1

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DO NOT QUOTE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.

2

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.

3

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

4

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

5

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

6

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

7

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

8

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.

9

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.

10

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.

11

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.

12

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

13

(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

14

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

15

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

16

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

17

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.

18

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

19

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

References (to be completed)

Adasme, O., Majnoni, G., and Uribe, M., 2006. Access and Risk: Friends or Foes?:

Lessons from Chile. World Bank Policy Research Working Paper 4003.

Ayyagari, M., Beck, T., and Demirgüç-Kunt, A., 2007. Small and Medium Enterprises

across the Globe. Small Business Economics 29, 415-434.

Beck, T. and Demirgüç-Kunt, A., 2006. Small and Medium-Size Enterprises: Access to

Finance as a Growth Constraint. Journal of Banking and Finance 30, 2931–2943.

Beck, T., Demirgüç-Kunt, A., Laeven, L., and Maksimovic, V., 2006. The Determinants

of Financing Obstacles. Journal of International Money and Finance 25, 932-952.

Beck, T., Demirgüç-Kunt, A., and Maksimovic, V., 2005. Financial and Legal

Constraints to Firm Growth: Does Firm Size Matter? Journal of Finance 60, 137-

177.

Beck, T., Demirgüç-Kunt, A., and Maksimovic, V., 2008. Financing Patterns around the

World: Are Small Firms Different? Journal of Financial Economics.

Forthcoming.

Berger, A.N., Goldberg, L.G., White, L.J., 2001. The Effects of Dynamic Changes in

Bank Competition on the Supply of Small Business Credit. European Finance

Review 5, 115-139.

Beck, T., Klapper, L., and Mendoza, J.C., 2008. The Typology of Partial Credit

Guarantee Funds around the World. World Bank. Mimeo.

Berger, A. N., Kayshap, A. K., and Scalise, J. M., 1995. The Transformation of the U.S.

Banking Industry: What a Long Strange Trip It’s Been. Brookings Papers on

Economic Activity 2, 155-219.

29

Berger, A. N., Miller, N. H., Petersen, M. A., Rajan, R. G., and Stein, J. C., 2005. Does

Function Follow Organizational Form? Evidence from the Lending Practices of

Large and Small Banks. Journal of Financial Economics 76, 237-269.

Berger, A. N., Rosen, R. J., and Udell G. F., 2006. Does Market Size Structure Affect

Competition? The Case of Small Business Lending. Journal of Banking and

Finance, forthcoming.

Berger, A.N., Saunders, A., Scalise, J.M., and Udell, G.F., 1998. The Effects of Bank

Mergers and Acquisitions on Small Business Lending. Journal of Financial

Economics 50, 187-220.

Berger, A. N. and Udell, G. F., 1996. Universal Banking and the Future of Small

Business Lending. In: Saunders, A., Walter I., (Eds.), Financial System Design:

The Case for Universal Banking. Irwin (Richard D), Burr Ridge, IL, 559-627.

Berger, A. N. and Udell, G. F., 2006. A More Complete Conceptual Framework for SME

Finance. Journal of Banking and Finance 30, 2945-2966.

Cole, R. A., Goldberg, L. G., and White, L. J., 2004. Cookie-Cutter versus Character:

The Micro Structure of Small Business Lending by Large and Small Banks.

Journal of Financial and Quantitative Analysis 39, 227-251.

De la Torre, A., Martinez Peria, M.S. and Schmukler, S., 2008. Bank Involvement with

SMEs: Beyond Relationship Lending. World Bank. Mimeo.

DeYoung, Goldberg and White, 1999.

Djankov, S., McLiesh, C., and Shleifer, A., 2007. Private Credit in 129 Countries.

Journal of Financial Economics 84, 299-329.

Goldberg. L.G., and White, 1998.

30

Hallberg, K., 2001. A Market-Oriented Strategy for Small and Medium-Scale

Enterprises. International Finance Corporation Discussion Paper 40.

Haynes, G. W., Ou, C. and Berney, R., 1999. Small Business Borrowing from Large and

Small Banks. In: Williams, J.L., Rhine, A. S.L.W. (Eds.), Business Access to

Capital and Credit, Blanton, A Federal Reserve System Research Conference,

287-327.

Honohan, P., 2008. Partial Credit Guarantees: Principles and Practice. Trinity College.

Mimeo.

IADB, 2004. Unlocking Credit: The Quest for Deep and Stable Lending. The Johns

Hopkins University Press.

IFC, 2007. Benchmarking SME Banking Practices in OECD and Emerging Markets.

Keeton, W., 1995. Multi-Office Bank Lending to Small Businesses: Some New

Evidence. Federal Reserve Bank of Kansas City Economic Review 80, 45-57.

Schiffer, M. and Weder, B., 2001. Firm Size and the Business Environment: Worldwide

Survey Results. International Finance Corporation Discussion Paper 43.

Stephanou, C. and Rodriguez, C., 2008. Bank Financing to Small- and Medium-Sized

Enterprises (SMEs) in Colombia. World Bank Policy Research Working Paper

4481.

Strahan, P. E. and Weston, J., 1996. Small Business Lending and Bank Consolidation: Is

There Cause for Concern? Current Issues in Economics and Finance, Federal

Reserve Bank of New York, 2:1-6.

Strahan, P.E. and Weston, J. 1998.

Whalen, 1995.

31

World Bank, 2007a. Bank Financing to Small and Medium Enterprises: Survey Results

from Argentina and Chile. Mimeo.

World Bank, 2007b. Bank Lending to Small and Medium Enterprises: The Republic of

Serbia. Mimeo.

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