The document is a research paper that analyzes ways to reduce commercial bank loan interest rates in Mongolia. It uses breakeven analysis and short rate modeling with Monte Carlo simulation. The analysis finds that loan interest rates at the breakeven point have decreased over time from 2009 to 2011 for the major banks. This suggests lower expenses have allowed rates to fall. Simulation also shows interest rate stabilization decreasing slowly over time. The researchers conclude there is potential to further reduce rates through continued growth in assets relative to expenses and cuts in liability expenses.

1. Empirical Studies
MUST – CSMS Student Scientific Confernce
Possibility to reduce loan interest rate of commercial banks
Extended abstract
Batkhishig Badarch
Institute of Finance and Economics
Phone: 99726540
E-mail: d_hishegee@yahoo.com
Nomun Bukh-Ochir
Institute of Finance and Economics
Phone: 976-99269950
E-mail: b_nomun19@yahoo.com
Tserennadmid Gantumur
Institute of Finance and Economics
Phone: 976-99224550
E-mail: tserennadmidg@yahoo.com
Abstract
In this research we analysed data of five leading commercial banks of Mongolia and try to find
out ways to reduce loan interest rates of them. This work focused on Mongolian commercial
banks. In conclusion of our study, we find out possibility to reduce loan interest rate ant its
stability by using Breakeven analysis, Monte Carlo simulation method and short rate model.
Loan interest rate is decreasing slowly over time.
Key words: Breakeven point, Monte-Carlo simulation, Short rate model
JEL Classification: G12; G21
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2. Empirical Studies
MUST – CSMS Student Scientific Confernce
1. Introduction
Loan interest rate in my country is too high to discourage investment decisions
and run business with financial support, that is why, the study related to loan
interest is controversial. Our objective is to seek a possibility to make loan
interest rate lower. We have 15 commercial banks in Mongolia four of which
has greater share than other opponents in market. Commercial banks determine
their interest rates by imitating their opponent’s decision on interest rates and
by method based on expense. We have done our research with expense based
method and breakeven point analysis.
In economics we use breakeven point analysis to point the price in which an
expenses and income are equal. Breakeven point is the minimum limit of price
to operate of a firm. This means that the firm will gain no profit and no loss if
the price is lower than the price calculated at breakeven point.
We used the breakeven point analysis in banking sectors to determine possible
minimum interest rate of interest sensitive liabilities. Then we assumed that the
interest rate is stochastic process as in the short rate model and analyzed its
stabilization with Monte Carlo simulation.
Our research paper includes following steps:
i.
ii.
iii.
iv.
v.
Introduce studies explaining equilibrium of interest rate.
Formulation of expense based model
Formulation of short rate model
Doing research and analysis with previous models.
Conclusion
2. Model
Breakeven point analysis
Total income of commercial bank is determined as a sum of interest income, exchange rate
and revaluation income, income from charge of product and service, and non-operating
income as follows.
(3.1.1)
Үүнд:
– Total income
– Interest income
– Exchange rate and revaluation income
– Product and service income
– Non-operating income
Exchange rate and revaluation income, income from charge of product and service, and
non-operating income are not dependent and not sensitive from interest rate, so they can be
named as non-interest income. The equation is written as follows:
(3.1.2)
– Non-interest income
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3. Empirical Studies
MUST – CSMS Student Scientific Confernce
We can figure interest income as follows:
(3.1.3)
– Return to interest sensitive asset
– Interest sensitive assets
Thus we can rewrite total income using definition of non-interest income and interest
income in following form:
(3.1.4)
Total expenses of commercial bank are determined as a sum of interest expenses, exchange
rate and revaluation net expenses, expenses related to personnel, allowance for impairment
losses, administration expenses and non-operating expenses.
(3.2.1)
– Total expenses
– Interest expenses
– Exchange rate and revaluation net expenses
– Allowance for impairment losses
– Expenses related to personnel
– Administration expenses
– Non-operating expenses
Interest expenses can be formed like interest income.
(3.2.2)
– Non-interest expenses
– Interest sensitive liability
By integrating non-interest incomes and then adding the integration to the total income
formulation, we can have following equation.
(3.2.3)
– Non-interest expenses
Commercial bank can derive profit when return of
commercial bank locates α share of its
in
. If
in
. In the BEP, return of
will be as follows:
exceeds
. Assume that a
, the bank locates all its
(3.3.1)
Intersection of total income curve and total expenses curve is
. Ratio of
and
at the
is the point that the bank has no gain or no loss from its net profit of interest
sensitive assets.
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4. Empirical Studies
MUST – CSMS Student Scientific Confernce
The bank locates share of its
in loan, share of interest income is loan interest
income. With those assumptions, the loan interest rate in
is as follows:
(
)
(3.3.2)
This BEP point is either expense based method of determining loan interest rate. Equation
of interest rate dynamic change is as follows:
(
(
(
)
))
(3.3.3)
We can find two ways to reduce interest rates from this dynamic equation.
i.
Greater growth of assets than a net growth of expenses.
ii.
By cutting expenses of liabilities.
Short rate model
We assume that interest rate dynamic change is stochastic process. To examine this
assumption we consider interest rate model as follows:
( )
( ))
(
( )
(3.4.1)
– Stabilizing parameter
– Location parameter
– Scale parameter
– Return of securities and exchanges
Interest rate is formed by as follows:
( )
(
)
(
)
√
(
)
(
)
(3.4.2)
We will analyze stability with equation (3.4.3) by exponentiation of this stochastic process
with Monte Carlo simulation method.
( )
[
{([ [ (
])
+
)]
√
]]
[[
[
]
(
[ ( ̅ )(
[
])]
))}
*(
(3.4.3)
3. Result
According to their statistical data, the leading commercial banks of Mongolia have
beneficial operation. Please see this result in the Figure 1.
Figure 1 Beneficial operation of Commercial banks
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5. Empirical Studies
MUST – CSMS Student Scientific Confernce
2009
2010
2011
Billion tugrugs
50.00
45.00
40.00
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
Khanbank
TDB
Golomt bank
XacBank
Source: Authors’ calculation
In the Figure –2 we can see ratio of total loan and non–performing loan. This ratio is
decreasing over time; which means risk of interest sensitive assets is lower than that in the
past.
Figure 2 Non-performing loan ratio
2009
2010
2011
9.0%
8.0%
7.0%
6.0%
5.0%
4.0%
3.0%
2.0%
1.0%
0.0%
Khanbank
TDB
Golomt bank
XacBank
Source: Authors’ calculation
In the Figure –3 we show loan interest rate at breakeven point. From this graph we can say
that interest rate that commercial banks gain no profit and have no loss is decreasing, so
that there is possibility to reduce interest rate. This also means that they have reduced their
expenses related to their increased assets.
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6. Empirical Studies
MUST – CSMS Student Scientific Confernce
Figure 3 Loan interest rate at BEP
2009
2010
2011
16.0%
14.0%
12.0%
10.0%
8.0%
6.0%
4.0%
2.0%
0.0%
Khnbank
TDB
Golomt bank
XacBank
Source: Authors’ calculation
With Monte Carlo simulation, we analyzed interest rate stabilization as follows:
Figure 4 Loan interest rate dynamics stabilization
r_2009
r_2010
r_2011
1.80%
1.60%
1.40%
1.20%
1.00%
0.80%
0.60%
0.40%
0.20%
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
35
37
39
41
43
45
47
49
51
53
55
57
59
61
63
65
67
69
71
73
75
77
79
81
83
85
87
89
91
93
95
97
99
0.00%
Source: Authors’ calculation
In the figure 4, we can’t illustrate stabilization accurately because of stochastic process
influence that is why we exponentiated this process to eliminate effect of random
component. In the following figure, loan interest rate of commercial banks will go down
slower but won’t stabilize.
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7. Empirical Studies
MUST – CSMS Student Scientific Confernce
Figure 5 Loan interest rate dynamics stabilization (random process adjusted)
r_2009
r_2010
r_2011
1.80%
1.60%
1.40%
1.20%
1.00%
0.80%
0.60%
0.40%
0.20%
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
35
37
39
41
43
45
47
49
51
53
55
57
59
61
63
65
67
69
71
73
75
77
79
81
83
85
87
89
91
93
95
97
99
0.00%
Source: Authors’ calculation
4. Conclusion
To conclude with our study, we find out possibility to build a model to express bank loan
interest rate with breakeven point analysis and short rate model. We show that we can use
Breakeven analysis in equality of total expense of interest sensitive assets and total income
of interest sensitive liabilities.
There are two workable solutions to reduce loan interest rate: by cutting expenses of
liabilities and greater growth of assets than a growth of expenses.
In Mongolia’s banking sector improvement of commercial bank activity related to
economic scale extension, reduction in risk and improvement of financial indication might
cause reduction in loan interest rate. This reduction will continue slowly.
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8. Empirical Studies
MUST – CSMS Student Scientific Confernce
5. Bibliography
Bank of Mongolia. (2012, February 20). Financial Stability. Retrieved from Central Bank
of Mongolia: http://www.mongolbank.mn
Boldbaatar.D. (2006). Interest rate spread. Ulaanbaatr: Mongolbank.
Duulal.D. (2006). Nominal and real loan interest rate. Ulaanbaatar: Mongolbank.
Gan-Ochir.D. (2006). Study of interest rate spread in Mongolian commercial banks.
Ulaanbaatar: Mongolbank.
Golomt bank. (2012, January 1). About Golomt Bank. Retrieved from Golomt bank:
http://www.golomtbank.com
Holland, R. (1998). Assistant extension specialist, Break even point analysis. Agriculture
extension center, University of Tennessee.
http://www.puc-rio.br. (2004). Monte Carlo Simulation of Stochastic Process.
Khan
Bank. (2011, November
http://www.khanbank.com
11).
About
Us.
Retrieved
from
KhanBank:
Trade & Development Bank of Mongolia. (2011, December 10). Annual Report. Retrieved
from Trade & Development Bank: http://www.tdbm.mn
XacBank. (2012, January 5). About XacBank. Retrieved from XacBank Right Bank:
http://www.xacbank.mn
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