banking smes around the world: lending practices, business
TRANSCRIPT
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Banking SMEs around the world:
Lending practices, business models, drivers and obstacles
Thorsten Beck (World Bank)
Asli Demirgüç-Kunt (World Bank)
María Soledad Martínez Pería (World Bank)∗
FIRST DRAFT April 30, 20008
DO NOT QUOTE
Abstract Using newly gathered data from 91 banks in 45 countries, we document the state of financing to SMEs by large banks around the world: we characterize the extent, type, and pricing of this financing; we describe banks’ business models and lending practices; and we examine the factors driving and impeding bank lending to SMEs, including analyzing the role of government programs to promote SME financing and of banking regulations. Our results indicate that banks in both developed and developing countries are actively serving SMEs. However, we uncover surprisingly small differences when we compare SME versus large firm banking terms and lending practices. Instead, we find significant differences in lending terms and practices between banks operating in developed and developing countries. Also, while banks in developed countries see competition as a major obstacle, banks in developing countries point mainly to macroeconomic conditions. Banks’ reaction to government support programs is positive overall and prudential regulations do not seem to be perceived as a hurdle. Access to information through the existence of credit registries is especially valued by banks operating in developing countries.
∗ The views expressed in this paper are solely those of the authors and do not represent the opinions of The World Bank, its Executive Directors or the countries they represent. Subika Farazi and Noemi Soledad Lopez provided excellent research assistance.
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I Introduction The financing of small and medium-sized enterprise (SME) finance has been of great
interest both to policy-makers and researchers because of their significance in private sectors
around the world. Data collected by Ayyagari, Beck, and Demirgüç-Kunt (2007) for 76
developed and developing countries indicate that SMEs account for over 60% of manufacturing
employment. More importantly, a number of studies using firm-level survey data have shown
that SMEs not only perceive access to finance and the cost of credit to be greater obstacles than
large firms, but these factors constrain SMEs (i.e., affect their performance) more than large
firms. (Schiffer and Weder 2001, IADB 2004, Beck, Demirgüç-Kunt, and Maksimovic 2005, and
Beck, Demirgüç-Kunt, Laeven, and Maksimovic 2006). While this research has advanced our
understanding of the demand side of SME financing, outside the U.S. and a handful of other
countries where case studies have been done, little data exist on the supply side of bank
financing to SMEs across countries. This paper tries to fill this void in the literature.
Using newly gathered data for 91 banks from 45 countries, this paper documents the state
of financing to SMEs by large banks (the top 5 in each country) around the world. First, we
characterize the extent, type, and pricing of this financing and, wherever possible, we compare it
to bank financing of large firms. Second, we describe banks’ business models and lending
practices when it comes to serving SMEs. Finally, we examine the factors driving and impeding
bank lending to SMEs across countries. In particular, we analyze the association between bank
financing to SMEs and factors related to the contractual, information, legal, and macroeconomic
environments as well as to the extent of competition in the segment. Furthermore, we examine
the role of government programs and of banking regulations.
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Our main findings can be summarized as follows. First, banks both in developed and
developing countries see the SME segment as an attractive one, with good prospects, and offer
SMEs not only credit, but also other financial services. Hence, we confirm the findings from
previous case studies (World Bank, 2007a,b; De la Torre, Martinez Peria and Schmukler, 2008;
and Stephanou and Rodriguez, 2008) for a much larger number of countries. Second, though a
higher share of bank loans is directed to large firms relative to SMEs, there are surprisingly small
differences in the type and pricing of bank loans across firm size. Specifically, we primarily
observe differences between developed and developing countries rather than across firm size in
the share of lending for investment, in the ratio of secured loans, in fees and interest rates. Third,
banks across all countries have set up separate departments to serve SMEs and have
decentralized the sale of financial products to the branches, but the loan approval, risk
management, and loan recovery functions remain centralized. Fourth, though scoring models are
used by most banks in the sample, especially in small business lending, they are only one input
in the lending decision process. Fifth, we observe some differences in the lending criteria and
collateral used by banks operating in developing vis-à-vis developed countries. In particular,
banks in developing countries are more likely to make lending decisions based on a firm’s credit
history with the bank and the firm owner’s characteristics. Furthermore, while real estate is the
most important collateral for SME loans around the world, it is less so for banks in developing
countries where liquid assets are also commonly used as collateral. Sixth, we also uncover
differences across countries in the obstacles to SME financing. In particular, banks in developing
countries perceive macroeconomic factors to be the most important obstacle to SME financing,
while competition in the SME segment is the main obstacle among banks in developed countries.
Finally, across all countries, government programs to promote SME finance are perceived
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positively and bank prudential regulations and documentation requirements are not deemed by
banks to be a hurdle to SME financing.
This paper is related both to the U.S. literature on bank financing to small businesses as
well as to recent case studies on the topic outside the US, a number of which have been
conducted by the World Bank. There are two relevant strands in the U.S. literature on bank
financing to small businesses. The first strand includes studies that have investigated the
propensity of different types of banks to lend to SMEs. In particular, this literature has focused
on lending to SMEs by small and large banks and for the most part concludes that small banks
are more likely to lend to SMEs (see Berger, Kayshap, and Scalise 1995, Keeton 1995, Berger
and Udell 1996, and Strahan and Weston 1996). However, recent studies by Berger and Udell
(2006), and Berger, Rosen and Udell (2006) defy this conventional wisdom and discuss evidence
to the contrary. Specifically, Berger, Rosen, and Udell (2006) argue that there is not a small-bank
bias in lending to SMEs, as indicated by the fact that the probability that a small firm borrows
from a large bank is proportional to the market share of large banks. The second strand includes
studies that have examined the consequences of bank consolidation on small business lending.
Here the evidence is mixed. Studies such as Peek and Rosengren (1996), Berger, Saunders,
Scalise, and Udell (1998), Berger, Goldberg, and White (2001) find that mergers reduce small
business lending, while Whalen (1995) and Strahan and Weston (1998) provide evidence to the
contrary. Goldberg and White (1998) and DeYoung, Goldberg, and White (1999) show that the
decline in small business lending due to consolidation can be mitigated by de novo banks that
tend to lend more to SMEs than other banks.
Like the studies focused on the U.S., our paper focuses on bank financing to SMEs but
the similarities end there. Since our dataset targets the largest 5 banks across countries, we focus
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only on large bank financing and cannot speak about differences in lending between small and
large banks. Also, because we only have data for one year, we are not able to examine the
implications of changes in banking sector structure (like bank consolidation) on small business
financing. At the same time, our study goes deeper than most of the U.S. studies in examining
the business models and lending practices pursued by banks in connection to SMEs.
Furthermore, we document banks’ perceptions on the drivers and obstacles to financing SMEs.
We also explore banks’ perceptions on the role of government programs in financing SMEs and
on banking regulations. Finally, this paper’s biggest appeal is our ability to include information
on many important banks operating in a wide range of countries.
This paper is closely linked to and builds on a couple of previous International Finance
Corporation (IFC) and World Bank initiatives to better understand banks’ involvement with
SMEs. The IFC (2007) study was conceived to identify “best practices” in bank involvement
with SMEs, including key factors and links among business models, processes, tools, as well as
the actual performance in SME banking. As part of this effort, the IFC developed its own
questionnaire and in 2006 surveyed 11 banks assumed to be leaders in the SME business
segment operating in Australia, Brazil, India, the Netherlands, Poland, Thailand, the UK, and the
U.S.
As part of a Latin American Regional study on SME finance, the World Bank (2007a)
developed a survey to capture three broad areas of bank business with SMEs: the extent of banks’
involvement with SMEs, the determinants of the degree of bank financing to SMEs, and the business
model and risk management process that banks use when working with SMEs. The initial study
focused on Argentina and Chile and its objective was to cover the most important banks in terms of
assets and a wide range of banks in terms of types (e.g., small, large, foreign, domestic, and
niche banks). Similar studies using the same questionnaire and with the same objectives were
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done for Colombia (Stephanou and Rodriguez 2008 ) and Serbia (World Bank 2007b). Finally,
De la Torre, Martinez Peria, and Schmukler (2008) combine the data from the IFC and World
Bank case studies, along with data from SME surveys in Latin America, to show that the
conventional wisdom that relationship lending by small and niche banks is at the heart of SME
finance is misguided, at least in the countries they consider in their sample.
Though the questionnaire developed as part of this paper has elements of the surveys
used by the IFC (2007) and World Bank (2007a) studies, there are a couple of important
differences between our paper and these other studies. First, the objectives of all three studies are
different. While the IFC study is interested in benchmarking best practices in SME finance
around the world and the World Bank study is focused on examining in depth the banking
sector’s involvement with SMEs in individual countries, this study’s objective is to document the
state of large bank financing to SMEs around the world. Hence, we cover a lot more countries
than both other studies. In particular, we try to compare findings for developed and developing
countries. However, in striving to cover more countries, we can only focus on the largest banks.
Also, our questionnaire and this study places a lot more emphasis on obtaining and analyzing
quantitative data on the extent, type, and pricing of bank financing to SMEs than the other two
studies. Finally, wherever possible, this study tries to compare SME financing to large firm
financing which the other studies do not.
The rest of the paper is organized as follows. Section II describes the survey we use to
gather our data. Section III presents our findings regarding the extent, type, and pricing of banks
financing to SMEs across countries. Section IV documents what we find regarding banks’
business models and lending practices when it comes to serving SMEs. Section V presents the
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evidence on banks’ perceptions regarding the determinants of SME financing and the role that
government programs and regulations play and Section VI concludes.
II The Survey To gather information on bank financing to SMEs around the world, we designed a
survey with 56 questions focusing on three main areas. The first part includes questions to gauge
the extent, type, and pricing of bank financing to SMEs. To measure the extent of banks’
involvement with SMEs, we gathered data on the share of lending to SMEs vis-à-vis total loans.
To characterize the type of financing, we collected information on the share of loans devoted to
investment purposes and the ratio of loans that are collateralized or secured. We describe the
pricing of SME loans by gathering data on the fees and interest rates charged on these loans. For
many of these questions, we also asked for the corresponding values for large firms in order to
compare SME to large firm bank financing.
Second, the survey includes questions related to the business models, lending practices
and risk management setups used by banks to serve SMEs. In particular, we asked whether banks
have separate specialized departments to manage their business with SMEs, whether sales
decisions are separated from risk management, whether SME loans are processed at the branches
or at headquarters, whether credit scoring is used to approve SME loans, what types of criteria
are most important when evaluating SME loans (i.e., relative importance of financial assessment
of the business, firm credit history, firm owner characteristics, collateral, size of the loan,
purpose of the loan, etc.) and what type of collateral is most frequently used in SME lending.
Finally, we included questions to determine the factors that banks consider important
drivers and obstacles in their involvement with SMEs. In particular, we asked banks to rank the
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importance of factors related to the macroeconomic, regulatory, legal, and institutional
frameworks, as well as the significance of factors such as the demand for financing, the degree of
competition in the banking sector (and in different business segments), the level of taxes in the
economy, bank organizational issues, and SME specific factors (such as opacity, informality,
size, etc.). Within this section of the survey, we also included questions on the role and
importance of government programs and of regulations to facilitate financing to SMEs.
The survey targets the 5 largest banks in each country. We focus on the largest banks
because these are the ones with the most extensive branch networks and, hence, the ones most
accessible to SMEs, at least in terms of location. Also, these are the banks with the largest
lending capabilities.
Table 1 shows the number of banks and countries that responded to our survey along with
the banks’ market share. To date, we have obtained responses from 91 banks in 45 countries.
We obtained multiple bank responses for 30 countries: for 4 countries we got 4 banks to respond
in each country, for 8 countries we received responses from 3 banks, and for 18 countries we
obtained 2 bank responses. Only one bank responded in 15 countries.
Among the 45 countries in our sample, 38 are developing and the remaining 7 are
developed. Our dataset covers 14 countries in Eastern Europe and Central Asia, 9 in Latin
America and the Caribbean, 8 in Sub-Saharan Africa, 4 in South Asia, 2 in the Middle East and
North Africa and 1 in East Asia. All 7 developed countries are in Western Europe.
On average, the banks that responded account for 32 percent of banking system loans.
The loan market share exceeded 30 percent for 24 countries. For 25 countries, we were able to
get a response from the largest bank in the system.
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Our questionnaire includes quantitative and qualitative questions. To insure
representativeness and in order not to reveal banks’ identity, we report quantitative data at the
country-level only for those countries where more than one bank responded and the market share
of respondents exceeds 30 percent. We also show country-level figures for those countries where
the market shares might be below 30 percent, but the largest bank in the country was among
respondents. When we report quantitative country-level data, we show weighted averages where
we weigh each individual bank data by the share of loans held by each bank among banks that
responded in that country. Along with the individual country-level data, we report an unweighted
average for all banks operating in developing countries and, separately, in developed countries.
Information on the qualitative questions is conveyed by reporting the percentage of banks
that chose each option provided under each question. Because the number of banks covered in
each country in our survey is small, we do not show individual country-level responses. Instead,
we report the percentage of banks that chose each response, separating among banks operating in
developed and developing countries.
III The state of bank financing to SMEs
The vast majority of banks in our survey report having SME clients. Critically, most
banks offer deposit, payment, and credit services to SMEs, showing that they approach SME
banking broadly rather than narrowly focusing on lending only. Specifically, 100 percent of
banks in developed and 94 percent of banks in developing countries state that they offer loans,
deposit, and payment services to SMEs. Among the 80 banks from developing countries, 3 banks
state they provide loans and deposits services, 1 bank reports offering only deposit and payment
services, and only 1 bank indicates not having any SME clients.
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Most banks define SMEs in terms of sales. Approximately 85 percent of banks operating
in developing countries and 71 percent of those in developed countries use sales to define SMEs.
The remaining banks define SMEs in terms of assets or employees. On average, banks in
developing countries define small businesses as those with sales up to 4 million dollars and
medium-sized enterprises as those with sales up to 14.5 million dollars. Among banks in
developed countries, on average, SMEs have up to 5.5 million dollars in sales and medium-sized
enterprises’ sales average up to 28 million dollars.
Loan exposures to SMEs and to large firms are similar across banks operating in
developed and developing countries, with close to 20 percent of loans devoted to SMEs and
approximately 30 percent going to large firms (see Figure 1). Table 2b reveals that there are no
statistically significant differences between loan exposures of banks operating in developing and
developed countries. On the other hand, at least for banks operating in developing countries we
observe statistically significant differences between exposures by firm size (see Table 2a).
Specifically, across all developing country banks, the share of lending to SMEs averages 23
percent of total lending (in terms of amounts), while lending to large enterprises accounts for 33
percent of total lending.1 For banks operating in developed countries, SME bank financing
averages 18 percent and large firm financing accounts for 28 percent of total lending. Unlike the
case of banks operating in developing countries, this difference is not statistically significant,
perhaps because the number of observations for developed countries is quite small. Lending to
SMEs is highest in Georgia, where 61 percent of loans seem to be SME loans, and lowest in
Uruguay, where only 1 percent of loans are directed to SMEs.
Loan approval rates are similar for SMEs and large enterprises (Figure 2). Both among
developing and developed countries, we only find very small and statistically insignificant 1 The remaining loans are to households, financial institutions, and governments.
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differences between the percentage of SME loans approved and those approved for large firms
(Table 2a). In particular, among banks operating in developing countries the share of loan
applications approved for SME lending is 78 percent and it is 81 percent for large firms. Across
countries, only for India and Mexico do we observe significant differences in the share of
applications approved for SMEs and large firms. In India, 55 percent of SME applications
received are approved relative to 81 percent for large firms. In Mexico, these same numbers are
76 percent and 99 percent, respectively. The percentage of SME loan applications approved is
highest in Bulgaria at 97 percent and lowest in Slovenia with 16 percent. For banks in developed
countries, the share of SME loan applications approved is 83 percent and it is only 4 percentage
points higher (87 percent) for large firm loans. Table 2b shows that there are no significant
differences within firm size classes across banks operating in developing and developed
countries. In other words, we find no statistically significant differences in the share of
applications approved for SMEs and, separately, large firms by banks operating in developed and
developing countries.
While we observe considerable differences in the percentage of investment loans directed
to SMEs among banks operating in developed vis-à-vis developing countries (see Table 2b),
within each group of countries we do not observe significant differences in the shares of
investment loans for SMEs and those for large firms (see Figure 3 and Table 2a ).2 For banks
operating in developing countries, the average share of investment lending directed to SMEs
(i.e., how much of the SME lending is devoted to financing long-term investments) is 46 percent,
while it is close to 50 percent for large firms. As expected, investment lending is more common
in developed countries (perhaps due to a more efficient contractual framework and greater access
to information), where 68 percent of SME loans are for investment purposes and 73 percent of 2 Lebanon seems to be the only exception.
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large loans are also dedicated to financing investments. Across all countries, the share of SME
lending for investment purposes is highest among the largest banks in Switzerland (93%) and
lowest in Greece (18%).
The share of secured lending both to SMEs and large firms is generally lower (and
statistically different) among banks in developed countries vis-à-vis those in developing
countries (see Table 2b), while there is no significant difference across borrowers of different
sizes within each group of countries (see Figure 4 and Table 2a). The mean share of secured
SME loans among banks in developed countries is 49 percent, while it is 81 percent for banks in
developing countries. Similarly, for large firm financing the mean share of secured lending by
developed country banks is 43 percent, while it is 75 percent among banks in developing
countries. The larger share of secured lending by banks operating in developing countries might
reflect the weaker informational and contractual environment in these countries. Across
countries, the share of SME lending that is secured is highest in Costa Rica (100%) and lowest in
Malta (28%).
Figure 5 shows that fees charged on SME loans are generally lower for banks operating
in developed relative to developing countries. On average, the fees charged for SME loans by
developed country banks are 0.37 percent of these loans, while fees charged for SME loans by
developing country banks average 0.96 percent. This might reflect the higher fixed transaction
costs, typically smaller loan sizes, and less competitive banking sectors in developing countries.
Fees on large firm lending are lower than those on SME loans. Among developing country
banks fees average 0.83 percent and they average 0.22 percent among banks operating in
developed countries. Differences between the average fees for banks in developed and
developing countries (both for SMEs and large firms loans) are large and statistically significant
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(see Table 2b). On the other hand, the difference between fees on large and SME loans seem
surprisingly small, in particular, given the frequently stated argument that SME loans are based
on soft information that is very costly to gather for the bank. In fact, there is no statistical
difference between the means for fees on SMEs and large firms (see Table 2a). Across countries,
fees are highest in Kenya (2.8%) and lowest in Colombia (almost 0%).
As expected given differences in macroeconomic fundamentals (in particular, greater
growth and exchange rate stability and lower inflation) interest rates charged by banks operating
in developed countries are lower than those in developing countries (see Table 2b). On the other
hand, surprisingly, there is no significant difference in interest rates for the large and SME
borrowers within each country group (Figure 6 and Table 2a). The average interest charged to a
bank’s best clients on SME loans among banks operating in developed countries is 4.7 percent,
while the mean for banks operating in developing countries is 11.2 percent. For banks in
developed countries the interest rate on the best large firm clients averages 4 percent, less than 1
percentage point below that charged on SME loans. For banks in developing countries, the
difference between SME and large loan interest rates is one percentage point. Banks operating in
developing countries, on average charge 10.2 percent on large firm loans.
Figure 7 shows that interest rates charged on the highest risk (worst) clients are
significantly higher than the ones charged on the best clients, but the pattern described in terms
of differences between developed and developing countries and lack of differences between
SMEs and large firms continue to hold. The average interest rate on SME loans made by banks
operating in developed countries is 8.8 percent, while it is 15.7 percent for banks operating in
developing countries. As shown in Table 2b, these differences are statistically significant. On the
other hand, we find no significant difference between the rates charged on large firm loans and
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those charged on SME loans (see Table 2a). Among, developed country banks, the interest rates
charged on large firm loans averages 7.3 percent. The average interest rate on large firm loans
among developing country banks is 14 percent.
While SME loans perform worse than large enterprise loans across most countries, the
differences are not very large and they are only marginally statistically significant (i.e.,
significant at 10 percent) across banks in developing countries (see Figure 8 and Table 2a). For
these banks, the average share of non-performing loans to total loans for SMEs is 6.5 percent
while it is 4.1 percent for large firm loans. Among banks operating in developed countries, the
average share of non-performing loans is for 6.93 for SME loans and 2.54 for large firm loans.
Differences between non-performing loan shares for banks in developed and developing
countries are not statistically significant (see Table 2b). The share of SME loans that is non-
performing is lowest in Turkey (close to 0%) and highest in Malta (close to 17%).
Summarizing, banks in developing and developed countries are active in providing
financial services to SMEs. While there are differences in banks’ exposure to SMEs vis-à-vis
large firms, there are small and statistically insignificant differences in approval rates, share of
investment loans, ratios of secured lending, fees, and interest rates between loans to large
enterprises and SMEs. Instead, we observe significant differences between banks operating in
developed and developing countries.
IV Banks’ business models and lending practices in serving SMEs
In this section, we examine the business models and lending practices banks follow to
serve SMEs. How do banks structure their operations to serve SMEs? What degree of
decentralization do they allow for? How do banks make lending decisions? What criteria do
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banks use to make loans? What types of collateral are most commonly used? Wherever it is
possible, we compare our findings for small versus medium-sized businesses and we contrast
them to what banks report about their approach to large firm financing.
Most banks have set up separate departments to manage their relations with SMEs
(Figure 9). Sixty percent of developed country banks have an SME department, separate from
the division that deals with large businesses. Sixty-eight percent of developing country banks
indicate having a similar set up. Thirty percent of banks from developed countries say they have
separate departments for small businesses and for medium-sized enterprises. This set up is less
common among developing countries, where only 9 percent of banks report having a department
for small businesses and one for medium-sized enterprises. In developing countries, 12 percent
of banks have only a small business department and seem to lump medium-sized enterprises with
large enterprises and only 9 percent of banks do not have any special department to handle their
involvement with SMEs.
The majority of banks operating both in developed and developing countries have
decentralized the selling of non-lending products to small and medium-sized enterprises (Figure
10 and 11). Roughly 61 percent of banks in developing countries and 70 percent of banks
operating in developed countries respond that the sales of non-lending products to small
businesses is done only or primarily at branches (Figure 10). Decentralization is somewhat less
prevalent when it comes to medium-sized lending. Sixty percent of developed country banks and
51 percent of developing country banks select the same option for medium-sized enterprises
(Figure 11).
In contrast to sales, banks’ loan approval, risk management and non-performing loan
recovery functions tend to be more centralized, especially when it comes to medium-sized
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enterprises and, in particular, among developing country banks. While close to 45 (36) percent of
developed country banks say that loan approval for small (medium-sized) loans is done only or
primarily at branches, only 19 (14) percent of banks operating in developing countries report this
option for small(medium-sized) lending. Similarly, 40 (22) percent of developed country banks
respond that risk management for small business (medium-sized) lending is done only or
primarily at branches, while solely 8 (4) percent of developing country banks select this option
for small business (medium-sized) lending. Finally, both for developing and developed country
banks, non-performing loan recovery actions are mostly centralized. Only 20 percent of
developed country banks indicate that loan recovery for small and medium-sized loans is done
only or primarily at branches. Among developing country banks, only 13 (8) percent say that
small (medium-sized) business loan recovery is done primarily at branches.
Banks operating in developed and developing countries perceive that the demand for their
services from small and medium-sized firms is strong, but they indicate that they still have to do
a fair amount of reaching out to clients. Close to 90 percent of developing country banks and 80
percent of developed country banks select this option when asked about how much reaching out
banks are doing to clients.
While banks operating in developed countries seem to rely to a large extent on existing
databases (like credit registries) to go after potential SME clients, banks operating in developing
countries reach out to clients in many different ways (Figure 12). Almost 45 percent of
developed country banks say they use information from existing data sources. In contrast, only
16 percent of developing country banks say they rely on these databases, perhaps because they
are less frequently available in these countries. Banks in developing countries, on the other hand,
seem to focus on attracting SMEs that are clients/suppliers of existing clients or rely on existing
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deposit clients. Almost 27 percent select the first option and 25 percent select the second one,
respectively.
Banks from developed and developing countries are using scoring models for their
lending decisions to small firms, but less so for medium-sized enterprises (Figure 13). Only 18
percent of developed country banks say they do not use scoring for small business lending, while
almost 45 percent report not using scoring for medium-sized enterprise lending. Among
developing countries banks, as expected given that they tend to be less sophisticated, a higher
percentage is not using scoring. Almost 49 percent of banks are not using scoring for medium-
sized enterprises and 35 percent report not using scoring for small business lending.
But scoring is used primarily as one input in the lending decision process. Among banks
in developing countries, only 10(7) percent of banks report approving small(medium-sized)
business loans purely based on scoring as opposed to 54(44) percent that report using scoring as
an input for small(medium-sized) business lending. Among banks in developed countries, 82
percent say that scoring is only an input into loan decisions for small businesses and 55 percent
give the same response in connection to loans to medium-sized enterprises.
When scoring is not used as the main loan approval mechanism, the majority of banks in
developing countries report that lending decisions for both small and medium-sized enterprises
are made by the credit risk and sales department in conjunction (Figure 14). For small business
loans almost 83 percent of banks indicate this option. This percentage climbs to 85 percent for
lending to medium-sized enterprises. When it comes to small business lending among developed
country banks, 60 percent of them state that the sales department has the capacity to approve
loans independently. On the other hand, for medium-sized loans 83 percent of banks report that
lending decisions are made by the sales and credit departments in conjunction.
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While the financial assessment is the most important loan approval criterion across
countries, a firm’s credit history and owner characteristics are important in developing countries,
while loan size is the second-most important criterion in developed economies. We examine
separately the criteria used for small and medium-sized business lending and compare this to
banks’ responses regarding lending to large firms. In particular, Figures 15, 16 and 17 report the
percentage of banks that rank each option presented as the most important for small, medium-
sized, and large business lending, respectively. We examine the role of collateral, the financial
assessment of the business, a firm’s credit history with the bank, a firm’s credit history from a
credit registry, the firm’s owner characteristics, and the size and purpose of the loan. For small
business lending, 50 percent of developed country banks and 49 percent of developing country
banks indicate that the financial assessment of the business is the most important criteria (Figure
15). Among developed country banks, the size of the loan receives the second most votes as the
key factor driving small business lending (20 percent of banks select this option). The purpose of
the loan, the collateral and a firm’s credit history from a registry are all mentioned next, with 10
percent of banks selecting each of these options. Among developing country banks, a firm’s
credit history with the bank is the second most selected criteria followed by firms’ owner
characteristics and collateral. Almost 16 percent of developing country banks indicate that a
firm’s credit history with the bank is the most important criteria, while 9 percent of developing
country banks pick firm’s owner characteristics. Approximately, 8 percent reports collateral as
the most important criteria.
While we observe a similar pattern for medium-sized as for small business financing
(Figure 16), the financial assessment of the firm is more important for medium-sized business
financing than for small business lending and collateral is relatively less important. Sixty-three
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percent of developed country banks and 59 percent of developing country banks report the
financial assessment of the business as the most important criteria. Similarly to what we found
for small business lending, among developed country banks the size of the loan is second in
importance, with 18 percent of developed country banks reporting this option. Among
developing country banks, the credit history of the firm and the owner characteristic rank second
and third as the most important criteria banks consider when approving a loan. On the other
hand, collateral is only mentioned as the most important factor among 4 percent of developing
country banks.
Surprisingly, we do not find many differences in terms of the criteria for making loans to
large businesses relative to what we find for small and medium-sized enterprises (Figure 17).
Perhaps the most notable difference is that a higher percentage of banks report the financial
assessment of the business as the most important criteria considered in lending to large firms. In
particular, 70 percent of developed country banks and 63 percent of banks from developing
countries indicate this option. Among developed country banks, the size of the loan, purpose of
the loan, and firm credit history are tied in the rankings, with 10 percent of banks choosing each
of these factors as the most important. Among developing country banks, firm’s credit history
with the bank continues to be the second most reported option, with 13 percent of banks
choosing this response.
While not a decisive approval criterion, at least three quarters of banks require collateral
to make business loans (Figure 18). Once again, we do not see significant differences in terms of
small, medium-sized and large firm financing. Among developed countries, 78 percent of banks
require collateral for small business financing, almost 88 percent require it for medium-sized
business lending and 75 percent require it for large firm financing. As expected given that the
20
informational and institutional environment is weaker in developing countries, a higher
percentage of banks require collateral to make business loans in these countries. Almost 87
percent of banks required collateral for small business lending, 93 percent require it for medium-
sized enterprise financing and 94 percent ask for collateral for loans made to large firms.
Real estate is the most frequently used type of collateral for small business lending, but
less so in developing countries (Figure 19). Almost 56 percent of banks in developed countries
indicate that real estate is the most commonly used type of collateral for small business lending.
In contrast, 37 percent of developing country banks report real estate as the most important
collateral type. Among these banks, cash and other liquid assets rank second in terms of
importance as collateral types, with 23 percent of banks indicating this option. Bank and
personal guarantees and cash and other liquid assets are equally important for banks in developed
countries, with 22 percent of banks reporting each of these options.
Real estate is even more important as collateral for lending to medium-sized businesses.
Relative to small business lending, a higher percentage of banks report real estate as the most
important collateral type for medium-sized business lending, especially among developed
country banks (Figure 20). Eighty percent of them indicate real estate as the most important type
of collateral, while 10 percent select cash and other liquid assets and 10 percent choose bank and
personal guarantees. On the other hand, 40 percent of developing country banks select real estate
as the most important collateral type for medium-sized lending and 23 percent indicate that cash
and other liquid assets are important.
For large enterprise lending, real estate appears to be less commonly used as collateral by
developed country banks, while the proportion of developing country banks using real estate as
collateral for large firm financing is very similar to that found for medium-sized and small
21
business lending (Figure 21). Approximately 63 percent of developed country banks and 39
percent of developing country banks use real estate as collateral for large firm financing. Bank
and personal guarantees are the second most commonly used collateral type among developed
country banks, while banks operating in developing countries tend to rely more on cash and
liquid assets. Among developed country banks, twenty five percent select bank and personal
guarantees, while only 14 percent of banks operating in developing countries indicate using this
collateral type. On the other hand, 21 percent of banks in developing countries use cash and other
liquid assets as collateral for large firm financing, while only 13 percent of developed country
banks select this option.
Summarizing, banks across all countries have set up separate departments to serve SMEs,
have decentralized the sale of financial products to the branches, but continue to centralize the
loan approval, risk management, and loan recovery functions. Though scoring models are used
by most banks in the sample, especially in small business lending, they are only one input in the
loan decision process. Finally, we observe some differences in the lending criteria and collateral
used by banks operating developed vis-à-vis developing countries. In particular, banks in
developing countries are relatively more likely to engage in relationship lending, making lending
decisions based on a firm’s credit history with the bank and the firm owner characteristics.
Furthermore, while real estate is the most important collateral for SME loans around the world, it
is less so in developing countries where liquid assets are also commonly used as collateral.
V What factors affect bank financing to SMEs?
Our survey includes a number of questions related to the determinants of banks’
involvement with SMEs. In particular, we ask banks about the drivers and obstacles to their
22
involvement, about the size of the market and future prospects, and about the role of government
programs and of regulations in shaping their exposure to SMEs.
Figure 22 reveals that the most important driver for banks’ involvement with SMEs is the
perceived profitability of this segment. Eighty-one percent of banks from developed countries
and 72 percent of banks from developing countries indicate that this is the most important
determinant for their involvement. In the case of banks from developing countries, 9 percent of
respondents mention competition in the large business segment as being the most important
driver. Competition for retail customers seems to be more important among developed country
banks. Nine percent of these banks select this as the most important driver. Finally, 9 percent of
developed country banks and 5 percent of developing country banks indicate that the most
important driver for their involvement with SMEs is the possibility to seek out these clients
through their existing relations with large clients.
The fact that most banks find the SME market desirable is also confirmed in Figure 23.
The figure shows banks’ responses to how they perceive the SME market. Eighty-two percent of
banks from developed countries and 83 percent from developing countries respond that they
believe the SME market is big (in terms of the number of potential clients) and that prospects are
good. The SME market is perceived to be small but prospects to be good by 14 percent of
developing country banks. Only 3 percent of banks from developing countries respond that they
think the prospects for the SME segment are bleak, while 18 percent of developed country banks
respond in this way.
While most banks seem to agree on the factors driving their involvement with SMEs and
perceive prospects in this segment to be very good, there is more widespread disagreement
regarding the obstacles to banks’ growth in this line of business (Figure 24). Among banks in
23
developed countries, the top obstacle seems to be competition in the SME segment. Forty-five
percent give the highest rating to this obstacle. Lack of adequate demand bank also seems to be a
consideration. Eighteen percent of developed country banks rank this as the main obstacle. On
the other hand, among developing country bank, the top rated obstacle is the state of the
macroeconomy. Thirty-nine percent of banks indicate this as the top reason impeding their
growth in the SME segment.3 Regulations and competition in the SME segment also seem to be
important. Seventeen percent of respondents indicate regulation and 15 percent mark competition
in the SME segment as the top obstacles. Surprisingly, only 8 percent of developing country
banks rate the legal and contractual environment as the top obstacle. This suggests that banks
adapt to the legal and contractual environment in which they operate perhaps by offering
instruments that allow them to circumvent existing deficiencies (See de la Torre, Martinez Peria
and Schmukler 2008). Similarly, only 6 percent of banks in developing countries cite SME-
specific factors (like opacity or informality) as an obstacle.
Banks report that government programs to promote SME finance exist in 6 out of the 7
developed economies and 32 out of the 45 developing countries in our sample. Consistent with
recent evidence (Beck, Klapper, Mendoza, 2008; Honohan, 2008), guarantee schemes are the
most common government program used to support SME financing among developed countries
and developing countries. According to the surveyed banks, such schemes are in operation in 6
developed countries and 28 developing countries. Directed credit programs are the second most
popular among developing countries. They are in place in 24 developing countries. Among
developed countries, interest rate subsidies are the second most common, they exist in 5 of the 7
countries in our sample. Interest rate subsidies are also prevalent among developing countries, 23
3 We also ask banks to list the macroeconomics factors that were most problematic. Most banks mention macro instability, high interest rates and exchange rate risk.
24
economies have them in place. Regulatory subsidies are less common. Only 16 developing
countries and only 3 developed countries have these.
In general, banks have a positive perception of government programs to support SMEs
(Figure 25). In developing countries more than 70 percent of banks rate the impact of interest
subsidies, guarantee programs, and even directed credit program as positive. Regulatory
subsidies are less popular with only 47 of banks rating them as having a positive influence. But,
these programs are less common and in most cases they are rated as inconsequential. Among,
developed countries more than 50 percent of banks rate government programs as having a
positive effect on their involvement with SMEs.
Not surprisingly given how ubiquitous guarantee program are, banks from developed and
developing countries rate them as the most important government program influencing SME
financing (Figure 26). Specifically, 50 percent of developed country banks and 56 percent of
banks from developing countries rate guarantees as the most influential government program.
Among banks in developed countries, directed credit programs are the second most popular with
40 percent of banks ranking them as the most influential. On the other hand, developing country
banks perceive interest rate subsidies and directed credit programs as equally influential since in
21 percent of banks are ranking each of these programs as the most important.
It is important to be careful in interpreting banks’ responses regarding the impact of
government programs. Banks might have a positive view of these programs and perceive them as
influential even if they are not successful in terms of their public policy objectives. For example,
banks can rate the effect of these programs as positive because they allow them to offer cheap or
longer term financing to their existing clients allowing them to solidify their banking
relationships, but yet the programs might be failing the goal of extending bank financing to
25
previously unserved SMEs. Hence, while it is interesting to know banks’ perception of
government programs, an evaluation of their true impact requires much more careful analysis
and data.
Aside from the role of specific programs to promote SME financing, governments can
influence banks’ involvement with SMEs through the regulations that they put in place. Figure
27 examines the role of regulations concerning documentation requirements for lending to
SMEs, while Figure 28 shows banks’ impression of how prudential regulations affect their
involvement with SMEs. Sixty-four percent of developed country banks and 68 percent of
developing country banks indicate that they perceive documentation requirements for lending to
SMEs to be “appropriate and beneficial” compared to 20 percent of developing country banks
and 9 percent of developed country banks that consider them “excessive”. Similarly, most banks
consider prudential regulations to have a positive or inconsequential effect on SME financing.
Fifty-four percent of developing country banks indicate that prudential regulations have a
positive impact and 24 percent of these banks rate them inconsequential. Among developed
country banks, almost 36 percent rate them positively and 46 percent of banks consider them
inconsequential. This is an interesting finding, given that recent country studies (Adasme,
Majnoni and Uribe, 2006) have found that capital requirements can have a bias against SME
lending, as SME loans are more risky overall but have less tail risk than large enterprise loans.
Access to credit history information appears to be particularly important for banks in
developing countries (Figure 29). More than two thirds of developing country banks respond that
the existence of a credit bureau in their country facilitates SME lending. On the other hand, only
44 percent of banks from developed countries rate the existence of a credit bureau as beneficial
for SME lending. These differences might reflect the fact that SME opaqueness (e.g., lack of
26
verifiable financial statements for the firm) and perhaps informality are greater issues for banks
operating in developing countries. This finding is also consistent with aggregate results from
Djankov, McLiesh and Shleifer (2007) who find that the quality of credit information sharing is
more important for financial deepening in developing than in developed countries.
In summary, banks are attracted to the SME segment due to its perceived high
profitability and good prospects. While banks in developed countries see competition as a major
obstacle, banks in developing countries point mainly to macroeconomic conditions. Banks’
reaction to government support programs is positive overall and prudential regulations do not
seem to be perceived as a hurdle. Access to information through the existence of credit registries
is especially valued by banks operating in developing countries.
VI Conclusions
This paper surveyed banks around the world to document the state of SME financing
across countries and to compare it to large firm financing, wherever possible. We find that across
countries, banks perceive serving SMEs as a profitable endeavour and almost all banks have
SME clients. Though we find differences in exposure, lending practices, business models, drivers
and obstacles of SME finance for banks operating in developed vis-à-vis developing countries,
we uncover surprisingly small differences when we compare banking to SMEs relative to large
firms.
While a large literature has used firm-level data to analyze differences in access to
finance by firm size, this paper is a first step in better understanding SMEs financing from the
supply side. Going forward, it would be interesting to expand the number of banks and countries
surveyed in order to see if we can corroborate our findings in a larger sample. Also, it would be
27
useful to explore in greater depth what drives the differences we have found across developed
and developing countries.
28
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32
Table 1 Survey respondents: countries, banks, and market share
Table shows the countries in our sample, the number of banks that responded from each country (including whether the largest bank has participated in the survey) and the market share of respondents relative to total loans.
Country No. of Banks Has largest bank responded? Market share covered (% of loans to total system loans)
Albania 3 Yes 59%
Armenia 3 Yes 35%
Austria 1 1%
Belarus 1 Yes 48%
Belgium 1 10%
Bosnia 2 Yes 38%
Brazil 1 9%
Bulgaria 2 Yes 32%
Chile 1 19%
Colombia 3 Yes 48%
Costa Rica 2 Yes 31%
Croatia 2 22%
Ecuador 1 Yes 38%
El Salvador 1 26%
Ethiopia 1 16%
Finland 1 Yes 38%
Georgia 3 47%
Greece 2 Yes 33%
Honduras 2 29%
Hungary 2 Yes 35%
India 4 Yes 41%
Indonesia 2 20%
Jordan 1 6%
Kenya 2 Yes 27%
Lebanon 3 Yes 37%
Lithuania 3 48%
Malawi 2 Yes 65%
Malta 3 Yes 71%
Mexico 2 Yes 23%
Moldova 2 35%
Nepal 1 8%
Pakistan 1 Yes 14%
Poland 1 8%
Sierra Leone 2 21%
Slovakia 2 Yes 40%
Slovenia 4 Yes 61%
South Africa 2 Yes 11%
Sri Lanka 4 Yes 69%
Swaziland 1 35%
Sweden 1 27%
Switzerland 2 Yes 40%
Turkey 3 Yes 24%
Uruguay 2 Yes 46%
Zambia 2 28%
Zimbabwe 4 25%
33
Table 2.a Test of differences in means between SMEs and large firms
Variable Income group Mean for SME loans
Mean for large firms loans
t-test p-value
Developed 17.93% 27.88% 1.18 0.26 Share of total loans Developing 22.99% 32.80% 2.33 0.02** Developed 82.75% 86.94% 0.29 0.80
Share of applications approved Developing 78.11% 80.76% 0.52 0.61 Developed 68.04% 72.93% 0.35 0.74
Share of loans for investment Developing 46.18% 49.82% 0.74 0.46 Developed 49.27% 42.80% -0.45 0.67
Share of secured loans Developing 81.48% 74.85% -1.36 0.18 Developed 0.37% 0.22% -0.68 0.51
Loan fees Developing 0.96% 0.83% -0.73 0.47 Developed 4.66% 4.00% -0.59 0.57
Interest rates on best clients Developing 11.16% 10.22% -0.74 0.46 Developed 8.79% 7.30% -0.86 0.41
Interest rates on worst clients Developing 15.65% 14.09% -0.98 0.33 Developed 6.93% 2.54% -1.46 0.19
Share of non-performing loans Developing 6.49% 4.13% -1.68 0.10*
*, ***,*** indicate significance at the 10, 5, and 1 percent levels, respectively
Table 2.b Test of differences in means between developed and developing countries Variable Firm Type Mean for
Developing Countries
Mean for Developed Countries
t-test p-value
SMEs 22.99% 17.93% -1.03 0.32 Share of total loans Large firms 32.80% 27.88% -0.61 0.55
SMEs 78.11% 82.75% 0.57 0.59 Share of applications approved
Large firms 80.76% 86.94% 0.47 0.71 SMEs 46.18% 68.04% 1.58 0.18
Share of loans for investment Large firms 49.82% 72.93% 4.26 0.01**
SMEs 81.48% 49.27% -3.01 0.03** Share of secured loans
Large firms 74.85% 42.80% -2.92 0.03** SMEs 0.96% 0.37% -2.90 0.02**
Loan fees Large firms 0.83% 0.22% -3.23 0.00***
SMEs 11.16% 4.66% -5.28 0.00*** Interest rates on best clients
Large firms 10.22% 4.00% -5.32 0.00*** SMEs 15.65% 8.79% -3.96 0.00***
Interest rates on worst clients Large firms 14.09% 7.30% -4.21 0.00***
SMEs 6.49% 6.93% 0.14 0.89 Share of non-performing loans
Large firms 4.13% 2.54% -1.19 0.25 *, ***,*** indicate significance at the 10, 5, and 1 percent levels, respectively
34
Fig
ure
1 L
oan
expo
sure
to
SME
s an
d la
rge
firm
s F
igur
e sh
ows
the
perc
enta
ge o
f lo
ans
dire
cted
to S
ME
s (b
ars)
and
larg
e fi
rms
(tri
angl
es).
Dat
a re
port
ed f
or in
divi
dual
cou
ntri
es w
as o
btai
ned
by ta
king
the
wei
ghte
d av
erag
e ac
ross
ba
nks
in th
e co
untr
y, w
here
the
wei
ght
is g
iven
by
the
loan
mar
ket
shar
e of
eac
h ba
nk a
mon
g al
l ba
nks
for
whi
ch w
e ha
ve d
ata.
We
only
rep
ort
data
for
cou
ntri
es w
here
at
leas
t 2
bank
s re
spon
ded
and
the
mar
ket
shar
e of
res
pond
ents
was
gre
ater
tha
n 30
per
cent
. Mea
n fo
r ba
nks
oper
atin
g in
dev
elop
ed a
nd, s
epar
atel
y, d
evel
opin
g co
untr
ies
are
not
wei
ghte
d an
d in
clud
e al
l ban
ks th
at r
espo
nded
to o
ur s
urve
y, in
depe
nden
t of
thei
r m
arke
t sha
re. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
1%1%
2%4%
4%6%
7%8%
9%10
%13
%14
%15
%15
%18
%19
%20
%23
%24
%24
%25
%27
%30
%32
%
48%
61%
0%20%
40%
60%
80%
100%
Uruguay South Africa
Sri Lanka
MexicoKenya
HungarySwitzeland
MalawiLebanon
Costa RicaGreece
IndiaMoldovaSlovakia
Cross Bank Mean Developed Countrie
s (6)AlbaniaBulgaria
Cross Bank Mean Developing Countrie
s (35)
MaltaArmenia
BosniaLithuania
TurkeySlovenia
ColombiaGeorgia
Share of amount of loans out of total loans (%)
Shar
e of
loan
s (a
mou
nt) t
o SM
EsSh
are
of lo
ans
(am
ount
) to
larg
e fir
ms
35
Fig
ure
2 Sh
are
of lo
an a
pplic
atio
ns a
ppro
ved
for
SME
and
larg
e fi
rm lo
ans
Fig
ure
show
s th
e pe
rcen
tage
of
appl
icat
ions
app
rove
d am
ong
SM
E (
bars
) an
d la
rge
(tri
angl
es)
firm
loan
app
lica
tions
. Dat
a re
port
ed f
or in
divi
dual
cou
ntri
es w
as o
btai
ned
by ta
king
th
e w
eigh
ted
aver
age
acro
ss b
anks
in
the
coun
try,
whe
re t
he w
eigh
t is
giv
en b
y th
e lo
an m
arke
t sh
are
of e
ach
bank
am
ong
all
bank
s fo
r w
hich
we
have
dat
a. W
e on
ly r
epor
t da
ta
for
coun
trie
s w
here
at l
east
2 b
anks
res
pond
ed a
nd th
e m
arke
t sha
re o
f re
spon
dent
s w
as g
reat
er th
an 3
0 pe
rcen
t. M
ean
for
bank
s op
erat
ing
in d
evel
oped
and
, sep
arat
ely,
dev
elop
ing
coun
trie
s ar
e no
t w
eigh
ted
and
incl
ude
all
bank
s th
at r
espo
nded
to o
ur s
urve
y, i
ndep
ende
nt o
f th
eir
mar
ket
shar
e. D
ata
com
e fr
om t
he s
urve
y of
ban
ks c
ondu
cted
ele
ctro
nica
lly
by
the
auth
ors.
16%
32%
39%
43%
45%
55%
58%
61%
62%
69%
76%
77%
78%
81%
83%
89%
89%
91%
93%
95%
97%
0%20%
40%
60%
80%
100%
Slove
niaM
oldov
aSlo
vakia
Kenya Costa
Rica
India
Georg
iaGre
ece
Leban
on
Mala
wiM
exico
Malt
a
Cross
Bank M
ean D
evelo
ping C
ountr
ies (2
6)Colom
bia
Cross
Bank M
ean D
evelo
ped C
ountri
es (4
) South A
frica
Alban
iaSri
Lanka
Hunga
rySwitz
eland
Bulgaria
Applications approved out of applications received (%)
SME
appl
icat
ions
app
rove
dLa
rge
firm
app
licat
ions
app
rove
d
36
Fig
ure
3 Sh
are
of in
vest
men
t lo
ans
amon
g SM
E a
nd la
rge
firm
loan
s F
igur
e sh
ows
the
perc
enta
ge o
f in
vest
men
t lo
ans
amon
g S
ME
(ba
rs)
and
larg
e (t
rian
gles
) fi
rm l
oans
. D
ata
repo
rted
for
ind
ivid
ual
coun
trie
s w
as o
btai
ned
by t
akin
g th
e w
eigh
ted
aver
age
acro
ss b
anks
in
the
coun
try,
whe
re t
he w
eigh
t is
giv
en b
y th
e lo
an m
arke
t sh
are
of e
ach
bank
am
ong
all
bank
s fo
r w
hich
we
have
dat
a. W
e on
ly r
epor
t da
ta f
or c
ount
ries
w
here
at l
east
2 b
anks
res
pond
ed a
nd th
e m
arke
t sha
re o
f re
spon
dent
s w
as g
reat
er th
an 3
0 pe
rcen
t. M
ean
for
bank
s op
erat
ing
in d
evel
oped
and
, sep
arat
ely,
dev
elop
ing
coun
trie
s ar
e no
t wei
ghte
d an
d in
clud
e al
l ban
ks th
at r
espo
nded
to o
ur s
urve
y, in
depe
nden
t of
thei
r m
arke
t sha
re. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
18%
30%
35%
42%
44%
46%
47%
48%
49%
52%
53%
58%
62%
62%
63%
65%
68%
72%
93%
0%20%
40%
60%
80%
100%
Greec
eKen
ya South A
frica
Slova
kiaLeb
anon
Cross
Bank M
ean D
evelo
ping C
ountr
ies (2
3)
India Costa
Rica
Lithuan
iaSlo
venia
Hunga
ryColom
bia Sri
Lanka
Georg
iaAlb
ania
Armen
ia
Cross
Bank
Mea
n Dev
eloped
Coun
tries
(4)
Malt
a Switzela
ndLoans for investment (%)
Shar
e of
SM
E in
vest
men
t loa
ns
Shar
e of
larg
e fir
m in
vest
men
t loa
ns
37
Fig
ure
4 Sh
are
of s
ecur
ed lo
ans
amon
g SM
E a
nd la
rge
firm
loan
s F
igur
e sh
ows
the
perc
enta
ge o
f se
cure
d lo
ans
amon
g S
ME
(ba
rs)
and
larg
e (t
rian
gles
) fi
rm l
oans
. D
ata
repo
rted
for
ind
ivid
ual
coun
trie
s w
as o
btai
ned
by t
akin
g th
e w
eigh
ted
aver
age
acro
ss b
anks
in
the
coun
try,
whe
re t
he w
eigh
t is
giv
en b
y th
e lo
an m
arke
t sh
are
of e
ach
bank
am
ong
all
bank
s fo
r w
hich
we
have
dat
a. W
e on
ly r
epor
t da
ta f
or c
ount
ries
w
here
at l
east
2 b
anks
res
pond
ed a
nd th
e m
arke
t sha
re o
f re
spon
dent
s w
as g
reat
er th
an 3
0 pe
rcen
t. M
ean
for
bank
s op
erat
ing
in d
evel
oped
and
, sep
arat
ely,
dev
elop
ing
coun
trie
s ar
e no
t wei
ghte
d an
d in
clud
e al
l ban
ks th
at r
espo
nded
to o
ur s
urve
y, in
depe
nden
t of
thei
r m
arke
t sha
re. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
28%
30%
33%
49%
50%
55%
65%
67%
73%
76%
81%
89%
90%
91%
94%
96%
99%
100%
100%
0%20%
40%
60%
80%
100%
Malt
a Switzela
nd South A
frica
Cross
Bank M
ean D
evelo
ped C
ountri
es (5
)
Greec
eCol
ombi
aLeb
anon
Kenya
India
Slov
akia
Cross
Bank M
ean D
evelo
ping C
ountr
ies (2
4)
Hunga
rySri
Lanka
Slov
enia
Georg
iaLith
uania
Armen
iaAlb
ania Cos
ta Rica
Secured loans (%)
Shar
e of
SM
E se
cure
d lo
ans
Shar
e of
larg
e fir
m s
ecur
ed lo
ans
38
Fig
ure
5 F
ees
char
ged
on S
ME
and
larg
e fi
rm lo
ans
Fig
ure
show
s th
e fe
es o
n S
ME
(ba
rs)
and
larg
e fi
rm (
tria
ngle
s) l
oans
. D
ata
repo
rted
for
ind
ivid
ual
coun
trie
s w
as o
btai
ned
by t
akin
g th
e w
eigh
ted
aver
age
acro
ss b
anks
in
the
coun
try,
whe
re t
he w
eigh
t is
giv
en b
y th
e lo
an m
arke
t sh
are
of e
ach
bank
am
ong
all
bank
s fo
r w
hich
we
have
dat
a. W
e on
ly r
epor
t da
ta f
or c
ount
ries
whe
re a
t le
ast
2 ba
nks
resp
onde
d an
d th
e m
arke
t sh
are
of r
espo
nden
ts w
as g
reat
er t
han
30 p
erce
nt.
Mea
n fo
r ba
nks
oper
atin
g in
dev
elop
ed a
nd,
sepa
rate
ly,
deve
lopi
ng c
ount
ries
are
not
wei
ghte
d an
d in
clud
e al
l ban
ks th
at r
espo
nded
to o
ur s
urve
y, in
depe
nden
t of
thei
r m
arke
t sha
re. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
0.0
0%
0.0
8%
0.1
9%0
.29
%0
.31%
0.3
7%0
.41%
0.4
9%0.
50%
0.7
4%0.
77%
0.8
9%0.
96%
1.07
%1.
10%
1.14
%1.2
0%1.2
6%
2.8
6%
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
Colom
bia Switz
eland
Armen
ia
Malt
a South A
frica
Cross
Bank M
ean D
evelo
ped C
ountri
es (4
)
India
Slove
niaSri
Lanka
Slova
kiaGeo
rgia
Lithua
nia
Cross
Bank M
ean D
evelo
ping C
ountr
ies (2
5)Hun
gary
Bosnia
Alban
iaLeb
anon
Costa
Rica
Kenya
Loan fees (%)
Fees
on
SME
loan
sFe
es o
n la
rge
firm
loan
s
39
Fig
ure
6 In
tere
st r
ates
cha
rged
on
best
(lo
wes
t ri
sk)
SME
and
larg
e fi
rm lo
ans
Fig
ure
show
s th
e in
tere
st r
ates
cha
rged
on
the
best
(lo
wes
t ri
sk)
SM
E (
bars
) an
d la
rge
firm
(tr
iang
les)
loa
ns.
Dat
a re
port
ed f
or i
ndiv
idua
l co
untr
ies
was
obt
aine
d by
tak
ing
the
wei
ghte
d av
erag
e ac
ross
ban
ks i
n th
e co
untr
y, w
here
the
wei
ght
is g
iven
by
the
loan
mar
ket
shar
e of
eac
h ba
nk a
mon
g al
l ba
nks
for
whi
ch w
e ha
ve d
ata.
We
only
rep
ort
data
for
co
untr
ies
whe
re a
t le
ast
2 ba
nks
resp
onde
d an
d th
e m
arke
t sh
are
of r
espo
nden
ts w
as g
reat
er t
han
30 p
erce
nt.
Mea
n fo
r ba
nks
oper
atin
g in
dev
elop
ed a
nd,
sepa
rate
ly,
deve
lopi
ng
coun
trie
s ar
e no
t w
eigh
ted
and
incl
ude
all
bank
s th
at r
espo
nded
to o
ur s
urve
y, i
ndep
ende
nt o
f th
eir
mar
ket
shar
e. D
ata
com
e fr
om t
he s
urve
y of
ban
ks c
ondu
cted
ele
ctro
nica
lly
by
the
auth
ors.
1.6%
2.2%
3.9%
4.3%
4.7%
4.7%
6.0%
6.4%
6.5%
7.2%
7.9%
8.2%
11.1%
11.5
%
15.4
%15
.5%
16.5
%
18.7
%
11.2
%11
.2%
0%2%4%6%8%10%
12%
14%
16%
18%
20% Hun
gary
Slova
kiaColom
bia Switz
eland
Cross
Bank M
ean D
evelo
ped C
ountri
es (5
)
Greec
eSlo
venia
Malt
aLith
uania
Alban
iaLeb
anon
Bosnia South
Afri
ca
Cross
Bank M
ean D
evelo
ping C
ountr
ies (2
3)
India Costa
Rica
Georg
iaArm
enia
Kenya Sri
Lanka
Interest rate on best (lowest risk) loans (%)
Inte
rest
rate
on
SME
best
(low
est r
isk)
loan
s
Inte
rest
rate
s on
larg
e fir
m b
est (
low
est r
isk)
loan
s
40
Fig
ure
7 In
tere
st r
ates
cha
rged
on
wor
st (
high
est
risk
) SM
E a
nd la
rge
firm
loan
s F
igur
e sh
ows
the
inte
rest
rat
es c
harg
ed o
n th
e be
st (
high
est
risk
) SM
E (
bars
) an
d la
rge
firm
(tr
iang
les)
loa
ns.
Dat
a re
port
ed f
or i
ndiv
idua
l co
untr
ies
was
obt
aine
d by
tak
ing
the
wei
ghte
d av
erag
e ac
ross
ban
ks i
n th
e co
untr
y, w
here
the
wei
ght
is g
iven
by
the
loan
mar
ket
shar
e of
eac
h ba
nk a
mon
g al
l ba
nks
for
whi
ch w
e ha
ve d
ata.
We
only
rep
ort
data
for
co
untr
ies
whe
re a
t le
ast
2 ba
nks
resp
onde
d an
d th
e m
arke
t sh
are
of r
espo
nden
ts w
as g
reat
er t
han
30 p
erce
nt.
Mea
n fo
r ba
nks
oper
atin
g in
dev
elop
ed a
nd,
sepa
rate
ly,
deve
lopi
ng
coun
trie
s ar
e no
t w
eigh
ted
and
incl
ude
all
bank
s th
at r
espo
nded
to o
ur s
urve
y, i
ndep
ende
nt o
f th
eir
mar
ket
shar
e. D
ata
com
e fr
om t
he s
urve
y of
ban
ks c
ondu
cted
ele
ctro
nica
lly
by
the
auth
ors.
5.1%
6.6%
7.6%
8.0%
8.2%
8.8%
9.6%
9.7%
9.8%
9.8%
10.2
%
13.5
%14
.7%
15.7
%17
.8%
19.3
%19
.9%
19.9
%
24.2
%31.7
%
0%5%10%
15%
20%
25%
30%
35%
40% Hun
gary
Slova
kiaSlo
venia
Malt
aLith
uania
Cross
Bank M
ean D
evelo
ped C
ountri
es (5
)Leb
anon
Alban
iaBosn
ia
Greec
e Switzela
ndCosta
Rica
India
Cross
Bank M
ean D
evelo
ping C
ountr
ies (2
3) South A
frica
Armen
iaSri
Lanka
Kenya
Colombi
aGeo
rgia
Interest rate on the worst (highest risk) loans (%)
Inte
rest
rate
on
SME
wor
st (h
ighe
st ri
sk) l
oans
Inte
rest
rate
s on
larg
e fir
m w
orst
(hig
hest
risk
) loa
ns
41
Fig
ure
8 Sh
are
of S
ME
and
larg
e fi
rm n
on-p
erfo
rmin
g lo
ans
Fig
ure
show
s th
e pe
rcen
tage
of
SM
E (
bars
) an
d la
rge
firm
(tr
iang
les)
non
-per
form
ing
loan
s. D
ata
repo
rted
for
ind
ivid
ual
coun
trie
s w
as o
btai
ned
by t
akin
g th
e w
eigh
ted
aver
age
acro
ss b
anks
in
the
coun
try,
whe
re t
he w
eigh
t is
giv
en b
y th
e lo
an m
arke
t sh
are
of e
ach
bank
am
ong
all
bank
s fo
r w
hich
we
have
dat
a. W
e on
ly r
epor
t da
ta f
or c
ount
ries
whe
re a
t le
ast
2 ba
nks
resp
onde
d an
d th
e m
arke
t sh
are
of r
espo
nden
ts w
as g
reat
er t
han
30 p
erce
nt.
Mea
n fo
r ba
nks
oper
atin
g in
dev
elop
ed a
nd,
sepa
rate
ly,
deve
lopi
ng c
ount
ries
are
not
w
eigh
ted
and
incl
ude
all b
anks
that
res
pond
ed to
our
sur
vey,
inde
pend
ent o
f th
eir
mar
ket s
hare
. Dat
a co
me
from
the
surv
ey o
f ba
nks
cond
ucte
d el
ectr
onic
ally
by
the
auth
ors.
0.0%
0.0%
0.4%
1.0%
2.1%
2.2%
2.3%
2.5%
2.7%
4.0%
4.2%
4.9%
5.4%
6.5%
6.9%
6.9%
9.2%
9.9%
9.9%
10.2
%10
.8%
17.2
%
0%5%10%
15%
20%
25% Tur
key
Greec
e Armen
iaHun
gary Switz
eland
Slove
niaGeo
rgia Colom
bia Lith
uania
Slova
kiaAlb
ania
India
South
Afri
ca
Cross
Bank M
ean D
evelo
ping C
ountr
ies (3
1)
Cross
Bank M
ean D
evelo
ped C
ountri
es (4
) Sri L
anka
Mold
ova
Bosnia
Mala
wi Leban
onKen
yaM
alta
Share of non-performing loans out of total loans (%)
Shar
e of
SM
E no
n-pe
rfor
min
g lo
ans
Shar
e of
larg
e fir
m n
on-p
erfo
rmin
g lo
ans
42
Fig
ure
9 B
anks
’ or
gani
zati
onal
set
up
to s
erve
SM
Es
Thi
s fi
gure
is
base
d on
ban
ks’
resp
onse
s to
the
que
stio
n “P
leas
e in
dica
te (
wit
h a
‘Yes
’ or
‘N
o’)
whe
ther
you
r ba
nk h
as a
sep
arat
e de
part
men
t th
at a
tten
ds t
o: S
mal
l-si
zed
ente
rpri
ses
sepa
rate
ly, M
ediu
m-s
ized
ent
erpr
ises
sep
arat
ely
and
Smal
l an
d M
ediu
m s
ized
ent
erpr
ises
sep
arat
ely”
. We
show
the
per
cent
age
of b
anks
tha
t an
swer
ed ‘
Yes
’ to
eac
h of
th
e op
tions
giv
en a
s po
ssib
le r
espo
nses
. A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
tha
t se
lect
ed e
ach
opti
on.
Dat
a co
me
from
the
sur
vey
of b
anks
con
duct
ed
elec
tron
ical
ly b
y th
e au
thor
s
.
60%
(6)
30%
(3)
10%
(1)
0%0%
12%
(9)
1% (1)
68%
(53)
9% (7)
9% (7)
0%20%
40%
60%
80%
100%
Smal
l-si
zed
ente
rpri
ses
sepa
rate
lyM
ediu
m-s
ized
ent
erpr
ises
sepa
rate
lySm
all a
nd m
ediu
m s
ized
ente
rpri
ses
com
bine
d (b
utse
para
tely
fro
m la
rge
firm
s)
Smal
l and
med
ium
siz
eden
terp
rise
s se
para
tely
Non
e of
the
optio
ns
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
7T
otal
Res
pons
es D
evel
oped
Cou
ntri
es:1
0
43
Fig
ure
10
Ext
ent
of d
ecen
tral
izat
ion
in b
anks
’ se
t up
to
serv
e sm
all e
nter
pris
es
Thi
s fi
gure
is
base
d on
ban
ks’
resp
onse
s to
the
ques
tion
“W
hat
aspe
cts
of t
he s
mal
l en
terp
rise
ban
king
bus
ines
s ar
e de
cent
rali
zed
(onl
y do
ne a
t br
anch
es a
nd d
one
prim
aril
y at
the
br
anch
es)
and
at w
hat
leve
l?”.
We
show
the
per
cent
age
of b
anks
tha
t ch
ose
each
of
the
opti
ons
give
n as
pos
sibl
e re
spon
ses.
Als
o, w
ithi
n pa
rent
hese
s, w
e di
spla
y th
e nu
mbe
r of
ba
nks
that
sel
ecte
d ea
ch o
ptio
n. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
20%
(2)
40%
(4)
45%
(5)
70%
(7)
13%
(10)
8% (6)
19%
(15)
61%
(45)
0%20%
40%
60%
80%
100%
Sale
of
non-
lend
ing
prod
ucts
Loa
n ap
prov
alR
isk
man
agem
ent
Non
-per
form
ing
loan
rec
over
y
Percentage of banks
Dev
elop
edD
evel
opin
g
Res
pons
es D
evel
opin
g C
ount
ries
: 74
Res
pons
es D
evel
oped
Cou
ntri
es: 1
0R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
7R
espo
nses
Dev
elop
ed C
ount
ries
:11
Res
pons
es D
evel
opin
g C
ount
ries
: 76
Res
pons
es D
evel
oped
Cou
ntri
es: 1
0R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
5R
espo
nses
Dev
elop
ed C
ount
ries
: 10
44
Fig
ure
11
Ext
ent
of d
ecen
tral
izat
ion
in b
anks
’ se
t up
to
serv
e m
ediu
m-s
ized
ent
erpr
ises
T
his
figu
re is
bas
ed o
n ba
nks’
res
pons
es to
the
ques
tion
“Wha
t asp
ects
of
the
med
ium
-siz
ed e
nter
pris
e ba
nkin
g bu
sine
ss a
re d
ecen
tral
ized
(on
ly d
one
at b
ranc
hes
and
done
pri
mar
ily
at th
e br
anch
es)
and
at w
hat l
evel
?”. W
e sh
ow th
e pe
rcen
tage
of
bank
s th
at c
hose
eac
h of
the
opti
ons
give
n as
pos
sibl
e re
spon
se. A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
that
sel
ecte
d ea
ch o
ptio
n. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
60%
(6)
36%
(4)
22%
(2)
20%
(2)
51%
(36)
14%
(10)
4% (3)
8% (6)
0%20%
40%
60%
80%
100%
Sale
of
non-
lend
ing
prod
ucts
Loa
n ap
prov
alR
isk
man
agem
ent
Non
-per
form
ing
loan
rec
over
y
Percentage of banks
Dev
elop
edD
evel
opin
g
Res
pons
es D
evel
opin
g C
ount
ries
: 70
Res
pons
es D
evel
oped
Cou
ntri
es: 1
0R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
4R
espo
nses
Dev
elop
ed C
ount
ries
: 11
Res
pons
es D
evel
opin
g C
ount
ries
: 73
Res
pons
es D
evel
oped
Cou
ntri
es: 9
Res
pons
es D
evel
opin
g C
ount
ries
: 72
Res
pons
es D
evel
oped
Cou
ntri
es: 1
0
45
F
igur
e 12
W
ays
in w
hich
ban
ks r
each
out
to
pote
ntia
l SM
E c
lient
s T
his
figu
re i
s ba
sed
on b
anks
’ re
spon
ses
to t
he q
uest
ion
“How
do
you
iden
tify
pote
ntia
l S
ME
cli
ents
? R
ank
from
1 t
o 5
(wit
h 1
bein
g th
e m
ost
impo
rtan
t) t
he i
mpo
rtan
ce o
f th
e fo
llow
ing
poss
ible
way
s of
ide
ntif
ying
cli
ents
”. W
e sh
ow t
he p
erce
ntag
e of
ban
ks t
hat
rank
ed e
ach
of t
he o
ptio
ns a
s th
e m
ost
impo
rtan
t (i
.e.,
perc
enta
ge t
hat
rank
ed e
ach
opti
on
“1”)
. Als
o, w
ithi
n pa
rent
hese
s, w
e di
spla
y th
e nu
mbe
r of
ban
ks th
at s
elec
ted
each
opt
ion.
Dat
a co
me
from
the
surv
ey o
f ba
nks
cond
ucte
d el
ectr
onic
ally
by
the
auth
ors.
Bec
ause
not
al
l the
ban
ks h
ave
rank
ed a
n op
tion
“1”,
add
ing
all b
anks
wil
l not
equ
al 1
00 p
erce
nt.
0%
18%
(2)
45.% (5)
9% (1)
27%
(20)
25%
(19)
16%
(12)
23%
(17)
0%20%
40%
60%
80%
100%
Rel
y on
exi
stin
g de
posi
tcl
ient
sU
se in
form
atio
n fr
om e
xist
ing
firm
dat
abas
es (
e.g.
cre
dit
bure
aus)
Attr
act c
lien
ts w
ith b
ank
cred
itFo
cus
on a
ttra
ctin
g SM
Es
that
are
clie
nts/
supp
liers
of
your
exis
ting
cli
ents
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
5T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
1
46
Fig
ure
13
Ban
ks’
use
of s
cori
ng m
odel
s in
SM
E le
ndin
g T
his
figu
re i
s ba
sed
on b
anks
’ re
spon
ses
to t
he q
uest
ion
“Doe
s yo
ur b
ank
use
scor
ing
mod
els
to a
ppro
ve l
oans
to
smal
l-si
zed
or m
ediu
m-s
ized
ent
erpr
ises
?”.
We
show
the
pe
rcen
tage
of
bank
s th
at c
hose
eac
h of
the
opt
ions
giv
en a
s po
ssib
le r
espo
nses
. A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
tha
t se
lect
ed e
ach
optio
n. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
0%0%
45%
(5)
55%
(6)
18%
(2)
82%
(9)
49%
(35)
44%
(31)
7% (5)
35%
(26)
54%
(40)
10%
(8)
0%20%
40%
60%
80%
100%
Yes
, app
rova
l is
com
plet
ely
done
by
scor
ing
Yes
, but
sco
ring
ison
ly a
n in
put i
nto
loan
dec
isio
n
No,
sco
ring
pla
ys n
oro
le in
loan
dec
isio
nY
es, a
ppro
val i
sco
mpl
etel
y do
ne b
ysc
orin
g
Yes
, but
sco
ring
ison
ly a
n in
put i
nto
loan
dec
isio
n
No,
sco
ring
pla
ys n
oro
le in
loan
dec
isio
n
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
4 (S
mal
l Ent
erpr
ises
) T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
1T
otal
Res
pons
es D
evel
opin
g C
ount
ries
: 71
(Med
ium
Ent
erpr
ises
)T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
1
Smal
l -si
zed
Ent
erpr
ises
Med
ium
-siz
ed E
nter
pris
es
47
Fig
ure
14
SME
loan
app
rova
l pro
cedu
res
Thi
s fi
gure
is
base
d on
ban
ks’
resp
onse
s to
the
que
stio
n “I
f yo
u do
not
use
sco
ring
mod
els
in s
mal
l-si
zed
(SE
) or
med
ium
-siz
ed (
ME
) en
terp
rise
s lo
an a
ppro
val,
who
app
rove
s th
ese
loan
s?”.
We
show
the
perc
enta
ge o
f ba
nks
that
cho
se e
ach
of th
e op
tions
giv
en a
s po
ssib
le r
espo
nses
. Als
o, w
ithi
n pa
rent
hese
s, w
e di
spla
y th
e nu
mbe
r of
ban
ks t
hat s
elec
ted
each
opt
ion.
Dat
a co
me
from
the
surv
ey o
f ba
nks
cond
ucte
d el
ectr
onic
ally
by
the
auth
ors.
0%0%
83%
(5)
17%
(1)
40%
(2)
60%
(3)
85%
(47
)
13%
(7)
2% (1)
83%
(43)
12%
(6)
6% (3)
0%20%
40%
60%
80%
100%
Sal
es d
epar
tmen
tex
clus
ivel
ySa
les
depa
rtm
ent
with
inpu
t but
no
veto
fro
m c
redi
t ris
kde
part
men
t
Sale
s an
d cr
edit
ris
kde
part
men
t nee
d to
agre
e
Sale
s de
part
men
tex
clus
ivel
yS
ales
dep
artm
ent
with
inpu
t but
no
veto
fro
m c
redi
t ris
kde
part
men
t
Sale
s an
d cr
edit
ris
kde
part
men
t nee
d to
agre
e
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 5
2 (S
mal
l Ent
erpr
ises
) T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 5
(Sm
all E
nter
pris
es)
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 5
5 (
Med
ium
Ent
erpr
ises
)T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 6
(M
ediu
m E
nter
pris
es)
Smal
l-si
zed
Ent
erpr
ises
Med
ium
-siz
ed E
nter
pris
es
48
Fig
ure
15
Cri
teri
a us
ed b
y ba
nks
to e
valu
ate
smal
l ent
erpr
ise
loan
s T
his
figu
re i
s ba
sed
on b
anks
’ re
spon
ses
to t
he q
uest
ion
“Ple
ase
indi
cate
how
im
port
ant
are
for
your
ban
k th
e fo
llow
ing
fact
ors
in m
akin
g de
cisi
ons
rega
rdin
g bu
sine
ss l
oans
to
smal
l en
terp
rise
s” R
ank
impo
rtan
ce f
rom
1 t
o 8
(wit
h 1
bein
g th
e m
ost
impo
rtan
t)”.
We
show
the
per
cent
age
of b
anks
tha
t ra
nked
eac
h of
the
opt
ions
giv
en a
s th
e m
ost
impo
rtan
t (i
.e.,
the
perc
enta
ge t
hat
rank
ed e
ach
opti
on a
s “1
”).
Als
o, w
ithi
n pa
rent
hese
s, w
e di
spla
y th
e nu
mbe
r of
ban
ks t
hat
sele
cted
eac
h op
tion.
Dat
a co
me
from
the
sur
vey
of b
anks
co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s. B
ecau
se n
ot a
ll th
e ba
nks
have
ran
ked
an o
ptio
n “1
”, a
ddin
g al
l ban
ks w
ill n
ot e
qual
100
per
cent
.
0%0%
10%
(1)
10%
(1)
20%
(2)
10%
(1)
50%
(5)
0%0%
9% (7)
4% (3)
16%
(12)
49%
(38)
8% (6)
0%20%
40%
60%
80%
100%
Col
late
ral
Fina
ncia
las
sess
men
t of
the
busi
ness
Firm
's cr
edit
hist
ory
with
you
rba
nk
Firm
's cr
edit
hist
ory
from
acr
edit
regi
stry
Firm
's o
wne
rch
arac
teri
stic
s(a
ge, s
ex, e
tc.)
Siz
e of
the
loan
Purp
ose
for
the
loan
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
7T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
0
49
Fig
ure
16
Cri
teri
a us
ed b
y ba
nks
to e
valu
ate
med
ium
-siz
ed e
nter
pris
e lo
ans
Thi
s fi
gure
is
base
d on
ban
ks’
resp
onse
s to
the
que
stio
n “P
leas
e in
dica
te h
ow i
mpo
rtan
t ar
e fo
r yo
ur b
ank
the
foll
owin
g fa
ctor
s in
mak
ing
deci
sion
s re
gard
ing
busi
ness
loa
ns t
o m
ediu
m-s
ized
ent
erpr
ises
” R
ank
impo
rtan
ce f
rom
1 t
o 8
(wit
h 1
bein
g th
e m
ost
impo
rtan
t)”.
We
show
the
per
cent
age
of b
anks
tha
t ra
nked
eac
h of
the
opt
ions
giv
en a
s th
e m
ost
impo
rtan
t (i
.e.,
the
perc
enta
ge t
hat
rank
ed e
ach
optio
n as
“1”
). A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
tha
t se
lect
ed e
ach
opti
on. D
ata
com
e fr
om t
he s
urve
y of
ba
nks
cond
ucte
d el
ectr
onic
ally
by
the
auth
ors.
Bec
ause
not
all
the
bank
s ha
ve r
anke
d an
opt
ion
“1”,
add
ing
all b
anks
will
not
equ
al 1
00 p
erce
nt.
0%0%
0%0%
9% (1)
18%
(2)
9% (1)
63%
(7
)
9% (7)
9% (7)
14%
(10)
14%
(10)
59%
(44)
4% (3)
0%20%
40%
60%
80%
100%
Col
late
ral
Fina
ncia
las
sess
men
t of
the
busi
ness
Firm
's cr
edit
hist
ory
with
you
rba
nk
Firm
's cr
edit
hist
ory
from
acr
edit
reg
istr
y
Firm
's ow
ner
char
acte
rist
ics
(age
, sex
, etc
.)
Size
of
the
loan
Purp
ose
for
the
loan
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
4T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
1
50
Fig
ure
17
Cri
teri
a us
ed b
y ba
nks
to e
valu
ate
larg
e en
terp
rise
loan
s T
his
figu
re i
s ba
sed
on b
anks
’ re
spon
ses
to t
he q
uest
ion
“Ple
ase
indi
cate
how
im
port
ant
are
for
your
ban
k th
e fo
llow
ing
fact
ors
in m
akin
g de
cisi
ons
rega
rdin
g bu
sine
ss l
oans
to
larg
e en
terp
rise
s” R
ank
impo
rtan
ce f
rom
1 t
o 8
(wit
h 1
bein
g th
e m
ost
impo
rtan
t)”.
We
show
the
per
cent
age
of b
anks
tha
t ra
nked
eac
h of
the
opt
ions
giv
en a
s th
e m
ost
impo
rtan
t (i
.e.,
the
perc
enta
ge t
hat
rank
ed e
ach
opti
on a
s “1
”).
Als
o, w
ithi
n pa
rent
hese
s, w
e di
spla
y th
e nu
mbe
r of
ban
ks t
hat
sele
cted
eac
h op
tion.
Dat
a co
me
from
the
sur
vey
of b
anks
co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s. B
ecau
se n
ot a
ll th
e ba
nks
have
ran
ked
an o
ptio
n “1
”, a
ddin
g al
l ban
ks w
ill n
ot e
qual
100
per
cent
.
0%0%
0%
10%
(1)
10%
(1)
10%
(1)
70%
(7)
0%
10%
(6)
11%
(7)
2% (1)
13%
(8)
3% (2)
63%
(40)
0%20%
40%
60%
80%
100%
Col
late
ral
Fina
ncia
las
sess
men
t of
the
busi
ness
Firm
's cr
edit
hist
ory
with
you
rba
nk
Firm
's c
redi
thi
stor
y fr
om a
cred
it re
gist
ry
Firm
's o
wne
rch
arac
teri
stic
s(a
ge, s
ex, e
tc.)
Size
of
the
loan
Purp
ose
for
the
loan
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 6
3T
otal
Res
pons
es D
evel
oped
Cou
ntri
es:
10
51
Fig
ure
18
Ban
ks’
use
of c
olla
tera
l in
busi
ness
lend
ing
Thi
s fi
gure
is b
ased
on
bank
s’ r
espo
nses
to th
e qu
esti
on “
Do
you
requ
ire
coll
ater
al?”
. We
show
the
perc
enta
ge o
f ba
nks
that
ans
wer
ed ‘
Yes
’. A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
that
sel
ecte
d ea
ch o
ptio
n. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
75%
(6)
88%
(7)
78%
(7)
94%
(64
)93
% (
71)
87%
(65)
0%20%
40%
60%
80%
100%
For
loan
s to
sm
all-
size
d en
terp
rise
sFo
r lo
ans
to m
ediu
m-s
ized
ent
erpr
ises
For
loan
s to
larg
e en
terp
rise
s
Percentage of banksD
evel
oped
Dev
elop
ing
Res
pons
es D
evel
opin
g C
ount
ries
:: 7
5R
espo
nses
Dev
elop
ed C
ount
ries
: 9R
espo
nses
Dev
elop
ing
Cou
ntri
es::
68
Res
pons
es D
evel
oped
Cou
ntri
es: 8
Res
pons
es D
evel
opin
g C
ount
ries
:: 7
6R
espo
nses
Dev
elop
ed C
ount
ries
: 8
52
Fig
ure
19
Typ
es o
f co
llate
ral u
sed
for
smal
l ent
erpr
ise
lend
ing
Thi
s fi
gure
is
base
d on
ban
ks’
resp
onse
s to
the
que
stio
n “W
hat
type
s of
ass
ets
are
com
mon
ly u
sed
as c
olla
tera
l fo
r sm
all
busi
ness
len
ding
? R
ank
impo
rtan
ce f
rom
1 t
o 7
(wit
h 1
bein
g th
e m
ost
impo
rtan
t)”.
We
show
the
per
cent
age
of b
anks
tha
t ra
nked
eac
h of
the
opt
ions
giv
en a
s th
e m
ost
impo
rtan
t (i
.e.,
the
perc
enta
ge t
hat
rank
ed e
ach
opti
on “
1”).
Als
o,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
tha
t se
lect
ed e
ach
optio
n. D
ata
com
e fr
om t
he s
urve
y of
ban
ks c
ondu
cted
ele
ctro
nica
lly
by t
he a
utho
rs.
Bec
ause
not
all
the
bank
s ha
ve r
anke
d an
opt
ion
“1”,
add
ing
all b
anks
wil
l not
equ
al 1
00 p
erce
nt.
0%0%
22%
(2)
22%
(2)
56%
(5)
14%
(10)
13%
(9)
7% (5)
37%
(26)
23%
(16)
0%20%
40%
60%
80%
100%
Lan
dE
quip
men
tR
eal e
stat
eB
ank/
pers
onal
gua
rant
eeC
ash
and
othe
r liq
uid
asse
ts
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es::
70T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 9
53
Fig
ure
20
Typ
es o
f co
llate
ral u
sed
for
med
ium
-siz
ed e
nter
pris
e le
ndin
g T
his
figu
re i
s ba
sed
on b
anks
’ re
spon
ses
to t
he q
uest
ion
“Wha
t ty
pes
of a
sset
s ar
e co
mm
only
use
d as
col
late
ral
for
med
ium
-siz
ed b
usin
ess
lend
ing?
Ran
k im
port
ance
fro
m 1
to
7 (w
ith
1 be
ing
the
mos
t im
port
ant)
”. W
e sh
ow th
e pe
rcen
tage
of
bank
s th
at r
anke
d ea
ch o
f th
e op
tion
s gi
ven
as th
e m
ost i
mpo
rtan
t (i.e
., th
e pe
rcen
tage
that
ran
ked
each
opt
ion
“1”)
. A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
tha
t se
lect
ed e
ach
optio
n. D
ata
com
e fr
om t
he s
urve
y of
ban
ks c
ondu
cted
ele
ctro
nica
lly
by t
he a
utho
rs. B
ecau
se n
ot a
ll th
e ba
nks
have
ran
ked
an o
ptio
n “1
”, a
ddin
g al
l ban
ks w
ill n
ot e
qual
100
per
cent
.
0%0%
10%
(1)
10%
(1)
80%
(8)
23%
(15)
9% (6)
40%
(26)
9% (6)
12%
(8)
0%20%
40%
60%
80%
100%
Lan
dE
quip
men
tR
eal e
stat
eB
ank/
pers
onal
gua
rant
eeC
ash
and
othe
r liq
uid
asse
ts
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es::
65T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
0
54
Fig
ure
21
Typ
es o
f co
llate
ral u
sed
for
larg
e en
terp
rise
lend
ing
Thi
s fi
gure
is
base
d on
ban
ks’
resp
onse
s to
the
que
stio
n “W
hat
type
s of
ass
ets
are
com
mon
ly u
sed
as c
olla
tera
l fo
r la
rge
busi
ness
len
ding
? R
ank
impo
rtan
ce f
rom
1 t
o 7
(wit
h 1
bein
g th
e m
ost
impo
rtan
t)”.
We
show
the
per
cent
age
of b
anks
tha
t ra
nked
eac
h of
the
opt
ions
giv
en a
s th
e m
ost
impo
rtan
t (i
.e.,
the
perc
enta
ge t
hat
rank
ed e
ach
opti
on “
1”).
Als
o,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
tha
t se
lect
ed e
ach
optio
n. D
ata
com
e fr
om t
he s
urve
y of
ban
ks c
ondu
cted
ele
ctro
nica
lly
by t
he a
utho
rs.
Bec
ause
not
all
the
bank
s ha
ve r
anke
d an
opt
ion
“1”,
add
ing
all b
anks
wil
l not
equ
al 1
00 p
erce
nt.
0%0%
13%
(1)
63%
(5)
25%
(2)
21%
(12)
14%
(8)
16%
(9)
7% (4)
39%
(22)
0%20%
40%
60%
80%
100%
Lan
dE
quip
men
tR
eal e
stat
eB
ank/
pers
onal
gua
rant
eeC
ash
and
othe
r li
quid
asse
ts
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es::
57T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 8
55
Fig
ure
22
Ban
ks’
perc
epti
ons
of th
e dr
iver
s of
SM
E le
ndin
g T
his
figu
re i
s ba
sed
on b
anks
’ re
spon
ses
to th
e qu
esti
on “
To
wha
t de
gree
is
your
inv
olve
men
t w
ith
SM
Es
driv
en b
y th
e fo
llow
ing?
Ran
k im
port
ance
fro
m 1
to
7 (w
ith
1 be
ing
the
mos
t im
port
ant)
”. W
e sh
ow t
he p
erce
ntag
e of
ban
ks t
hat
rank
ed e
ach
of t
he o
ptio
ns g
iven
as
the
mos
t im
port
ant
(i.e
., th
e pe
rcen
tage
tha
t ra
nked
eac
h op
tion
as
“1”)
. Als
o, w
ithi
n pa
rent
hese
s, w
e di
spla
y th
e nu
mbe
r of
ban
ks th
at s
elec
ted
each
opt
ion.
Dat
a co
me
from
the
surv
ey o
f ba
nks
cond
ucte
d el
ectr
onic
ally
by
the
auth
ors.
Bec
ause
not
all
the
bank
s ha
ve
rank
ed a
n op
tion
“1”
, add
ing
all b
anks
wil
l not
equ
al 1
00 p
erce
nt.
0%0.
%0%
9%
(1)
9%
(1)
81%
(9)
5% (4)
3% (2)
1% (1)
1% (1)
9% (7)
72%
(55
)
0%20%
40%
60%
80%
100%
Perc
eive
dpr
ofita
bilit
y in
the
SME
seg
men
t
Inte
nse
com
peti
tion
for
larg
e co
rpor
ates
Inte
nse
com
peti
tion
for
reta
il cu
stom
ers
Exc
essi
ve e
xpos
ure
to la
rge
corp
orat
esE
xces
sive
exp
osur
eto
ret
ail c
usto
mer
sse
ctor
Pos
sibi
lity
to s
eek
out S
ME
s th
roug
hex
istin
g re
latio
nsw
ith
larg
e cl
ient
s(e
.g.,
reve
rse
fact
orin
g)
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
6T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
1
56
Fig
ure
23
Ban
ks’
perc
epti
ons
of th
e si
ze a
nd p
rosp
ects
of
the
SME
mar
ket
Thi
s fi
gure
is
base
d on
ban
ks’
resp
onse
s to
the
que
stio
n “W
hat
is y
our
view
on
the
size
and
pro
spec
ts f
or t
he S
ME
mar
ket
in g
ener
al,
not
just
for
you
r ba
nk?”
. W
e sh
ow t
he
perc
enta
ge o
f ba
nks
that
cho
se e
ach
of th
e op
tions
giv
en a
s po
ssib
le r
espo
nse.
Als
o, w
ithi
n pa
rent
hese
s, w
e di
spla
y th
e nu
mbe
r of
ban
ks th
at s
elec
ted
each
opt
ion.
Dat
a co
me
from
th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
0%
82%
(9)
18%
(2)
83%
(6
5)
3% (2)
14%
(11)
0%20%
40%
60%
80%
100%
SME
mar
ket i
s sm
all a
ndpo
rspe
cts
are
blea
kSM
E m
arke
t is
smal
l but
pros
pect
s ar
e go
odSM
E m
arke
t is
big
but
pros
pect
s ar
e bl
eak
SME
mar
ket i
s bi
g an
dpr
ospe
cts
are
good
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
8T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
1
57
Fig
ure
24
Ban
ks’
perc
epti
ons
on t
he o
bsta
cles
on
SME
lend
ing
Thi
s fi
gure
is
base
d on
ban
ks’
resp
onse
s to
the
que
stio
n “I
ndic
ate
to w
hat
degr
ee t
he f
ollo
win
g fa
ctor
s ar
e im
port
ant
obst
acle
s to
you
r ex
posu
re t
o/in
volv
emen
t w
ith
SM
Es
and
rank
im
port
ance
fro
m 1
to 8
(w
ith
1 be
ing
the
mos
t im
port
ant)
.” W
e sh
ow th
e pe
rcen
tage
of
bank
s th
at r
anke
d ea
ch o
f th
e op
tion
s gi
ven
as th
e m
ost i
mpo
rtan
t (i.e
., th
e pe
rcen
tage
th
at r
anke
d ea
ch o
ptio
n as
“1”
). A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
tha
t se
lect
ed e
ach
optio
n. D
ata
com
e fr
om t
he s
urve
y of
ban
ks c
ondu
cted
ele
ctro
nica
lly
by th
e au
thor
s.
0%
18%
(2)
45%
(5)
9% (1)
9% (1)
9% (1)
9% (1)
6% (4)
15%
(11)
6% (4)
8% (6)
8% (6)
17%
(12)
39%
(28)
0%20%
40%
60%
80%
100%
Mac
roec
onom
ic(e
cono
my-
wid
e)fa
ctor
s)
Reg
ulat
ions
Leg
al a
ndco
ntra
ctua
len
viro
nmen
t
Ban
k sp
ecif
icfa
ctor
sN
atur
e of
the
lend
ing
tech
nolo
gy to
SME
s
Com
peti
tion
inth
e SM
Ese
gmen
t
Lac
k of
ade
quat
ede
man
d
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
1T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
1
58
Fig
ure
25
Ban
ks’
atti
tude
tow
ards
gov
ernm
ent
prog
ram
s to
pro
mot
e SM
E f
inan
cing
T
his
figu
re i
s ba
sed
on b
anks
’ re
spon
ses
to t
he q
uest
ion
“Ple
ase
com
men
t on
the
eff
ect
of t
he f
ollo
win
g go
vern
men
t pr
ogra
ms
on y
our
invo
lvem
ent
wit
h S
ME
s”.
We
show
the
pe
rcen
tage
of
bank
s th
at r
ate
gove
rnm
ent
prog
ram
s as
hav
ing
a “p
osit
ive”
im
pact
on
bank
’s i
nvol
vem
ent
wit
h S
ME
s. A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
th
at s
elec
ted
this
opt
ion.
Dat
a co
me
from
the
surv
ey o
f ba
nks
cond
ucte
d el
ectr
onic
ally
by
the
auth
ors.
0%
75%
(3)
57%
(4)
67%
(6)
47%
(7)
76%
(36)
73%
(38)
71%
(32)
0%20%
40%
60%
80%
100%
Inte
rest
sub
sidi
esG
uara
ntee
pro
gram
sD
irec
ted
cred
it pr
ogra
ms
Reg
ulat
ory
subs
idie
s (l
ike
low
er p
rovi
sion
s)
Percentage of banks
Dev
elop
edD
evel
opin
g
Res
pons
es D
evel
opin
g C
ount
ries
: 47
Res
pons
es D
evel
oped
Cou
ntri
es: 7
Res
pons
es D
evel
opin
g C
ount
ries
: 52
Res
pons
es D
evel
oped
Cou
ntri
es: 9
Res
pons
es D
evel
opin
g C
ount
ries
: 45
Res
pons
es D
evel
oped
Cou
ntri
es: 4
Res
pons
esD
evel
opin
g C
ount
ries
: 15
Res
pons
es D
evel
oped
Cou
ntri
es: 3
59
Fig
ure
26
Ban
ks’
rank
ing
of g
over
nmen
t pr
ogra
ms
to p
rom
ote
SME
fin
anci
ng
Thi
s fi
gure
is b
ased
on
bank
s’ r
espo
nses
to th
e qu
esti
on “
Ran
k th
e im
port
ance
fro
m 1
to 5
(w
ith
1 be
ing
the
mos
t im
port
ant)
of
the
foll
owin
g go
vern
men
t pro
gram
s in
inf
luen
cing
yo
ur i
nvol
vem
ent
wit
h S
ME
s. W
e sh
ow t
he p
erce
ntag
e of
ban
ks t
hat
rank
ed e
ach
of t
he o
ptio
ns g
iven
as
the
mos
t im
port
ant
(i.e
., th
e pe
rcen
tage
tha
t ra
nked
eac
h op
tion
as
“1”)
. A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
that
sel
ecte
d ea
ch o
ptio
n. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
0%
40%
(2)
50%
(4)
17%
(1)
16%
(5)
21%
(11)
56%
(3
0)
21%
(12)
0%20%
40%
60%
80%
100%
Inte
rest
sub
sidi
esG
uara
ntee
pro
gram
sD
irec
ted
cred
it p
rogr
ams
Reg
ulat
ory
subs
idie
s (l
ike
low
er p
rovi
sion
s)
Percentage of banksD
evel
oped
Dev
elop
ing
Res
pons
es D
evel
opin
g C
ount
ries
: 56
Res
pons
es D
evel
oped
Cou
ntri
es: 5
Res
pons
es D
evel
opin
g C
ount
ries
: 32
Res
pons
es D
evel
oped
Cou
ntri
es: 3
Res
pons
es D
evel
opin
g C
ount
ries
: 52
Res
pons
es D
evel
oped
Cou
ntri
es: 3
Res
pons
es D
evel
opin
g C
ount
ries
: 54
Res
pons
es D
evel
oped
Cou
ntri
es: 4
60
Fig
ure
27
Ban
ks’
impr
essi
on o
f th
e bu
rden
pos
ed b
y do
cum
enta
tion
req
uire
men
ts f
or le
ndin
g to
SM
Es
Thi
s fi
gure
is
base
d on
ban
ks’
resp
onse
s to
the
que
stio
n “G
ive
your
im
pres
sion
on
the
burd
en p
osed
by
docu
men
tati
on r
equi
rem
ents
(if
any
) fo
r le
ndin
g to
SM
Es”
. We
show
the
pe
rcen
tage
of
bank
s th
at c
hose
eac
h of
the
opt
ions
giv
en a
s po
ssib
le r
espo
nses
. A
lso,
wit
hin
pare
nthe
ses,
we
disp
lay
the
num
ber
of b
anks
tha
t se
lect
ed e
ach
optio
n. D
ata
com
e fr
om th
e su
rvey
of
bank
s co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
27%
(3)
64%
(7)
9% (1)
12%
(9)
68%
(51)
20%
(15)
0%20%
40%
60%
80%
100%
Exc
essi
ve
App
ropr
iate
and
ben
efic
ial
Inco
nseq
uent
ial
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
5T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
1
61
Fig
ure
38
Ban
ks’
impr
essi
on o
f ho
w p
rude
ntia
l reg
ulat
ions
aff
ect
thei
r in
volv
emen
t w
ith
SME
s T
his
figu
re i
s ba
sed
on b
anks
’ re
spon
ses
to t
he q
uest
ion
“How
do
prud
entia
l re
gula
tion
s (c
apit
al r
equi
rem
ents
, re
gula
tion
s co
ncer
ning
loa
n cl
assi
fica
tion
, re
gula
tion
s co
ncer
ning
lo
an d
ocum
enta
tion
, et
c.)
affe
ct y
our
invo
lvem
ent
wit
h S
ME
s?”.
We
show
the
per
cent
age
of b
anks
tha
t ch
ose
each
of
the
optio
ns g
iven
as
poss
ible
res
pons
es.
Als
o, w
ithin
pa
rent
hese
s, w
e di
spla
y th
e nu
mbe
r of
ban
ks th
at s
elec
ted
each
opt
ion.
Dat
a co
me
from
the
surv
ey o
f ba
nks
cond
ucte
d el
ectr
onic
ally
by
the
auth
ors.
46%
(5)
18%
(2)
36%
(4)
24%
(19)
22%
(17)
54%
(42)
0%20%
40%
60%
80%
100%
Pos
itive
lyN
egat
ivel
yIn
cons
eque
ntia
l
Percentage of banks
Dev
elop
edD
evel
opin
g
Tot
al R
espo
nses
Dev
elop
ing
Cou
ntri
es: 7
8T
otal
Res
pons
es D
evel
oped
Cou
ntri
es: 1
1
62
Fig
ure
29
Ban
ks’
perc
epti
on o
f w
heth
er t
he e
xist
ence
of
a cr
edit
bur
eau
faci
litat
e SM
E le
ndin
g T
his
figu
re i
s ba
sed
on b
anks
’ re
spon
ses
to t
he q
uest
ion
“Doe
s th
e ex
iste
nce
of a
cre
dit
bure
au i
n yo
ur c
ount
ry f
acil
itat
e S
ME
len
ding
?”.
We
show
the
per
cent
age
of b
anks
tha
t ch
ose
each
of
the
optio
ns g
iven
as
poss
ible
res
pons
es.
Als
o, w
ithi
n pa
rent
hese
s, w
e di
spla
y th
e nu
mbe
r of
ban
ks t
hat
sele
cted
eac
h op
tion.
Dat
a co
me
from
the
sur
vey
of b
anks
co
nduc
ted
elec
tron
ical
ly b
y th
e au
thor
s.
44%
(4)
56%
(5
)
67%
(48
)
33%
(24)
0%20%
40%
60%
80%
100%
Yes
No
Percentage of banks
Dev
elop
edD
evel
opin
g