Journal of Service Science and Management, 2011, 4, 234-241
doi:10.4236/jssm.2011.42028 Published Online June 2011 (http://www.SciRP.org/journal/jssm)
An Empirical Analysis of Credit Card Customers’
Overdue Risks for Medium- and Small-Sized
Commercial Bank in Taiwan
Chia-Chi Lee1, Tyrone T. Lin2, Yi-Ting Chen3
1Department of Accounting Information, National Taipei College of Business, Taipei, Chinese Taipei; 2Department of International
Business, National Dong Hwa University, Hualien, Chinese Taipei.
Received April 22nd, 2011; revised May 16th, 2011; accepted May 18th, 2011.
ABSTRACT
This paper constructs a multiple regression model to evaluate the overdue risk of credit card holders. The results can
identify the factors influencing the credit card holders’ overdue risk behavior in order to provide card issuing banks a
decision-making reference in the investigation of credit card holders’ related characteristics and the relationship qual-
ity between the credit card holders and the bank. In addition, the paper can also provide credit card issuing banks the
practice reference of the application on risk management decision.
Keywords: Credit Card, Overdue Risk, Credit Card Holder, Credit Card Issuing Bank
1. Introduction
The rapid growth of the credit card market after the full
liberalization results in the increase of people’s depend-
ence on credit cards [1]. For banks, the income derived
from credit cards has changed from the past transaction
amount fee of credit card payment into today’s high re-
volving interest rate income of credit cards’ loans. This
change makes the credit card market become an impor-
tant business sprint target of banks’ earnings. Banks en-
joy the generous income brought by credit card issuing,
but should be careful about taking credit risk due to the
over issuing problem in the credit card market [2].
Reference [3] points out that there is a concern about
an increasing number of consumers may be unable to
meet their future financial commitments. At the same
time, credit providers are avidly seeking greater profits
by enticing consumers to borrow more and more. Against
this background, the issue of corporate social responsi-
bility (CSR) in the Australian consu mer credit industry is
discussed. Therefore, in order to pursue banks’ CSR and
profits, the banking industry or related interest groups
need to establish a complete risk control mechanism. In
addition, for the consumers of the above-mentioned type,
it is necessary to complete an in-depth study about the
implementation of the relevant policies, regulations, and
the application of business strategies so as to strengthen
the sound operation of a financial system.
The paper explores the factors affecting the overdue
credit card holders from two dimensions such as the per-
sonal characteristics of the credit card holder, the trans-
action relationship between the credit card holder and the
case bank to identify the variables related to the dimen-
sions of the empirical research. Through the use of the
complete data established by the case bank, the paper can
perform an overdue factor analysis. Different from most
of the past studies which used only limited information
publicly available as a research subject, the feature of the
current research is to more specifically capture the poten-
tial factors affecting the cred it card holder’s overdue risk.
The paper expects that the findings of the paper can pro-
vide banking executives a reference concerning deciding
credit standards, loan amount, and criteria assessment in
order to establish a complete risk control mechanism.
The paper will also provide the government a reference
about the future development of relevant financial regu-
lations and policies.
2. Hypotheses Development
2.1. Dimension of the Credit Card Holder’s
Personal Characteristics
Whether a client has a higher level of occupation or not
will affect the stability of his work. The occupations and

An Empirical Analysis of Credit Card Customers ’ Overdue Risks for Medium - and Small-Sized Commercial Bank in Taiwan 235
companies with better welfare can usually more easily
retain employees, whose work stability is also higher.
The customers with a worse occupation will chang e work
more often, and thus their stability decreases. Reference
[4] uses the occupation classification as a variable and a
decision tree to analyze it. The paper expects that the
credit card hold ers with a higher level of occupation will
have higher work stability and their probab ility of occur-
rence of credit card overdue risk will be lower. In that
case, the credit card overdue amount is relatively low.
Therefore, the hypothesis H1-1 is established as follows:
H1-1: The higher the credit card holder’s occupation
level is, the lower his credit card overdue amount will be.
Reference [5] points out that consumers’ labor income
will have an impact on the credit card overdue amount
and the consideration of consumer loan credit focuses on
whether customers have stable income and on the
amount of revenue to determine their solvency. A cus-
tomer with higher income stability and higher amount of
revenue will have a lower overdue risk. Therefore, the
paper expects that the amount of credit card holder’s
monthly income is negatively correlated with the credit
card overdue amount. Thus, the hypothesis H1-2 is es-
tablished as follows:
H1-2: The higher the credit card holder’s monthly in-
come is, the lower his credit card overdue amount will
be.
The credit card business operates in coordination with
banks’ plann ing marketing activities to exp ect that credit
card holders can use their cards more frequently after the
application. Banks perform the analysis of consumers’
credit card usage behavior in order to help the banking
industry to provid e comprehensive financial services and
increase credit card holders’ utilizat ion rate [6]. However,
if customers lack the ability of self-d iscipline an d can no t
normally pay credit card accounts, the possibility of
credit card overdue risk is relatively increased. Therefore,
the paper expects that the credit card overdue amount of
the credit card holders using their cards every month is
relatively higher than that of the credit card holders not
using their cards every month. Hence, the hypothesis
H1-3 is established as follows:
H1-3: The credit card overdue amount of the card
holder using his card every month is relatively higher
than that of the credit card holder not using his card
every month.
Credit card holders should deposit the amount of credit
card bill into the bank designated account before the
agreed credit card payment deadline [7]. The revolving
credit users’ will or ability of monthly fee is different
from the credit card holders who pay the total amount of
bill. If customers’ payment begins to become unstab le or
the payment will is weak, the credit card overdue risk is
increasing. Therefore, the paper expects that the credit
card holder’s payment will is negatively correlated with
the credit card overdue amount. Therefore, the hypothe-
sis H1-4 is established as follows:
H1-4: The higher the credit card holder’s payment will
is, the lower his credit card overdue amount will be.
2.2. Dimension of the Transaction Relationship
between the Credit Card Holder and the
Bank
The major purpose of using a credit card is to facilitate
the payment. Because of the highly competitive credit
card market, banks have lending money pressure and
then allow credit card holders to withdraw cash with the
revolving credit card interest rate under the credit limit.
However, the customers who can have lower interest rate
loans by normal ways rarely use credit cash [8]; this
method is usually used by the credit card holders who are
urgently in need of funds. Such customers are more ac-
tive and diverse in the use of funds, but their credit card
overdue risks are relatively increased. Therefore, the pa-
per expects that the credit card holders using cash ad-
vance have relatively higher credit card overdue amounts
than those not using cash advance. Thus, the hypothesis
H2-1 is established as follows:
H2-1: The credit card holders using cash advance have
relatively higher credit card overdue amounts than those
not using cash advance.
Part of the credit card holders without the increase in
income constantly use th eir credit cards as payment tools
and begin to steadily accumulate the debts of revolving
credit with high credit card interest rates [9]. The paper
expects that the credit card holders who use the revolving
credit interest will have relatively higher credit card
overdue amounts compared with those who do not use it.
Thus, the hypothesis H2-2 is established as follows:
H2-2: The credit card holders who use the revolving
credit interest will have relatively higher credit card
overdue amounts compared with those who do not use it.
For the credit card hold ers failing to pay off credit card
accounts, the unpaid amount plus the revolving credit
interest will be counted into the next bill. If the credit
card holders continuously delay paying the total amount,
the correspondent revolving credit interest will continu-
ously to be charged. Thus, the increase of credit card
principal and the corresponding revolving interest will
make the credit card debtors be mired in the financial
crisis. Reference [10] and Reference [11] find that the
credit card holder’s use of credit limit and the delays of
credit card accounts significantly affect the increase of
the credit card debt. Therefore, the paper expects that the
higher the amount of revolving credit used by the credit
card holder is, the higher the credit card overdue amount

An Empirical Analysis of Credit Card Customers ’ Overdue Risks for Medium - and Small-Sized Commercial Bank in Taiwan 236
will be; they are positively correlated. Therefore, the
hypothesis H2-3 is established as follows:
H2-3: The higher the amount of revolving credit used
by the credit card holder is, the higher the credit card
overdue amount will be.
The use of consumer finance credit tools is mainly to
bring customers the convenience of using short-term
working capital under emergency. If credit card holders
use a large number of credit financing in short term, their
fund leverage will tend to be too high. Reference [12]
studies the financial situation of consumers and finds that
the credit card loans have an absolute impact on the in-
crease of consumer credit card debt which leads to a
bankruptcy probability. The paper expects that the credit
card holders having credit loans in other banks means
that they have more shortage problems or financial diffi-
culties in cash flows and their credit card overdue
amounts will be relatively higher. Hence, the hypothesis
H2-4 is established as follows:
H2-4: The credit card holders who have credit loans in
other banks will have higher credit card overdue amounts
compared with those who do not have credit loans in
other banks.
Reference [13] uses the multiple criteria linear pro-
gramming to propose a classification model and find that
this model theory can deal with the credit card holders’
behavior pattern of any class. They assess the behavior of
the credit card holders pre-divided into four classes and
perform the credit card management portfolio. They pre-
dict the key points of the credit card holders’ consumer
behavior to reduce the risk occurrence. The levy review
officer of the case bank will composite score and give a
risk level to a new credit card applicant in accordance
with the customer’s attributes. The credit card holder
with a higher risk factor also has a higher overdue prob-
ability. The paper expects that th ere is a positive correla-
tion between the credit card holder’s risk coefficient and
the credit card overdue amount. Thus, the hypothesis
H2-5 is established as follows:
H2-5: The higher the credit card holder’s risk coeffi-
cient set by the bank is, the higher the credit card over-
due amount will be.
If customers possess longer bank credit cards, banks
will be able to accumulate their personal credit ratings
and then determine customers’ loyalty to banks. There-
fore, banks will have more negotiation space in deter-
mining whether they will give interest rate concessions to
customers. Reference [14] points out that bank used to
observe the historical information of loan applicants’
accounts to predict their credit scoring. Therefore, the
paper expects that the audit checks of the credit card
holders having a longer transaction period with banks
will be less rigorous compared with the customers of
initial credit card application. Hence, the transaction pe-
riod between the credit card holder and the bank is posi-
tively correlated with the credit card overdue amount.
Therefore, the hypothesis H2-6 is established as follows:
H2-6: The longer the transaction period between the
credit card holder and the bank is, the higher the credit
card overdue amount will be.
Reference [15] finds that credit card holders having a
good attitude of credit u s age are more willing to maintain
their credit quality. Reference [16] points out that the
high ratio of used credit to the credit limits will increase
the possibility of credit card overdue risk. The paper ex-
pects that the ratio of the credit card holder’s used credit
to the credit limit is positively correlated with the credit
card overdue amount. Thus, the hypothesis H2-7 is es-
tablished as follows:
H2-7: The higher the ratio of the used credit to the
credit limit is, the higher the amount of the credit card
overdue amount will be.
Reference [17] finds that the quality of bank auditors
and the amount of issued credit have an absolute impact
on whether the bank is able to select the appropriate cli-
ent in accordance with conditions. If the credit card
holder’s credit limit issu ed by the bank is too high, it can
potentially push the credit card holder to use too much
amount of credit. Hence, the paper expects that the credit
card’s credit limit issued by the bank is positively corre-
lated with the credit card overdue amount. Therefore, the
hypothesis H2-8 is established as follows:
H2-8: The higher the credit card holder’s credit limit
issued by the bank is, the higher the credit card overdue
amount will be.
3. Methodology
3.1. Sample and Data Source
The samples of the paper come from the credit card
holders of a medium- and small-sized commercial bank
from January 1998 to December 2006 for a total of nine
years. The paper introduces a stratified random sampling
way to choose 612 credit card holders which include 2
types of data segments: 439 normal credit card holders
and 173 overdue credit card holders.
Normal credit card holders: it refers to the customers
who pay the entire payable account or more than the
minimum payable account before the current payment
deadline. The payable account is the sum of current and
previous unpaid credit card accounts, cash advance
amount, or plus other payable accounts such as: interest
on revolving credit, annual fees, cash advance fees, fees
of report the loss, or the fees of accessing bill details. A
total of 439 customers belong to the type of normal credit
card holders.

An Empirical Analysis of Credit Card Customers ’ Overdue Risks for Medium - and Small-Sized Commercial Bank in Taiwan 237
Overdue credit card holders: it refers to the customers
who have not repaid the principal or interest yet for more
than three months, or have prosecuted or dealt with the
collaterals from the principal or accessory debtors even
though not exceeding three months. The paper focuses on
the occurred facts of customers’ overdue risks. Therefore,
the customers who have non-performing loans but be-
come normal payment customers or transfer their credit
loans to other banks after lending calls are still assigned
to the type of overdue credit card holders.
3.2. Regression Model
According to the research hypotheses established in Sec-
tion 2, the paper includes the control variables of overall
economic environment in the regression model in order
to control the influencing factors such as industrial char-
acteristics, external environment, and economic climate
on the credit card overdue amount. The empirical model
(1) of the pape r is developed as follows:
AMT=β0+β1OCUP+β2MREV+β3UCARD+β4WILL+β5
ADVN+β6REINT+β7REINTAMT+β8BLOAN+β9RISK+β10
PERD+β11RATIO+β12APPROV+β13SCORE+β14UMEP+
β15CGRO+e (1)
where the dependent variable AMT is the credit card
holder’s actual overdue amount. On the independent
variables, OCUP is the credit card holder’s occupation
level, according to the occupational level in descending
order, the paper sets 1 for the military staff and civil ser-
vice workers; 2 for the business practitioners; 3 for the
employees in the manufacturing industry; 4 for the
workers in agriculture, forestry, fish, farming and the
customers having no fixed working; MREV is the credit
card holder’s monthly income; UCARD is whether the
credit card holder uses his credit card every month; WILL
is the credit card holder’s payment will, according to the
payment will in descending order, the paper sets 1 for the
full payable on time; 2 for the minimum payment due on
schedule; 3 for the full payable after the deadline; 4 for
the minimum payment due after the deadline. As to the
default credit card holders; 5 is set for the first default
and in arrears less than TWD10 thousand; 6 for the sec-
ond default or spending money more than TWD10 thou-
sand and less than TWD50 thousand; 7 for the third de-
fault or spending money more than TWD50 thousand
and less than TWD200 thousand; ADV N is whether the
credit card holder uses cash advance; REINT is whether
the credit card holder uses the revolving credit interest;
REINTAMT is the amount of revolving credit used by the
credit card holder; BLOAN is whether the credit card
holder has other banks’ credit loans; RISK is the credit
card holder’s risk coefficient set by the case bank, ac-
cording to the risk rating in ascending order, the paper
sets 1) for the case bank’s staff; 2) for the secured loan
customers and excellent customers; 3) for the general
customers; 4) for the customers holding an identity card;
5) for the customers of ad hoc promotion; 6) for the mer-
chants staff of promotion cases; 7) for the customers
from insurance agents’ promotion cases; 8) for the cus-
tomers of ad hoc promotion without auditing; 9) for the
customers of high-risk; PERD is the transaction period
between the credit card holder and the case bank; RATIO
is the ratio of the used credit to th e credit limit; APPROV
is the credit card holder’s credit limit issued by the case
bank. On the control variables, SCORE is the total score
of monitoring indicators in Taiwan; UMEP is the unem-
ployment rate; CGRO is the annual growth rate of total
credit card accounts. β0 is the intercept; β1…β15 are pa-
rameters of regression model; e is the error term of re-
gression model.
4. Empirical Results and Discussions
4.1. Descriptive Statistic Results
Table 1 shows the descriptive statistics for all variables.
The mean value of AMT is TWD32.34 thousand, the
maximum is TWD353 thousand, and the minimum is 0
which indicates that it is a normal account without any
overdue amount. As for the dimension of the credit card
holder’s personal characteristics, the mean value of
OCUP is 3.067; the distribution of the sample object
shows that the main credit card holders are the employ-
ees in the manufacturing industry. The mean value of
MREV is TWD30.902 thousand, which indicates that
most of the credit card holders are salaried workers;
banks still prefer the customers having a fixed and stable
source of income. The mean value of UCARD is 0.732;
this reveals that more than half of the credit card holders
are willing to use their credit cards as a monthly payment
tool in the consumption. The mean value of WILL is
2.588, which means most of the credit card holders are
willing to pay their credit card bills in time to maintain
their good credit records.
For the dimension of the transaction relationship be-
tween the credit card holder and the bank, the mean value
of ADV N is 0.025 , which indicates that most of the credit
card holders mainly use their credit cards as a payment
tool, but not a credit loan tool. The mean value of REINT
is 0.606, which indicates most of the credit card holders
will measure their capital needs and choose to pay the
minimum payments while having difficulties in capital
turnover in order to maintain a good credit rating and
make flexible use of available funds. The mean value of
REINTAMT is TWD40.827 thousand, which means that
the credit card holders being unable to pay all the credit
card bills will consider using the revolving credit interest;

An Empirical Analysis of Credit Card Customers ’ Overdue Risks for Medium - and Small-Sized Commercial Bank in Taiwan 238
Table 1. Descriptive statistic.
Mean Minimum 25th% 50th% (Median)75th% Maximum Std. deviation
AMT (Unit: 10 thousand TWD) 3.234 0.000 0.000 0.000 2.900 35.300 6.548
OCUP 3.067 1.000 3.000 3.000 4.000 4.000 0.791
MREV (Unit: thousand TWD) 30.902 16.000 24.000 30.000 35.000 80.000 9.821
UCARD 0.732 0.000 0.000 1.000 1.000 1.000 0.443
WILL 2.588 1.000 1.000 2.000 4.000 7.000 2.011
ADVN 0.025 0.000 0.000 0.000 0.000 1.000 0.155
REINT 0.606 0.000 0.000 1.000 1.000 1.000 0.489
REINTAMT (Unit: thousand TWD) 40.827 0.000 0.000 7.950 66.000 317.000 62.270
BLOAN 0.183 0.000 0.000 0.000 0.000 1.000 0.387
RISK 6.487 1.000 6.000 7.000 8.000 9.000 1.895
PERD (Unit: years) 4.814 1.000 4.000 5.000 5.000 9.000 1.318
RATIO (Unit: %) 0.228 0.000 0.000 0.000 0.450 1.267 0.386
APPROV (Unit: 10 thousand TWD)12.270 2.000 8.000 12.000 15.000 35.000 6.380
SCORE 22.032 12.500 19.500 19.500 27.000 30.500 5.227
UMEP (Unit: %) 4.757 2.690 4.570 4.990 5.170 5.170 0.639
CGRO (Unit: %) 17.063 –3.490 11.490 13.495 26.140 27.815 6.585
Notes: 1. The variable AMT is the credit card holder’s actual overdue amount; OCUP is the credit card holder’s occupation level; MREV is the credit card
holder’s monthly income; UCARD is whet her the credi t card ho lder uses h is credit card every mont h; WILL is the credit card holder’s payment will; ADVN is
whether t he credit card hol der uses the cash ad vance; REINT is wh ether the credi t card holder us es the revolving credit interest; REINTAMT is the amount of
the revol ving credi t used by the cr edit card ho lder; BLOAN is wh ether the cred it card hol der has oth er banks’ credi t loans; RISK is the credit card holder ’s risk
coeffici ent set by the cas e bank; PERD is the transacti on period between the credit car d holder and t he case bank; RATIO is the ratio of the used credit to the
credit limit; APPROV is the credit car d ho lder ’s cred it limit i ss ued b y th e case ban k; SCORE is the total score of monitoring indicators in Taiwan; UMEP is the
unemployment rate; CGRO is the annual growth rate of total credit card accounts. 2. The total observations are 612 records.
the amortization of principal and interest can reduce
debtors’ payment stress. The mean value of BLOAN is
0.183; it means that most of the credit card holders do
not have other banks’ credit loans. The mean value of
RISK is 6.487; it means that most of the customers are
concentrated in the merchants’ staff of promotion cases
and the customers from insurance agents’ promotion
cases. The mean value of PERD is 4.814 years; it means
that the credit card holders hold their credit cards for
about five years. The mean value of RATIO is 0.228%; it
means that the customers who use the revolving credit
interest will not excessively expand their credit. The
mean value of APPROV is TWD122.7 thousand, which
shows that the assessment criteria of the customer’s
credit limit is based on his credit capacity.
As for the control variables, the mean value of SCORE
is 22.032; it means that the average Taiwanese economy
is in the state of moderate development. The mean value
of UMEP is 4.757%; this indicates that during the sample
period, the unemployment rate increased from 1998 and
decreased in 2006. The mean value of CGRO is 17.063%;
this indicates that the average annual growth rate of total
credit card accounts increased slightly since 1998 and
showed a huge decline in 2005.
4.2. Regression Results
Table 2 shows the regression results of credit card over-
due amount. Firstly, Panel A is the ANOVA analysis of
the regression model. The regression model shows good
fitness, reaching a significant level ( F-statistic = 264.483,
p value = 0.000), and R2 = 0.869, Adj. R2 = 0.866; there-
fore, the explanatory ab ility of the model fo r independ ent
and control variables are all superior to 80%. In addition,
the variance inflation factor (VIF) test of all independent
and control variables are all inferior to 10, which means
that there is no such thing as a high degree of collinearity
problem between variables.
Panel B is the regression analysis results. As to the
dimension of the credit card holder’s personal character-
istics, OCUP and AMT are significantly positiv ely corre-
lated (p value=0.009), reaching the statistically signifi-
cant level of 1%. This is consistent with the expected
direction of hypothesis; thus, the hypothesis H1-1 is
supported. It means that when the credit card holder’s
occupation belongs to the military staff and civil service
workers (category 1), the overdue amount will be lower;
on the other hand, when the credit card holder belongs to
the workers in agriculture, forestry, fish, farming, or the
customers having no fixed working (category 4), the
overdue amount will be higher. MREV and AMT are in-
significantly negativ ely correlated; even though it is con-
sistent with the expected direction of hypothesis, it does
not reach a statistically significant level. Therefore, the
hypothesis H1-2 is not supported. However, the resu lt of
the variable can still reveal that when the credit card
holder’s has higher monthly income, his solvency will be
more stable and the overdue amount will be relatively
lower. UCARD and AMT are significantly positively
correlated (p value = 0.000), reaching the statistically
significant level of 1%. This is consistent with the ex-
pected direction of hypothesis; thus, the hypothesis H1-3
is supported. It means that when the credit card holder
uses his credit card every month, the overdue amount
will be higher. WILL and AMT ar e s i g nific antly positively

An Empirical Analysis of Credit Card Customers ’ Overdue Risks for Medium - and Small-Sized Commercial Bank in Taiwan 239
Table 2. Regression results of credit card overdue amount.
Panel A: ANOVA analysis
Sum of squares df Mean squareF-statistic Prob(F-statistic) R2 Adj. R2
Regression 22,776.882 15.000 1,518.459 264.483***0.000 0.869 0.866
Residual 3,421.778 596.000 5.741
Total 26,198.659 611.000
Panel B: Regression results
Total sample (N = 612)
Variables Predicted sign
CoefficientStd. error t valuep value (one-tailed) VIF
Intercept –5.652 2.273 –2.4870.007***
OCUP + 0.320 0.136 2.362 0.009*** 1.225
MREV – –0.011 0.010 –1.0730.142 1.089
UCARD + 2.633 0.590 4.463 0.000*** 7.282
WILL + 1.008 0.134 7.510 0.000*** 7.758
ADVN + 0.386 0.648 0.596 0.276 1.070
REINT + –2.303 0.326 –7.0630.000*** 2.706
REINTAMT + 0.017 0.003 6.924 0.000*** 2.621
BLOAN + 0.768 0.466 1.647 0.050** 3.468
RISK + –0.046 0.055 –0.8400.201 1.161
PERD + 0.033 0.150 0.222 0.412 4.140
RATIO + 12.401 0.631 19.6560.000*** 6.313
APPROV + 0.263 0.017 15.1110.000*** 1.315
SCORE –0.022 0.040 –0.5600.288 4.637
UMEP –0.266 0.215 –1.2370.108 2.004
CGRO 0.005 0.022 0.216 0.415 2.169
Notes: 1. Variables are defined in Table 1. 2. *p<0.1, **p<0.05, ***p<0.01. 3. N is the number of observations. 4. The univariate
test result of RISK confirms that there exists a significant difference in the overdue amounts of high- and low-risk groups’ credit
card holder s.
correlated (p value = 0.000), reaching the statistically
significant level of 1%. This is consistent with the ex-
pected direction of hypothesis; thus, the hypothesis H1-4
is supported. It means that when the credit card holder
has higher payment will, the overdue amount will be
lower.
As for the dimension of the transaction relationship
between the credit card holder and the bank, ADVN and
AMT are insignificantly positively correlated; even
though it is consistent with the expected direction of hy-
pothesis, it does not reach a statistically sign ificant level.
Therefore, the hypothesis H2-1 is not supported. How-
ever, the result of the variable can still reveal that the
credit card holder having difficulties in capital turnover
starts to use the cash advance; therefore, the overdue
amount will be higher. REINT and AMT are significantly
negatively correlated (p value = 0.000), reaching the sta-
tistically significant level of 1%. That is, the credit card
holders using the revolving credit interest have lower
overdue loan amounts; those who do not use the revolv-
ing credit interest have higher overdue loan amounts. It is
not consistent with the expected direction of hypothesis,
thus, the hypothesis H2-2 is not supported. The further
observations from the practice show that even though the
credit card holders can not totally pay their credit card
debts in order to maintain the good credit statu s , they will
at least choose to pay the minimum payments due; it is
deemed that the credit card holders are willing to be re-
sponsible for their credit card debts. Therefore, the cus-
tomers who pay attention to their own credit rating will
have lower overdue amounts. REINTAMT and AMT are
significantly positively correlated (p value = 0.000),
reaching the statistically significant level of 1%. This is
consistent with the expected direction of hypo thesis; thus,
the hypothesis H2-3 is supported. It means that when the
credit card holder’s revolving credit amount gradually
increases, the overdue amount will be higher. BLOAN
and AMT are significantly positively correlated (p value
= 0.050), reaching the statistically significant level of 5%.
This is consistent with the expected direction of hypothe-
sis; thus, the hypothesis H2-4 is supported. It means that
when the credit card holder has other banks’ credit loans,
the overdue amount will be higher.
RISK and AMT are insignificantly negatively corre-
lated and it is not consistent with the expected direction
of hypothesis; thus, the hypothesis H2-5 is not supported.
The reason for the insignificance is probably due to the
fact that the risk coefficient is set in accordance with the

An Empirical Analysis of Credit Card Customers ’ Overdue Risks for Medium - and Small-Sized Commercial Bank in Taiwan 240
credit card holder’s occupation and the acquisition chan-
nel. In practice, even though the bank sets the credit card
holder to a high risk category, if the credit card holder is
willing to maintain a good credit status and pay the
monthly credit card payments on time, it will not result in
an increase in the amount of overdue loans. PERD and
AMT are insignificantly positively correlated; even
though it is consistent with the expected direction , it does
not reach the statistically significant level. Thus, the hy-
pothesis H2-6 is not supported. RATIO and AMT are sig-
nificantly positively correlated (p value = 0.000), reach-
ing the statistically significant level of 1%. It is consis-
tent with the expected direction of hypothesis; thus, the
hypothesis H2-7 is supported. It means that the higher
the ratio of used credit to the credit limit is, the higher the
overdue amount will be. APPROV and AMT are signifi-
cantly positively correlated (p value = 0.000), reaching
the statistically significant level of 1%. It is consistent
with the expected direction of hypothesis; thus, the hy-
pothesis H2-8 is supported. It means that the higher the
credit card holder’s credit limit issued by the bank is, the
higher the overdue amount will be.
Even though the three macroeconomic control vari-
ables, SCORE, UMEP, CGRO do not have significant
impacts on the overdue amount, the results of these three
variables can still indicate that when the economy in
Taiwan is good, the overdue amount will be lower; when
the unemployment rate is higher, the customers using
credit cards more conservatively will not increase the
overdue amount. When the annual growth rate of total
credit card accounts increases, it means that customers
use credit cards more frequently; therefore, the overdue
amount will be higher.
5. Conclusions and Suggestions
The paper makes the following recommendations about
the credit amount of credit card lending for the banking
industry and management decision-making units: 1) the
recommendation to th e card issuing b anks’ planning unit:
it is suggested that before the issuance of credit cards, the
ad hoc planning unit’s credit card promotions should
engage the consumer market segmentation and consider
the potential customers of professional levels as the
choice of target customers; 2) the recommendation to the
card issuing banks’ credit approval unit: it is suggested
that after improving plans, the planning unit’s credit re-
viewer and loan approval staff should rigorously control
applicants’ credit conditions; while examining their pro-
vided written credit reports, the bank s should refer to the
purpose of customers’ consumption and use of a credit
card and customers’ financial status in order to perform
the detailed assessment of applicants’ future ability and
willingness to repay their debts; 3) the recommendation
to the card issuing banks’ audit unit: the audit unit is
suggested to implement the rigorous internal control to
ensure that no fraud circumstances will happen. It is also
suggested to appropriately adjust the lending regulations
of current financial situation under the present social
economy situation in order to avoid the outdated regula-
tory information and prevent the front-line workers from
facing the dilemma of not immediately dealing with a
contingency or emergency; 4) the recommendation to the
card issuing banks’ highest decision-making unit: the
business development should be based on the concept of
sustainability and stability. The op erating environment of
the financial industry is highly changeable; it repeatedly
tests the highest decision-making unit’s wisdom and
common sense. If banks only seek temporary profits and
hurt business foundation, it will be worth the candle. In
the pursuit of return on equity, it should be more prag-
matic to face the potential change of perspective, but also
to take into account the social responsibility in order to
reduce the generation of business cost and social cost.
6. Acknowledgements
The authors would like to thank the National Science
Council of the Republic o f China, Taiwan for financially
supporting this research under Contract No. NSC
98-2410-H-259-010-MY3 and NSC 99-2410-H-141-
007-MY2.
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