeared to turn to banks. ASCAs fill the gap
between 10,000 to 30,000 KES. Thus in order to borrow amount on the order of 250 USD
(approximately 22,000 KES as of December 2011), ASCAs may provide the best
alternative to a bank.
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Figure 8: Box plot of the reported amount generally borrowed from each institution.
Cost of borrowing
While respondents who obtained loans from banks could borrow more, the data indicated
that these loans were also the most expensive. The least expensive loans were those
obtained from informal credit sources. These results are shown in the combined boxcolumn plot shown in figure 9. The bars are associated with the left axis, the mean
interest rate, while the box plot is associated with the right axis, the reported interest rate.
Comparing figures 8 and 9 strengthens the conclusion that ASCAs may be an
entrepreneur’s best and cheapest option for obtaining credit on the order 22,000 KES, at
the low interest rate of approximately 10%.
15
Figure 9: A modified box plot (right axis) of the reported interest rate for loans obtained
from each institution along with a bar chart of the mean interest rates from each
institution (left axis). The 25th and 75th percentiles are indicated on the box plot by the
diamond line ends. The results are summarized below the x-axis.
Our results indicate that the cost of borrowing was closely associated with trust. This
relationship is shown graphically in figure 10. While formal institutions were associated
with the highest interest rates, ROSCAs were associated with the lowest. As noted in the
introduction, group lending and reciprocal social contracts facilitate the spread of trust
between members and increase social capital within the group. We argue that this
cumulative effect, from which ROSCAs benefit, increased the degree of trust between
members. This trust was key in facilitating zero interest-rate loans between members.
16
Figure 10: The cost of borrowing is inversely related to trust.
To further investigate the relationship between trust and the cost of borrowing, we asked
respondents about their lending habits: whom they lent money to, and at what cost. The
results are shown in figure 11. The interest rate charged to an institution, among informal
institutions, increased inversely with the social capital. The primary reason respondents
reported trusting the institution to which they lent was that they knew the borrower. Other
reported reasons were, in descending order, proven history or reliability, a perceived
obligation, collateral and perceived ability to pay back. Interviewees often explained that
they would lend to a friend or family member because the borrower needed their help or
had a “problem.” It seemed that a perceived obligation coupled with trust could trump the
borrower’s lack of collateral and perceived ability to pay back.
17
Figure 11: A modified box plot (right axis) of the reported interest rate for loans lent by
the respondent to each institution along with a bar chart of the mean interest rates charged
to each institution (left axis). The 25th and 75th percentiles are indicated on the box plot
by the diamond line ends. The results are summarized below the x-axis.
The data suggests that “knowing” a person or institution implies a certain level of social
closeness or connectedness which in-turn implies a certain level of trust. These “levels”
of trust varied amongst the borrowers and allude to “thresholds” of trust that influence
their social capital and access to financial capital. The data showed that these difficult-todefine levels of closeness and trust were the most important factors in determining whom
a person chose to lend to. A few respondents went as far as describing that knowing a
person was the minimal requirement, and that they must in fact have a particularly close
relationship with specific individuals in order to lend to them. Trust, and hence the
willingness to lend, diminished with levels of closeness, otherwise referred to as social
distance. Though social distance is undoubtedly enhanced by geographic proximity (i.e.
same household, neighbourhood or workplace), the ubiquity of mobile phones, coupled
with the advent of mobile phone-based money transfer services, such as M-Pesa, appear
to have reduced this constraint. Social networks grew and could be maintained through
cell phone use, and with a cellular phone and an M-Pesa account, lenders could transfer
up to tens of thousands of Kenyan shillings to a borrower for less than 100 KES
(Safaricom).
Concluding Remarks
18
Our exploratory work highlighted individual’s reliance on informal credit mechanisms in
gaining access to capital. A larger sample size is needed to more firmly ground the
observations and recommendations presented in this paper. ASCAs were found to be the
most popular source of credit among the sampled population. Women were found to
participate disproportionately in informal lending groups while a much higher percentage
of men borrowed larger amounts from banks. It was found that banks, ASCAs and FNRs
were popular borrowing institutions regardless of the respondent’s occupation. A
dichotomy between the reasons borrowers chose to borrow from banks and all other
financial institutions was discovered. For those with access, banks were perceived as
safe, legitimate and convenient. Informal lenders, on the other hand, were perceived as
having an easier lending process. ROSCAs and SACCOs were viewed as good
alternatives to banks. The vast majority of the respondents that borrowed from informal
channels did not mention, or even allude to, governmental regulation or legal
organization as an apprehension when choosing their credit source.
The insights gathered during the course of this study can guide the business strategy of
(social) entrepreneurs and development organizations working to implement ventures in
resource-constrained communities like Nyeri, Kenya. The most startling observation was
that absolutely none of the respondents reported borrowing money from an MFI.
Partnerships with MFIs can be beneficial only if they have an established track record of
working with rural marginalized individuals and helping them start micro-enterprises.
ROSCAs and ASCAs are the most prominent sources of funding for individuals in
impoverished rural communities. ASCAs offer the cheapest means to borrow amounts of
the order of 10,000 to 30,000 KES to start small enterprises. The hypothetical
entrepreneur presented in the introduction is more likely to borrow the 250 USD
(approximately 22,000 KES) necessary to finance her or his greenhouse from an ASCA.
This study suggests that when entering into communities that have a strong culture of
participation in informal lending groups, organizations should aim to create partnerships
with ROSCAs and ASCAs. Identifying community leaders and spheres of influence, like
faith-based or self-help groups, can provide inroads and build relationships with leaders
and participants of ROSCAs and ASCAs. ASCAs charge interest from their members.
This enables them to increase the total amount of money that they can lend without
relying on increased membership. Since this growth is sustainable, ASCAs can better
serve the entrepreneur’s needs as the enterprise grows and needs larger credit lines.
ROSCAs are much more popular and serve a large audience but have additional overhead
since they lack formal oversight and organization and can be chaotic.
Informal credit mechanisms, although ubiquitous and efficient, had been traditionally
restricted to small trusted networks. Modern technologies, best exemplified by the rapid
adoption of cell phones, are strengthening and expanding the reach of informal lending
mechanisms by facilitating the building of trust and social capital across social and
geographical boundaries. The inverse relationship between social capital and the cost of
borrowing is further bolstering the gradual evolution of informal mechanisms into
community-sanctioned formal financial institutions. It is essential to study this
phenomenon and its implications further to enable the development of mutually19
beneficial partnership models and organic engagement processes with semi-formal and
informal lending organizations. Such unusual business partnerships with amorphous but
effective organizations can ultimately help entrepreneurs gain access to capital and create
value for themselves and their communities.
20
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23
Figures
Figure 1: Number of respondents borrowing from each lending institution arranged by
gender.
Figure 2: Categorized occupations of respondents.
Figure 3: Occupation versus reported borrowing institution. The color of each square on
the grid indicates the percentage of borrowers in each job category borrowing from each
respective institution. The numbers in each square is the number of respondents, in each
job category, borrowing from each respective institution.
Figure 4: Reported reason for choosing to borrowing from a respondent’s respective
lending institution.
Figure 5: Male versus female general borrowing. The integration width is 5000 KES.
Figure 6: Male versus female general borrowing. The integration width is 500 KES.
Figure 7: Male versus female maximum borrowing. The integration width is 5000 KES
Figure 8: Box plot of the reported amount generally borrowed from each institution.
Figure 9: A modified box plot (right axis) of the reported interest rate for loans obtained
from each institution along with a bar chart of the mean interest rates from each
institution (left axis). The 25th and 75 percentiles are indicated on the box plot by the
diamond line ends. The results are summarized below the x-axis.
Figure 10: The cost of borrowing is inversely related to trust.
Figure 11: A modified box plot (right axis) of the reported interest rate for loans lent by
the respondent to each institution along with a bar chart of the mean interest rates charged
to each institution (left axis). The 25th and 75 percentiles are indicated on the box plot by
the diamond line ends. The results are summarized below the x-axis.
24