Transcript Slide 1

General background
Before the civil war erupted in 1974

Lebanon was the Middle East’s banking
center.

The strict secrecy law and the free
exchange system attracted money
from all Arab countries
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During the civil war period

The picture became totally different.

“In the 1980s banks grew more reliant on
lending to government, either directly or
via three month treasury bills”
(EIU Country Profile 1997-1998, p. 25).

Following the civil war

Lebanon has been a dollarized economy
(Khoury, 1999, p. 26).

65.6 per cent of deposits and 89.2 per
cent of credits are dominated in US dollars
(Banque Audi, 1st Quarter Economic
Report, 1999, p. 5).
The days of banks’ healthy profits and
easy money are coming to an end

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The Lebanese government succeeded in
saving interest payments by switching
from domestic to international borrowing.
A decline in the Treasury bill yields and a
decrease in the banks’ profits manifested
this success.
Pressure is mounting on the smaller
banks and acquisitions are picking
up.
To minimize the risk facing the banking industry
in Lebanon, the Central Bank has been working
hard to promote merging between banks by
offering:
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low cost loans
two-years tax holiday
Exemptions from employment legislation to
acquirers for five years.
“In 1997 the Central Bank also imposed new
capital requirements to encourage
undercapitalized banks to merge”
(EIU 1998-1999 Country Profile, p. 21).
Table I
shows that 19 banks have been taken over
by larger ones in the period 1993-1999.
Need for the study

During the post-war period 1992-98 Lebanese
commercial banks enjoyed making huge profits by
offering short-term deposits and reinvesting the
proceeds in high-yielding government Treasury bills.

Charles Olivier (1999) reports that a significant chunk of
Lebanese commercial banks’ profits between 55 and 70
per cent has been made by taking 45 days deposits
(offering 12 per cent) and reinvesting the proceeds in
government treasury bills (where two-year paper yields
16 per cent).
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There is, however, a darker side to this rosy
picture

The short maturity of the deposits has
prevented commercial banks from lending to
firms on medium or long term basis.
In addition to this, the emphasis of the
Lebanese government on borrowing from
abroad has caused the Lebanese interest rates
to go down
 (Euromoney, June 1999, p. 280).

, “In late 1995, however, the steam began to
run out of the construction boom”
 (EIU Country Profile 1998-99, p. 13).

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Internet waves have arrived on Lebanese
shores and the transactions moved up from
ATM to Pay-by-the-Phone to E-banking.

Customers at few-alpha group banks (banks
whose deposits are over US $500 million)
such as Saradar, HSBC Bank Middle East,
Credit Libanais and Banque National de
Paris, Intercontinentale (BNPI) can sit at
home and enjoy browsing few banking
services .
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Convenience, customer satisfaction and
low cost are the name of the game in this
information age. The big banks are able to
play the game. They are customer driven
and working hard on satisfying customers’
needs and retaining customers.

Knowing all of these, it becomes
imperative to ask what will happen to the
smaller banks?
“The general sentiment among analysts is
that Lebanon’s bank merge process is on
track” (EIU Country Report, 2nd Quarter
1999, p. 27).
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If Lebanon plans on having big
competitive banks it can expands
regionally into countries having
underdeveloped banking systems and
tight control such as Iraq, Syria, Jordan
and Palestine. Today, “Together with
Bahrain, Lebanon is considered a regional
leader in derivatives trading”
(EIU Country Profile 1997-98, p. 29).
Purpose of the study

There are 59 commercial banks in Lebanon
which make their financial statement available to
the public. These financial statements are
published in an industry publication, Bank Data:
328 Financial Statements Analyzed .

52 financial ratios are calculated for each of the
banks, and the banks are ranked based on their
performance for each ratio.
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For decision makers trying to
compare banks, analyzing 52
financial ratios may be too rough
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It would seem more appropriate to
look at a smaller number of ratios
that explain nearly as much as the 52
ratios do.
Analysis
Factor analysis is used to find seven financial
ratios that adequately explain the differences in
bank performance.
 Cluster analysis is then used to separate
banks into four different performance clusters.
 Multidiscriminant analysis is then used to
quantitatively examine the differences in
performance between these clusters.
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This research is organized as follows:

A review of the literature is provided in
the next section
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The data are described in the following
section.
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The application of factor analysis as data
reduction technique is shown in the
section after this.
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The application of multidiscriminant
analysis to examine the differences
between clusters is shown in the following
section.

The predictive ability of the model is
shown in the penultimate section while
the concluding remarks for merger
between banks are presented in the final
section
Review of literature
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Bridging the gap between advanced
multivariate statistical analysis and financial
ratio analysis for studying industry
characteristics has been growing steadily in
the financial literature, e.g. Charbaji and Ali
(1995), Altman (1968), Collins and Green
(1982), Deakin (1972), bond ratings, e.g.
Beaver (1966) and mergers and take-over,
e.g. Stevens (1973), Pinches et al. (1973).
The data

The data used in this study are 52
different financial ratios that have been
calculated for 59 commercial banks in
Lebanon for the fiscal year 1999.
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All of these data were taken from the
publication, Bank Data: 328 Financial
Statements Analyzed, by Fredi Baz (1996).
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In view of the sensitivity of the results to
the assumption of normality in the
observed sample, it was decided to use
the common log transformation of the
financial ratios.
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Because of having missing observations,
nine banks were deleted from analysis by
the use of SPSS.
Table II shows the skewness of the seven
financial ratios that were selected by
factor analysis Skewness of two financial
ratios (X15 and X44) are shown before
and after log transformation in Table II.
Skewness of significant financial
ratios
A Graphical Representation of A Financial Ratio
Before Transformation (Highly Skewed)
Frequency
30
20
10
Mean =7.07
Std. Dev. =12.08
N =49
0
0.00
10.00
20.00
30.00
x09
40.00
50.00
A Graphical Representation of A Financial Ratio
AfterTransformation (Almost Normal)
10
Frequency
8
6
4
2
Mean =0.40
Std. Dev. =0.709
N =46
0
-2.00
-1.00
0.00
LOGX9
1.00
2.00
Application of factor analysis
Factor analysis was used to find seven financial
ratios that adequately explain three dimensions of
bank performance. The three dimensions of bank
performance were:
The profitability factor
 The investment factor
 The liquidity factor
 The oblique solution from the factor analysis is
shown in Table III.

Oblique rotation factor solution
Pattern matrix
.
Structure matrix
.
Definition of the significant financial
ratios
Profitability ratios
X5 Interest margin = (Interest income from loans
and securities – interest expense on deposits
and other debt issues)/Total assets. The net
interest margin measures how large a
spread between interest revenues and
interest costs management has been able to
achieve by close control over the bank’s earning
assets and the pursuit of the cheapest sources
of funding
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X8 Total spread = (Interest
income/Earning assets) – (Interest
expense/Interest bearing liabilities).
Spread measures the effectiveness of
the bank’s intermediation function in
borrowing and lending money and
also the intensity of competition in
bank’s market area.
Greater competition tends to squeeze the
difference between average asset yields
and average liability costs.
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If other factors are held constant, the
bank’s spread declines as competition
increases, forcing management to try
other ways to make up for an eroding
earning spread.
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X15 Interest paid/Interest received. Shows
how much of the interest received goes to
interest to be paid. It measures operating
conditions and cost efficiency .
Investment ratios
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X34 ROE = Net income after tax/Total
equity. It is a measure of the rate of
return flowing to the bank’s shareholders.
It approximates the net benefit that the
shareholders have received from investing
their capital in the bank.
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X39 Net return on average equity to
hurdle rate. The hurdle rate is the
required rate of return in a discounted
cash flow analysis.
 This rate must be equal to the increment
cost of capital. If expected rate of return
on an investment is below hurdle rate, the
project is not undertaken.
Liquidity risk ratios
X24 Total net liquid assets/Total deposits. Banks
issue liabilities that are redeemable at par.
Saving accounts are deposits that pay interest.
Checking accounts are deposits that have no
maturity.
 Current accounts are similar to saving accounts
but subject to income tax.
 Fixed deposits are deposits blocked for a period
of time and pay higher interest rates.
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Banks and correspondents are placement
accounts that a bank opens with its
correspondent bank.
 They are of two types: call accounts with a two
days notice before withdrawal and blocked
accounts with longer maturities.
 The liquid assets consist of cash with banks, plus
securities, which are the short term Treasury
Bills by the Lebanese government.
 X44 T Bills/Tot Deposits
Classification of banks into
homogeneous groups
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Cluster analysis was used to identify
four relatively homogeneous groups
with the 50 commercial banks that
had complete information on the financial
ratios that were determined by factor
analysis.
The banks are classified into four cohesive
clusters, depending on their profitability,
investment and liquidity risk factors.
Group I
consists of Bank of Beirut and
Arab Countries sal., Bank of Kuwait and
the Arab World sal., Bank of Lebanon and
Kuwait, Banque Lebanaise Pour le
Commerce sal.
(This bank is under consideration to be
taken over very soon by UBL: United Bank
of Lebanon), Byblos Bank sal., Banque
Audi sal., Banque Libano- Francaise sal.
Banque Misr Liban sal., Banque de la
Bakaa, Banque de la Mediterrennee sal.,
Banque du Liban et d’ Outer Mer sal.,
Credit Bancaiare sal., Credit Lebanese sal.,
Fransabank sal., Lebanese Canadian Bank
sal., Lebanese Swiss Bank sal., Lebanon
and Gulf Bank sal., Saudi Lebanese Bank
sal., Societe Generale.
Libano-Europeenne de Banque sal
Group I is characterized by having very
high T bills/Total deposits, the highest
interest paid to interest received, average
total spread, close to average interest
margin, above average ROE and above
average total net equity to total deposits.
Group II
consists of Al Mawarid Bank sal.,
Allied Business Bank sal., BEMO- Banque
Europeenne Pour le Moyen- Orient, Banque Lati
sal, Banque Pharoan et Chiha sal.
Banque de l’Industrie et du Travail sal., First
National Bank sal., Jammal Trust Bank sal.,
Metropolitan Bank sal., Middle East & African
Bank sal., National Bank of Kuwait (Lebanon)
sal., Near East Commercial Bank sal.
Societe Bancaire du Liban sal,
Group II is characterized by having the
minimum ROE, minimum total spread,
minimum interest margin and they are
middle on interest paid to interest
received and are low to middle on T
bills/Total deposits and are below average
on total net equity to total deposits.
This segment of banks is known for
having specialized types of banking
transactions.
Group III consists of: HSBC Bank
Middle East, Banca di Roma, Bank Saderat
Iran, Intercontinental Bank of Lebanon
sal., Saudi National Commercial Bank,
Habib Bank Limited and characterized as
being the highest on:
ROE, total net equity to total deposit,
interest margin, total spread and the
lowest on two financial ratios: T bills/Total
deposits and interest paid to interest
received. This segment of banks is
known for its short-term and small
amount of profitable loans.
Group IV
consists of the following
banks: ABN Amro Bank N.V., Arab Bank
plc., Bank Al-Madina sal, Bank of Beirut
sal., Bank Nationale de Paris
(Intercontinental).
Banque Saradar sal, Banque de Credit
National sal., Citibank, ING Banks and the
Syrian Lebanese Commercial Bank sal.,
Group IV is characterized by having high
ROE, minimum total net equity to total
deposits, below average total spread,
middle interest paid to interest received
and high T bills/Total deposits. This
segment is known for its huge
transactions outside Lebanon.
Assessing the relative importance of
the discriminant financial ratios
The question of interest is whether the banks
that are broken into four segments can be
differentiated in terms of these financial ratios.
Since there are four groups, three equations are
extracted. Table IV shows that the eigen value
associated with the first equation is 3.817, and
this function accounts for 68.7 per cent of
variance in the data. The second function has a
smaller eigenvalue while the third has the
smallest (the first is superior).
Eigenvalues and Wilk’s Lambda
To test the null hypothesis of equal group
centroids, the three equations are
considered simultaneously. The value of
Wilks’ Lambda λ transformed to a χ2 that
is significant beyond 1 per cent indicates
that no functions have been removed. The
three functions together separate between
the four groups.
An examination of Table V indicates a
large coefficient for interest paid to
interest received and low coefficient on T
bills/Total deposits on function I. Function
II has relatively very high coefficient for
total spread and low coefficient for total
net equity to total deposits. Function III
has very high coefficient for total spread
and very low coefficient for ROE.
Standardized canonical discriminant
function coeficient
.
Structure Matrix
Table VI shows that variables with large
coefficients for a particular function are
grouped together as shown by asterisks in
the structure matrix. Financial ratios are
ordered by size of canonical (discriminant)
loading (correlation with function).
T bills/Total deposits and ROE are grouped
together while total spread, interest
margin, interest paid to interest received
are grouped together.
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Net return on average equity to hurdle
rate is not included in analysis by the
stepwise procedure.
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The first function separates between
groups I and III in terms of T bills/Total
deposits and in terms of interest paid to
interest received. The second function
separates between groups II and III in
terms of total spread and separates
between groups III and IV in terms of
total net equity to total deposits.
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The third function separates between
groups II and III in terms of ROE and in
terms of interest paid to interest received.
Predictive ability of the model
The classification results based on this
analysis are shown in Table VII, which
convey that 100 per cent of the cases are
correctly classified.
Classification results
.
Addressing globalization and future implications it
is suggested that banks in group I merge
horizontally while banks in groups I and II
merge vertically. Such a model may be of
interest to:
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decision-makers in Lebanon.
Academics may apply the present model to
different industries in Lebanon and the Arab
world.
 Practitioners in Lebanon may find this model
helpful in their credit rating schemes
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THANK YOU