• Knowledge Management Research
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• v.10 no.4
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• pp.1-15
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• 2009

국내에서 신용카드는 대표적인 지불 수단으로 정착되었으며 신용카드의 사용자와 신용카드의 발급 매수는 이미 포화상태에 도달해 있다. 이 같은 양적 성장은 정부의 신용카드 활성화 정책과 더불어 신용카드사 간의 과당 경쟁의 영향에 기인하고 있다. 신용차드의 사용층은 대부분의 성인 남녀로 확대되었으며, 특히 복수의 신용카드 소지자를 대상으로 자사가 발급한 신용차드를 사용하게 하기 위한 신용카드사 간의 경쟁이 치열한 상황이다. 이에 따라 신용카드사들이 경쟁사의 카드사용 회원을 자사의 회원으로 확보하는 젓이 불가피하며 마찬가지로 사용 중인 자사의 회원이 경쟁사로 이동하지 않도록 사전에 이탈 징후를 포착하여 유지 캠페인을 수행하는 것이 신용카드사 마케팅의 주요 활동이 되었다. 선행연구에서는 신용카드 회원의 이탈과 관련하여 다양한 데이터마이닝 기법을 이용한 이탈의 특성 분류 연구가 진행되었다. 본 연구는 회원 이탈에 영향을 주는 요인을 효과적으로 발견하기 위한 방법으로 베이지안 네트워크(Bayesian Network)를 활용한다. 특히, 베이지안 네트워크의 일종인 일반 베이지안 네트워크(General Bayesian Network)를 이용하여 회원의 이탈요인에 영향을 주는 요인들의 집합인 마코프 블랭킷(Makov Blanket)을 도출한다. 한편, 마코프 블랭킷에 포함된 변수를 이용해 민감도 분석을 수행하여 영향이 큰 요인을 찾아내고 이를 비즈니스 프로세스에 적용하여 실무적인 의의를 실증하고자 한다.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.49-64
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• 1999

본 연구는 백화점 고객이 신용 카드 신청 요구 시에 작성되는 가입 정보 및 사용되고 있는 고객의 거래 정보는 카드 사용 패턴으로 신용도를 예측하는 여러 방법론을 제시하고 성능을 비교하였다. 가입 정보를 분석하기 위해 역전파 신경망(Back-Propagation Neural Network, BPNN), 사례기반추론(Case-Based reasoning)을, 거래 정보를 분석하기 위해 역전파 신경망과 더불어 시간지연 신경망(Time-Delayed Neural Network, TDNN)을 각각 사용하여 그 결과를 비교하였다. 또한 전체시스템의 적중률을 높이기 위햐여, ID3와 신경망을 이용한 Meta-Leaning 방법을 제시하였으며, Meta-Learning 방법과 다른 방법들을 비교, 분석을 하였다. 본 연구에서는 모형 수립과 검증을 위하여 T백화점의 실제 신용 카드 가입 고객 데이터를 이용하여 실험하였다. 데이터의 성격에 따라 각 모델의 예측력에는 차이가 나타났으나, 신경망 모형의 예측력이 우수하였으며, 시간적 특성을 고려하는 시간지연 신경회로망 모형의 예측력은 더욱 우수하게 나타났다. 또한 Meta-Learning 모형을 사용하면 예측력이 더 높아진다는 것을 확인할 수 있었다.

• Journal of Families and Better Life
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• v.23 no.2 s.74
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• pp.77-91
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• 2005

The purpose of this study is to investigate general tendencies in credit card use, and determine the causes of the use of cash advance service and deferred payment among college students. Socio-demographic variables(gender, year in college, allowance, family income, parents' education and occupation, having taken a personal financial management course), knowledge and attitudes toward credit card, and financial management practices were incorporated as antecedent variables. Logistic regression analysis and multiple regression analysis were conducted to test the hypotheses. The results were as follows ; First, $32\%$ of the college students with no regular income experienced deferred payment, and $60.4\%$ of them had used a cash advance service. Second, the frequency and amount of cash advance service use were affected by family income, financial practices, and allowance. The financial practice as a parameter was affected by their completion of a personal finance course and their allowance. Third, deferred payment of credit was affected by their knowledge on credit cards and their financial practices. The financial practices as a parameter were affected by the family income and their completion of a personal finance course, and the knowledge on credit cards was affected by gender. Lastly, implications and suggestions for credit card use behavior research and consumer credit education are discussed in this article.

• Journal of the Korean Society for information Management
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• v.19 no.1
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• pp.23-46
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• 2002

With explosively increasing digital contents, library and Information center should have a new role between knowledge providers and knowledge users as information brokering organization. Electronic transaction system should be required for performing this brokering service since economic value is added to information and knowledge in information society. The developments and changes around library are keeping up with increasing building digital library and digitalizing printed sources. With the rapidly changing circumstances, the Internet is currently witnessing an explosive growth. By serving as a virtual information resource. the Internet can dramatically change the way business is conducted and Information is provided. However because of features o( the Internet like openness and information sharing, it has fundamental vulnerabilities in security issues. For Instance, disclosure of private information and line eavesdropping such as password, banking account, transaction data on network and so on are primary obstruction factors to activation of digital contents delivery on network. For high network security and authentication, this paper looks at smart card technologies and proposes multi-authentication protocol based on smart card on open network, implements and analyzes it.

• Knowledge Management Research
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• v.22 no.3
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• pp.151-172
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• 2021

The government's implementation of customer-friendly financial policies, such as lowering commission fees for credit card merchants and lowering the maximum interest rate, put the specialized credit finance companies in a crisis of lowering profitability. In this unfavorable situation, the efficiency study of specialized credit finance companies is meaningful. Accordingly, this study measured the efficiency of 34 specialized credit finance companies through Data Envelopment Analysis (DEA) and meta-frontier analysis. For meta-frontier analysis, specialized credit finance companies were divided into two groups (card companies and non-card companies) by industry or three groups (AA0 and above, AA-, and A+ or below) by credit rating. The results of the analysis will provide general insight into the efficiency of specialized credit finance companies. The results of this study are as follows. First, the average meta-efficiency of card companies was analyzed higher than that of non-card companies. Second, 80% of non-card's decision-making units (DMUs) were inefficient by pure technology rather than by scale. Third, decision-making units (DMUs), which account for 62.5% of the credit card company group and 80% of the 'AA-' credit rating group, are in non-economic areas of scale. Fourth, there was no statistically significant difference in meta-efficiency values (TE and PTE) by industry (card companies, non-card companies) and credit rating (AA0 or higher, AA-, A+ or lower). The contribution of this study will provide strategic initiatives for establishing management strategies to improve inefficiency by measuring the efficiency level of companies under an unfriendly business environment for specialized credit finance companies.

• Journal of Families and Better Life
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• v.10 no.2
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• pp.245-261
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• 1992

The Purpose of this study is to find out ;Which is the recognition of housewives abut the credit cards as a financial tool\ulcorner by what kind of motive is the use made\ulcorner How important the using credit card in the financed to household\ulcorner For this purpose, a survey was conducted by interview using questionnaire. The data were analyzed by frequency , percentage, arithmetic mean, standard deviation, x2 -test, ANOVA, correlation, multiple regression using SPSS/PC+ linear structural relationship using LISREL VI program. the conclusion deduced through result of data analysis and the discussion are as follows; First, in the respondent housekeeping, monthly average repayment of credit card is about 1/3 of the living expenses. Second, the knowledge of respondents about credit card was low generally Third, respondents use credit card by the motive of circulating money rather tan the motive of convenience. Fourth , generally respondents are not overdue the charge of credit card, but the smaller the cost of living is or the larger the motive of using credit card, the more overdue the charge of credit card. Fifth, as a result of linear structural relationship among the information credit card, motive of use and management behavior, the motive of using credit card effect on the management of credit card more directly than the knowledge of credit card. Sixth, as credit card is spread widely on the future, the information of credit card will be important variable on the personal credit and the management of credit card will be more important in the household financial management.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.1-9
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• 2002

Evolutionary artificial neural networks (EANNs) are towards the near optimal ANN using the global search of evolutionary instead of trial-and-error process. However, many real-world problems are too hard to be solved by only one ANN. Recently there has been plenty of interest on combining ANNs in the last generation to improve the performance and reliability. This paper proposes a new approach of constructing multiple ANNs which complement each other by speciation. Also, we develop a multiple ANN to combine the results in abstract, rank, and measurement levels. The experimental results on Australian credit approval data from UCI benchmark data set have shown that combining of the speciated EANNs have better recognition ability than EANNs which are not speciated, and the average error rate of 0.105 proves the superiority of the proposed EANNs.

• Journal of Families and Better Life
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• v.27 no.6
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• pp.95-109
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• 2009

This study focused on the development of a scale to measure the ability of consumers to use credit cards. The purposes of this study were to develop a tool which would be able to measure consumer knowledge, consumer skills and consumer attitudes. Data were collected from 313 credit card using consumers and were analyzed by employing a goodness of fit test, principal component analysis & confirmatory factor analysis(Amos 5.0), multiple regression. The results from this study were as follows: 1) Six factors of consumer knowledge(16-items) were identified: damage salvation; credit delinquency; personal credit information; credit provision period; credit & credit card issuance; credit delinquent striking out a record & credit rating. The total variance was 55.86%. 2) Three factors of consumer skills(17-items) were identified: credit delinquency & over-consumption; credit card management; and loss & damage salvation. The total variance was 62.90%. 3) Three factors of consumer attitudes(16-items) were identified: credit delinquency & credit; credit card issuance & use; and credit card management. The total variance was 58.75%.

• Journal of the Korea society of information convergence
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• v.6 no.2
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• pp.23-44
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• 2013

First, the average scores of personal financial management ability in the college students' financial management attitude were 72.24 for male and 71.65 for female, so that male students showed a little higher score than female. College students who had an experience of opening a bank account and who kept a record of spending revealed higher scores. Those whose parents were elementary or middle school graduates unfolded the highest score, 73.67, and the lowest score, 63.35, from those whose parents had M.A. or Ph.D. The average scores of personal financial management ability in the college students' financial management knowledge indicated almost no difference with 63.26 for male and 63.35 for female. Only whether they had an experience of opening a bank account, keeping a record of spending, or a credit card revealed score differences. Depending on the students' majors, there were also score differences. Students from engineering department came up with the highest score, an average of 66.88, and students from art & physical education department with the lowest score, 53.39, in the financial management knowledge. The personal financial management ability in the college students' financial management function showed that the score of male students was a little higher than that of female, 64.26 versus 63.58. Students who kept a record of spending and whose parents' income was between three million won and four million won marked the highest score, an average of 65.26, and students whose parents' income was below two million won marked the lowest score, an average of 60.43, in the college students' financial management function. There were score differences in the college students' financial management function depending on the students' majors. Students from engineering department came up with the highest score, an average of 69.67, and students from public health department with the lowest score, 63.21.