Recent Advances in Environmental and Earth Sciences and Economics
Innovations in the loan process for SME
segment. The findings and experience from the
Czech and Slovak banking sectors.
J. Belás, J. Doležal, R. Hlawiczka
Optimised management of the credit risk represents one of
the most significant opportunity of a better financial
performance for commercial banks.
The opinions of experts as for the banks´ interest in the
SME segment differ substantially. Some authors declare that
the SME financing is a very profitable segment for the
commercial banks due to an intensified competition in other
services to the corporate sector [11], [20]. Others state that
commercial banks are not interested in SME financing because
of the high risk and high supervision cost associated with this
type of lending. [30]
The global financial crisis has caused considerable
concerns as to what the banks' practices will be in relation to
the loan financing of corporate sector. Current signals confirm
that banks in the Czech Republic and Slovakia respond to their
clients by tightened conditions. From the perspective of
companies, very unfavorable situation can be occurred because
of restricts situation of business community in relation to
financing by bank instruments. [18]
The financing of SME segment is an issue of many
discussions in the Czech Republic and Slovakia. Some signals
confirm that banks have surpluses of cash which they cannot
allocate efficiently. Using too harsh criteria for lending could
be one of the reasons of this situation.
In this article, the role and the importance of internal rating
models (IRM) in commercial bank lending process is
examined. At the same time, we examined the opinion of
entrepreneurs on the commercial banks´ approach to their financing
Abstract—Small and medium enterprises (SME) fulfill important
tasks in the economic system, because they create jobs, contribute to
the GDP and engage in other important activities within the socioeconomic system. However, these companies have limited access to
credit sources when compared to large enterprises. The aim of this
paper was to introduce an innovated model of the loan process in
relation to the segment of small and medium-sized enterprises
(SMEs). In this context, the status and importance of open problems
of internal rating models (IRM) of commercial banks in the process
of SME credit risk management was analyzed.
Furthermore, we examined the opinions of experts on the IRM
role in the loan process, the opinions of entrepreneurs on the
commercial banks´ approach to their financing and their level of
knowledge of the criteria used in the loan process.
In the final phase our own innovative methodological proposal for
loan process management for SMEs was introduced. A model of the
loan process has been designed to ensure optimization of credit
decisions, a reasonable rate of effectiveness of lending practices and
a reasonable rate of individual commercial banks approach to the
SME segment. In this process there were used a qualitative and
quantitative research methods. The results of our study have shown
that the accuracy of the IRM in the banking sector is relatively low
and optimal adjustment of the loan process can bring additional bank
interest income.
Keywords—commercial banks, SME credit risk, internal rating
models, loan processing.
I. INTRODUCTION
T
HE issue of credit risk for small and medium-sized
enterprises (SME) is currently the actual theoretical field
of research and practical applications in the process of credit
risk management of commercial banks. [18]
and their level of knowledge of the criteria used in the loan process.
Based on the qualitative and quantitative analysis, we present
proposals to optimize the parameters of the credit policy of
commercial banks. Given the importance of SMEs in the
economic system and their persistent problem in the access to
financial resources, it is important to address this issue.
Authors are thankful to the Internal Grant Agency of FaME TBU No.
005/IGA/FaME/2014: Optimization of parameters of the financial
performance of the commercial bank, for financial support to carry out this
research.
J. B. Author is with Tomas Bata University, Faculty of Management and
Economics, Department of Enterprise Economics, Mostní 5139, 760 01 Zlín,
Czech Republic (phone: +420576032410; e-mail: [email protected])
J. D. Author is with Tomas Bata University, Faculty of Management and
Economics, Department of Enterprise Economics, Mostní 5139, 760 01 Zlín,
Czech Republic (e-mail: [email protected])
R. H. Author is with Tomas Bata University, Faculty of Management and
Economics, Department of Enterprise Economics, Mostní 5139, 760 01 Zlín,
Czech Republic (e-mail: [email protected])
ISBN: 978-1-61804-324-5
II. THEORETICAL BACKGROUND.
Credit risk is the most important and the biggest risk for
commercial banks because of its primary focus, which is the
collection of deposits and lending. It can be defined as the risk
that counterparty fails to meet its obligations, this means that it
will not return borrowed money on time and in full amount.
The height of credit risk is determined by the ability and
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willingness of counterparties to meet their commitments. [28],
[5]
Small and medium sized companies face many
disadvantages in comparison to large companies.
Disadvantages in the area of financing are affected primarily
of lesser availability options to finance especially for
individual entrepreneurs. The main funding source is a selffinancing. The most important borrowed capital is a bank loan
and supplier credit. Relatively higher cost of lower volume of
loan and higher risk of the lender do not make companies the
most popular clients of banks’ institutions. [1], [3], [4] Other
disadvantage in the area represents the fact that small and
medium sized companies do not have a high value of
intangible and tangible fixed assets because of depreciation
which could create the space for continuous reinvestment. [11]
Companies in SMEs segment are smaller, have higher
information opacity, carry greater risk [22], and they are more
dependent on a commercial credit and a bank loan. [14]
Internal models for credit risk assessment of the client
represent significant and an important part of credit risk
management in the commercial bank. These models showed of
very dynamic development and have become an essential part
of the assessment of credit risk in banks in the last period.
By using credit models, banks are now willing to provide
more loans to SMEs due to easier default measurement of the
borrowers. [9]
Internal rating systems are used to quantify the credit risk of
individual borrowers. The credit rating score is assigned to
individual borrowers by using different methods and indicates
the level of credit quality. Validation of the rating system is
closely linked with the validation of other risk parameters that
are derived from the rating provisions of Internal Rating Based
Approach of Basel II and which largely determine the amount
of required equity. The aim of internal rating models is to
estimate risk parameters such as Probability of Default (PD),
Loss Given Default (LGD), Exposure at Default (EAD), and
Effective Maturity (M) which are based on the quantitative and
qualitative variables. [13]
Internal rating of the client is assigned by the bank
according to its risk characteristics and risk characteristics of
the contract which is based on specific rating criteria from
which estimated PDs are derived. As part of the credit
approval process, each borrower is assigned to a rating class
where PD is assigned to individual class by the bank. The
rating evaluation of the client determines its access to credit
sources and their cost.
The major factors for SMEs default are classified according
to high indebtedness, low profit, and low liquidity. [17]
Profitability and bank relationship with a borrower has a
inverse relationship for predicting the probability of default.
The longer the relationship with bank the lowers the
probability of default. Firm size and number of employees
have inverse relationship with the probability of default. [22]
In this context Psillaki, Tsolas, and Margaritis state that firm
performance is negatively related with default. By using a
ISBN: 978-1-61804-324-5
DEA (Data Evolvement Analysis) they have also shown that
firm efficiency has enough explanatory power to perform
better than financial indicators. They have found that more
efficient firms are less likely to fail. A 0.1 unit increase in the
inefficiency score increases the probability of default on
average by about 2 percent. They also find that a one
percentage point fall in profitability increases the probability
of default by about 1 percent. Similarly, a one percentage point
fall in intangible assets is expected to increase the probability
of default by about 0.25 percent. They also find that solvency
ratio is a poor predictor of a company´s default. [29] The one
interesting thing is that a lot of SMEs has tendency to extract
money from the loan for their personal use, and the higher the
number of money extraction for personal use the higher is the
possibility of default. [22]
Agostino, Gagliardi and Trivieri [1] discovered that bank
concentration seems to positively (and significantly) affect
SMEs default risk when credit relationships are very
concentrated; that is when firms borrow heavily from their
main bank and have few credit relationships with other
intermediaries. A possible interpretation being that, as debt
from the main bank increases and firms do not resort to
multiple banking connection (in the attempt to induce
competition among lenders(, entrepreneurs might remain
locked into lending relationships and so, become exposed to
the potential negative effects of concentrated markets. The
results suggest that a detrimental effect of bank market
structure on firm default probability would emerge when
lending relationships are highly concentrated, and it would be
stronger the longer the duration of bank-firm relations.
In the theory, there are a lot of various approaches to credit
risk management of SMEs.
The relationship between the bank and the client is
determined by the credit techniques which can be
characterized as the relationship lending or the transactional
lending. The lending relationship is primarily based on a soft
information (soft information: personal character, quality of
management in the company, business strategy, ownership
structure, etc.), that the bank acquires in direct contact with the
client, in the local territory and on the base of the long-term
observations of the company’s performance. The transactional
lending is based on hard data (the quantitative data) such as:
return on equity, profitability, operating cash flow, interest
coverage, liquidity, etc. [25] Ono and Uesugi [26] indicate that
the relationship lending is common mainly in lending to small
businesses, because small businesses typically rely on bank
loans which represent a very important part of their financial
needs, but also tend to be informational opaque. In this context
Behr and Guttler state that relationship lending is more
convenient to reduce the asymmetric information problem. [4]
Ono and Uesugi [26] highlight the importance of the collateral,
which is a common tool in the credit process between banks
and small companies around the world. In the context of
information asymmetry between banks and the credit applicant
the collateral is seen as an option for reducing the problem of
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survey of McKinsey & Company state that the debt of SMEs is
considered as the most important quantitative factor of internal
rating; 50% of the banks give equal importance to indicators
such as liquidity and profitability. From the wide range of
possible quality factors around 50% of medium-sized and
large banks give high or very high priority to the quality of
management of SMEs and then there are other factors such as:
the market situation of SMEs and its legal form. According to
the document, qualitative factors have a greater influence on
the rating in the case of larger SMEs and larger loans. In the
case of start-up companies, the weight of these factors
represents 60% on the overall rating. In the case of companies
with a sufficiently long business history (minimum 2 years) the
weight of qualitative indicators is significantly lower and
represents only 20-30% of the overall rating.
improper selection and moral hazard.
According to internal documents of the largest Slovak bank,
within the rating process a following rule is applied: the
smaller the company, the more important soft information is.
Personality characteristics of the owner of the company are
very important in relation to the financial performance of the
company, which determines the level of credit risk in the
SMEs segment. [6] Witzany [33] states that accounting data
have low explanatory power in relation to SMEs and that an
expert system is very important in the rating process. In this
context, Altman, Sabato and Wilson reported that the use of
non-financial variables of function of default annunciators
significantly improves the quality (predictive power) of rating
models. [2]
According to Beck, Demirguc-Kunt and Pería [2] who
compared credit involvement of large international banks and
local banks in the SME segment, soft information is evaluated
by foreign banks as the less important one compared to
domestic banks where they use more decentralized processes
within credit approval and also work more with risk
management. According to authors, foreign banks are placing
more importance on the collateralization of loans and less
importance on soft information.
The age of owner, the inquiry frequency of owners´ credit
information for post-loan risk management and pro-loan
approval purpose, and the proportion of overdue loans are the
extreme significant variables which are valuable indicators in
default risk estimate model. [32]
In this context Canton, Grilo, Monteagudo, and Zwan [10]
find that the youngest and smallest SMEs have the worst
perception of access to bank loans. Better accounting
information, firm size and firm age found a positive
relationship for getting bank loan.
In Fig. 1 is shown a diagram of a typical loan process,
which is used in the Czech and Slovak commercial banking.
III. OBJECTIVES, METHODOLOGY AND DATA
The aim of this article was to present an innovative model of
lending process toward the segment of small and medium sized
companies. In this context, the status, importance and
shortcomings of internal rating models of commercial banks in
relation to credit risk measurements have been analyzed. At
the same time, opinions of entrepreneurs in selected regions of
the Czech Republic and Slovakia were examined.
Our own methodological proposal for the management of
the lending process have been presented.
Criticism of IRM is focused on various aspects of their
operations. In practice, the perfect rating systems do not exist
[13]; their explanatory power in relation to the assessment of
the quality of the client and its risk profile is significantly
limited. [15]
Quality and relevance ability of internal rating systems are
different. [12] Current models to measure credit risk are not
perfect and do not give quite reliable results. In this context,
Kuběnka, Králová indicate that the inaccuracy of the model in
predicting of financial distress is 27.5% and the success rate to
classify a financially healthy company to the group of
prosperous ones represents 89.2%. [21]
According to the results of our research [7] the accuracy and
quality of IRM has been experimentally verified. This model is
used by a significant Czech bank and it does not have
sufficient quality because it evaluates an excellent company as
a negative one and in the same time, it evaluates various
negative changes in the financial performance of the company
by the same rating. The model is less sensitive to significant
changes of important financial indicators that determine the
loan repayment which is especially evident when assessing the
profitability of different variants, respectively loss-making
firms.
The findings obtained from the sources have inspired us to
formulate the following four scientific hypotheses:
H1: IRM have a dominant position in the process of
granting the loan to the client. If the result of the client’s rating
is negative the bank does not give him a credit loan.
H2: IRM have a limited accuracy. According to the credit
Fig. 1 Diagram of a typical loan process in relation to SMEs
In the document of the European Committee [16], 75% of
the total number of large and medium-sized banks in the
ISBN: 978-1-61804-324-5
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specialists’ evaluation the average value of the accuracy of the
IRM in the Czech banking sector is below 80%.
H3: Entrepreneurs of the SME segment in the Czech
Republic and Slovakia do not assess the commercial banks
approach to their financing positively. Less than 50% of them
think banks accept their needs and behave appropriately
towards them.
H4: The level of knowledge of the lending criteria by Czech
and Slovak entrepreneurs is low. Less than 60% of them stated
they know the lending criteria of commercial banks.
H5: Optimization of the process of granting the loan leads to
a higher credit acceptance of SME by at least 20%.
In our research the process was as follows.
Through a structured interviews there was investigated the
role of IRM in the credit policy of commercial banks and what
is their accuracy degree. The data was obtained from the bank
managers and credit specialists. As a part of this research there
was contacted 10 banking executives and credit specialists
working in the Czech corporate banking sector, and 10
managers and specialists who work in Slovakian banks. In the
Czech Republic there were members of staff from the three
largest banks who have participated in this research, and in
Slovakia there were workers of the 3 medium-sized and of the
7 big banks who have participated in this research.
The samples of the respondents could be considered as
representative for the following reasons: employees from the
leading commercial banks in the Czech Republic and Slovakia
have participated in this research, banks apply a unified credit
policy, so if a representative of the bank has indicated a certain
fact that applies throughout the entire bank, which eliminates
the need to have a large number of respondents. In both
countries these banks have a market share for loans greater
than 70%. An important factor is also the fact that banks
consider their IRM as a business confidentiality, which they do
not inform the public about, so any quantitative search with a
large sample of respondents is excluded.
Research on basic determinant of the financial stability of
SMEs was carried out in 2013 in selected regions of the Czech
Republic and Slovakia through a questionnaire survey. In the
Zlin region data from 180 SME was collected and in the Zilina
region data from 164 SME was obtained in total. Data for
companies was provided by their owners.
Zlin region has an area of 3.964 square km, has an about
600.000 inhabitants, GDP per capita is around 11.720 EUR;
unemployment in 2012 was about 8%.
Zilina region has an area of 6.800 square km with total
population of 700.000 and the population density of 102
inhabitants per square kilometer. Unemployment in 2011 was
raised to 11.91%. GDP per capita in the Zilina region was
10.794 EUR in 2011.
In our survey in the Zlin region (CR) was the largest share
of SME, which undertook the business activities (35%),
followed by manufacturing firms (29%), construction
companies (12%), transport companies (4%) and agricultural
holdings (3%). Rest was presented by firms, which undertook
ISBN: 978-1-61804-324-5
in other sectors.
In Zilina region (SR), the structure of companies was as
follows: in manufacturing and production was involved 17%,
in trade activities 21%, 17% were construction companies,
transport enterprises 6%, only 1% was presented with
agricultural holdings and the largest share was formed by
companies, which undertook in other sectors (38%).
The associations in contingency tables were analyzed by
Pearson statistics for count data. Calculations have been
performed in statistical packages XL Statistics and R. There
were also used the tools of descriptive statistics: percentages,
averages and indexes.
In the process of creation of the upgraded model of the loan
process, the loan documents of three commercial banks have
been examined and two IRMs which were used by commercial
banks in the Czech Republic have been analyzed.
IV. RESULTS AND DISCUSSION
The results of the survey on status and importance of IRM
in the credit policy of the Czech and Slovak banks are listed in
Table 1. These results were found by the structured interviews
method.
TABLE I
THE IMPORTANCE OF IRM USED IN THE PROCESS OF GRANTING A LOAN
What importance the results of the rating
of corporate client have in the process of
granting a loan?
1. dominant – when a client fails rating,
the loan is not granted in any case.
2. substantial – if the client fails rating,
the possibility of granting a loan
is very limited
3. important – rating of the client is
considered to be an important part
of the loan process, but the quality
of security equipment or quality
of relationships with the client,
or other factors may change
the rating results.
4. have no relevance
5. other evaluation
CR
SR
0
8
Index
CR/
SR
0.000
8
2
4.000
2
0
-
0
0
-
The majority of the bank managers and loan specialists in
Slovakia have confirmed that the rating has a dominant
position in the credit process, because if the client fails rating,
the loan is not provided by this bank in any case.
Our study suggests that the Czech banks probably apply a
different approach (which was also confirmed by the value of
the relevant index), because the vast majority of the
respondents stated that the rating outcome has substantial
importance in the process of granting a loan. As a part of
structured interviews there was emerged that the majority of
the Czech banks realizes the importance of a correct
perception of economic indicators of companies and also some
space for improvement in their own staffing, on which they
want to focus in their future activities. These banks consider
improving the quality of the knowledge of an own employees
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in the field of financial analysis not only as an important
prerequisite for the proper credit evaluation of the client, but
also as a potential growth in loan transactions.
The Hypothesis 1 was confirmed in Slovakia and it was
partially established in the Czech Republic.
In Table 2 are presented the results of research in the
context of the accuracy of the IRM.
were perceived by entrepreneurs in the Czech Republic and
Slovakia were as follows: market, financial and personnel
risks. Market risk was identified as a key risk by the largest
number of entrepreneurs, that means 79.44% of them in the
Czech Republic and 80.49% in Slovakia. Average value of
market risk which was identified by entrepreneurs in the Czech
Republic was 56.00% and 51.30% in Slovakia. Amount of
adjusted average value (average of whole data set) in the
Czech Republic was 44.49% and 41.29% in Slovakia. Average
performance decrease is represented by 15.80% in the Czech
Republic (weighted average of upper values of individual
intervals). Average performance decrease was 18.78% in
Slovakia.
Table 4 then contains the results of the survey as for the
entrepreneurs´ knowledge of lending criteria of banks.
TABLE II
THE ACCURACY OF THE IRM USED
What is the accuracy of the internal models at
your bank?
1. 81% and more
2. from 70 to 80%
3. from 50 to 69%
4. less than 50%
5. I do not know
CR
SR
4
0
0
0
6
7
3
0
0
0
Index
CR/SR
0.571
0.000
-
TABLE IV
THE LEVEL OF KNOWLEDGE OF THE BANKS´ LENDING CRITERIA
In Slovakia most of our respondents agreed that these
models were very accurate, because most of them thought that
their accuracy was higher than 80%. In the Czech Republic 4
respondents have stated that the accuracy of these models was
higher than 80%, however most of them could not answer on
the corresponding question.
The Hypothesis 2 was not confirmed.
Table 3 presents the research results in the field of the
commercial banks approach to SME financing.
Do you know the criteria used to
rate clients in the lending
process of banks?
1. Yes
3. Banks behave unhelpfully
4. Banks use too harsh criteria
for lending
5. I cannot judge
* the share of the first two answers (in %)
CR
SR
8
5
70/
43*
16
47
33/
23*
23
61
0.1336
0.0271
39
42
0.3898
p-value
0.0488
0.4122
0.1868
Hypothesis 4 was confirmed. The level of knowledge of the
banks´ criteria in lending process was lower than 60% among
the surveyed entrepreneurs.
During the structured interviews with experts we also
confirmed our assumption that IRM represent an important
part of the loan process and are thus a trade secret of
commercial banks.
In this context, for example Behr and Güttler [4] see the
solution on companies’ part that understood banks’ approach
within the evaluation of creditworthiness and also they were
able to evaluate their expected probability of default (PD)
using rating model. This fact could help firms to understand
their position from the bank’s position. Also this fact would
lead to provide necessary document about themselves for
better assessment of their creditworthiness and also it would
lead to the possibility of further negotiations between the bank
and the company about credit conditions. According to author,
knowledge of own PD also allows to increase transparency in
credit process. As well as it allows potential use for searching
of external funding sources. If SMEs have knowledge about
their creditworthiness, they may affect management decisions
in favor of new sources of external funding due to the
expanding range of financing options.
The testing of Hypothesis 5 was realised by qualitative
research.
IRMs which are used by commercial banks have a variety of
limits. Tőzsér [31] states that in the context of world financial
and economic crisis, criticism of risk management models
continually and more frequently heard in academic circles.
pvalue
0.4965
0.0001
The Hypothesis 3 was confirmed. Only 43% of
entrepreneurs in the Czech Republic and 23% of entrepreneurs
in Slovakia stated banks accept their needs or behave
appropriately. We also found statistically significant
differences between the entrepreneurs of the Zlin and Zilina
regions in some answers. The entrepreneurs from the Zlin
region declared more often than their counterparts from the
Zilina region that banks behave appropriately and less often
that banks use too harsh criteria for lending.
Financial crisis and gradual recovery of economies in the
European Economic Community brought deterioration of the
business environment.
In our research [8] the most important business risks which
ISBN: 978-1-61804-324-5
SR
79/
5/
44* 34*
2. No
26
29
3. I have some idea
75
80
* the share of the first two answers (in %)
TABLE III
THE COMMERCIAL BANKS APPROACH TO SME FINANCING
How do you assess the commercial
banks approach to SME financing?
1. Banks accept our needs and
provide full assistance
2. Banks behave appropriately
CR
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Stable operation of financial systems represents, if not
impossible, but at least a very complex matter. This is due to
the imperfection of the used models of risk measurement,
which give very unreliable results. Today, the vastly increased
application of the statistical models to measure and predict the
risk ironically, even more contributes to the growth of
endogenous risk of the system. They promote pro-cyclical
changes in financial leverage of banks, thereby contributing to
pro-cyclical tendencies of the entire financial system. [23]
Credit risk management models represent an effort of
accurately defined complex of economic processes through
mathematical respectively statistical models. These models
despite their highly sophisticated approaches fail and cannot
accurately show the complexity of the economic system, which
is determined by significant non-quantifiable variables
(attitudes, expectations, preferences of individual economic
entities, etc.). [5]
Mitchell, Van Roy [24] reported that 20% of companies that
have been evaluated by different models have vastly different
ratings. One model assessed them as bad clients, while another
model assessed them as good clients. The results of our
research have confirmed that the model failed to properly
assess the financial health of the company. When the
distinctive character of the model was compared with the real
data about the default of companies, it was found out that our
model has badly judged more than 20% of companies in the
segment of SME. [7]
Data collected from the Credit management research centre
of the University of Leeds containing all financial and nonfinancial data show Auroc kurve 0.74 for micro firms, 0.77 for
small firms and 0.76 for medium firms. [19]
Based on the qualitative analysis there was confirmed the
validity of the Hypothesis 5. This finding allows us to assume
that the optimal incorporation of IRM to the credit policy of
commercial banks leads to a higher credit acceptances of
SMEs by at least 20%.
The facts given, point to the need for appropriate use of
IRM in the lending process of commercial banks as the bank
can lose a significant amount of revenue because of not
providing a loan to a good client (error of the 1st type).
While in case of an error of the second type, the bank may
compensate the revenue dropout by monetization of securing
means, in the case of an error of the first type is a nonrecoverable loss of income.
In this context, it is necessary to define a comprehensive
approach to managing the credit risk of the client, which lies in
the fact that there is created an approach which will ensure fair
and effective assessment of the possibilities, abilities and tastes
of the client to return borrowed money to the bank in the
agreed mode.
Methodological procedure of the proposed loan process is
shown in Fig. 2.
ISBN: 978-1-61804-324-5
Fig. 2 Methodical procedure of the loan process
Our theoretical contribution consists in the fact that there
was proposed to incorporate a Negotiation procedure I and
Negotiation procedure II to a standard loan process.
In the case of a negative outcome of the preliminary rating
of the client, it was proposed by us to apply a Negotiation
procedure I, within which the bank should obtain information
to verify, respectively modify the results of the preliminary
assessment. If this procedure goes with a negative result, the
credit process will be terminated. If the result is positive, the
bank continues with the lending process. The procedure
proposed by us should allow the removal, respectively making
the rating process softer in the context of defined limits and
limitations of quantitative rating and incorporation of positive
personality characteristics of the company owners, respectively
positive historical experience with the firm before the lending
process.
In the case of a negative result of the analysis, it is
proposed to hold Negotiation procedure II. A financial
analysis should be seen also as one of the processes that can
help to a good quality credit decision, however the results are
also not one hundred percent guaranteed (successful
development of the company in the past does not necessarily
mean a successful future). For example, in this context,
Pavelková, Knápková [27] define a number of weaknesses in
the financial analysis. In the case of negative, respectively
inconclusive results, the bank’s analyst must consider the
significant determinants of the financial analysis in the context
of credit risk.
The process of the financial analysis, despite its primary
exact character, requires a certain amount of imagination,
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[7]
professional knowledge and experience of this process from a
credit analyst because for example, same numbers can lead to
different results or indicators of profitability of the company
may be subjectively biased by the massive "tax optimization."
Paradoxically, if the business grows too quickly, also the risk
of growth management grows too. The company does not
handle the enormous personnel, managerial, capacity,
logistical growth in relation to management of customers, or in
the area of complaints.
There are still many factors that need to be considered in an
assessment of the future financial health of the company.
[8]
[9]
[10]
[11]
[12]
V. CONCLUSION
The aim of this article is to introduce an upgraded model of
the loan process in relation to the segment of small and
medium-sized enterprises, which would respond more
appropriately to their credit requirements and would assess
their credit worthiness more correctly.
Theoretical analysis and practical verification of the quality
of internal rating models created by us has shown that these
models have a limited quality and a number of outstanding
problems.
Rating models are important for the bank, but they should
not have a function of the credit machine.
For that reason there was introduced an innovative model
of the credit process in the SME segment, which should bring
the optimization of credit decisions, a reasonable level of
efficiency of credit processes through quantification and
optimization of operating costs in the context of an individual
approach to SMEs. Our collective assumes that at least 20% of
the companies are incorrectly graded by the IRM model, which
means that with the proper use of the methodology for the
credit process proposed by us, the bank may provide a
significant amount of safe loans.
In the next phase of our research, our team will focus on the
quantification of the effects of our model on the financial
performance of commercial banks. We are planning to conduct
quantitative research dedicated above all to find out how many
non default clients were refused in the lending process due to
harsh criteria currently used by commercial banks.
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
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