• 시큐리티연구
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• 제9호
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• pp.27-68
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• 2005

현재 개인신용정보이용 신용카드범죄는 그 특성상 고도의 전문화와 광역화로 인해 피해 발생후 원상회복이 어렵고 범죄인의 신속한 검거와 처벌 또한 쉽지 않다. 소수의 범죄인들에 의해서 발생하던 예전의 신용카드 위${\cdot}$변조 범죄들은 현재의 신용카드 관련 범죄와는 유형과 양상이 사뭇다르다. 현대신용사회에서 개인신용정보의 중요성은 굳이 강조할 필요가 없다. 따라서 개인신용정보이용 신용카드범죄가 국민 생활에 끼치는 악영향은 한 개인과 신용카드가맹점, 그리고 신용카드회사 모두에게 엄청난 경제적 손시로가 피해를 유발하는 것이다. 이 연구에서는 개인신용정보이용 신용카드범죄와 개인신용정보 부정이용범죄에 대한 효율적 대처방안들을 다음과 같이 제시하였다. 먼저, 신용카드정보 유출의 방지를 위한 대책으로서 카드사용자의 사용의식 전환, 신용카드매출전표의 인쇄내용 개선, PG(Payment Gateway) 업체 등을 통한 카드정보 암호화의 법제화를 들었다. 그리고, 비밀번호 입력에 대한 보완, 키보드 프로텍션(해킹방지) 시스템의 보급, 결제내역 즉시통보의무의 법제화를 들었다. 또한 다양한 본인 인증 방법으로서 전자인증서를 통한 인증, 생체인식 기술을 이용한 인증을 들었으며, 개인신용정보를 보호받지 못하는 나라에서의 신용카드사용을 제한하여 신용카드관련 피해 발생을 최소화하는 방안을 제시하였다. 그러므로 개인신용정보이용 신용카드범죄에 대한 효율적인 대처를 위해서는 카드사용자, 카드사, PG 업체, 정부 기관, 공인인증기관 등의 종합적인 협력과 노력이 요구되며, 경각심을 고취시키기 위한 처벌법규의 강화와 정책적 대안을 수립하여 현대사회에서의 건전한 신용문화를 형성하여야 할 것이다.

• Journal of Information Technology Applications and Management
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• 제13권4호
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• pp.273-290
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• 2006

This study suggests a frequency matrix technique to predict personal credit rate more efficiently using incomplete data sets. At first this study test on multiple discriminant analysis and logistic regression analysis for predicting personal credit rate with incomplete data sets. Missing values are predicted with mean imputation method and regression imputation method here. An artificial neural network and frequency matrix technique are also tested on their performance in predicting personal credit rating. A data set of 8,234 customers in 2004 on personal credit information of Bank A are collected for the test. The performance of frequency matrix technique is compared with that of other methods. The results from the experiments show that the performance of frequency matrix technique is superior to that of all other models such as MDA-mean, Logit-mean, MDA-regression, Logit-regression, and artificial neural networks.

• 한국컴퓨터정보학회논문지
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• 제22권4호
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• pp.83-90
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• 2017

In the past, when the credit card was delivered to the customer, the postal agreement and receipt were signed by customer. The repossessed documents were sent back to the card company through the reorganization process. The card company checks the error by scanning and keeps it in the document storage room. This process is inefficient in cost and personnel due to delivery time, document print out, document sorting, image scanning, inspection work, and storage. Also, the risk of personal data spill is very high in the process of providing personal information. The proposed system is a service that receives a postal agreement and a receipt to a recipient when signing a credit card, signing the mobile image instead of paper, and automatically sending it to the card company server. We have designed a system that can protect the cost of paper documents, complicated work procedures, delivery times and personal information. In this study, we developed 'u-paperless' and secure credit card delivery system applying electronic document and security system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3627-3641
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• 2021

Fintech, which stands for financial technology, is growing fast globally since the economic crisis hit the United States in 2008. Fintech companies are striving to secure a competitive advantage over existing financial services by providing efficient financial services utilizing the latest technologies. Fintech companies can be classified into several areas according to their business solutions. Among the Fintech sector, peer-to-peer (P2P) lending companies are leading the domestic Fintech industry. P2P lending is a method of lending funds directly to individuals or businesses without an official financial institution participating as an intermediary in the transaction. The rapid growth of P2P lending companies has now reached a level that threatens secondary financial markets. However, as the growth rate increases, so does the potential risk factor. In addition to government laws to protect and regulate P2P lending, further measures to reduce the risk of P2P lending accidents have yet to keep up with the pace of market growth. Since most P2P lenders do not implement their own credit rating system, they rely on personal credit scores provided by credit rating agencies such as the NICE credit information service in Korea. However, it is hard for P2P lending companies to figure out the intentional loan default of the borrower since most borrowers' credit scores are not excellent. This study analyzed the voices of telephone conversation between the loan consultant and the borrower in order to verify if it is applicable to determine the personal credit score. Experimental results show that the change in pitch frequency and change in voice pitch frequency can be reliably identified, and this difference can be used to predict the loan defaults or use it to determine the underlying default risk. It has also been shown that parameters extracted from sample voice data can be used as a determinant for classifying the level of personal credit ratings.

• 경영과정보연구
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• 제2권
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• pp.295-310
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• 1998

This exploratory study examines critical quality factors of store that can give access to credit card. The procedures of developing instrument is followed by recommendations on the developing measures of marketing constructs. The results shows that service quality of store available for credit card is divided four dimensions(personal service, payment-approving service, information-providing service, problem responsiveness service). These dimensions and scales are verified through the assessment of reliability and validity. Finally, the importance of personal service is showed to be different across types of industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.587-608
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• 2022

The European Union recently established the General Data Protection Regulation (GDPR) for secure data use and personal information protection. Inspired by this, South Korea revised their Personal Information Protection Act, the Act on Promotion of Information and Communications Network Utilization and Information Protection, and the Credit Information Use and Protection Act, collectively known as the "Three Data Bills," which prescribe safe personal information use based on pseudonymous data processing. Based on these bills, the personal data store (PDS) has received attention because it utilizes the MyData service, which actively manages and controls personal information based on the approval of individuals, and it practically ensures their rights to informational self-determination. Various types of PDS models have been developed by several countries (e.g., the US, Europe, and Japan) and global platform firms. The South Korean government has now initiated MyData service projects for personal information use in the financial field, focusing on personal credit information management. There is also a need to verify the efficacy of this service in diverse fields (e.g., medical). However, despite the increased attention, existing MyData models and frameworks do not satisfy security requirements of ensured traceability, transparency, and distributed authentication for personal information use. This study analyzes primary PDS models and compares them to an internationally standardized framework for personal information security with guidelines on MyData so that a proper PDS model can be proposed for South Korea.

• 한국정보시스템학회지:정보시스템연구
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• 제30권4호
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• pp.203-226
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• 2021

Purpose The purpose of this study is to enhance the accuracy score of personal credit scoring using the convolutional neural networks and secure the transparency of the deep learning model using eXplainalbe Artifical Inteligence(XAI) technique. Design/methodology/approach This study built a classification model by using the convolutional neural networks(CNN) and applied a methodology that is transformation of numerical data to imaged data to apply CNN on personal credit data. Then layer-wise relevance propagation(LRP) was applied to model we constructed to find what variables are more influenced to the output value. Findings According to the empirical analysis result, this study confirmed that accuracy score by model using CNN is highest among other models using logistic regression, neural networks, and support vector machines. In addition, With the LRP that is one of the technique of XAI, variables that have a great influence on calculating the output value for each observation could be found.

• 가정과삶의질연구
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• 제23권2호
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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.

• 가정과삶의질연구
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• 제23권5호
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• pp.15-26
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• 2005

The purpose of this study was to investigate the factors affecting credit card attitudes, financial management practices, and sound credit card use among college students, and to conceptualize a theoretical model. Earlier studies identified a number of antecedent variables (such as gender, year in college, job experience, amount of allowance, family income, living with parents, having taken a personal financial management course) and intervening variables (such as attitudes towards credit cards and financial management practices) as useful predictors of sound credit card practices. Four hundred and thirty four undergraduate students in Daejeon participated in this study. Stepwise multiple regression and path analysis were conducted. The results of this study were as follows: 1. Students' attitudes towards credit cards were affected by their you in college, whether they were living with their parents, and the amount of their allowance. Similarly, students' financial management practices were affected by their year in college, whether they were living with their parents, the amount of their allowance, and whether and not they had taken a personal financial management course. 2. Sound credit card practices were influenced by students' gender, their year in college, the amount of their allowance, attitudes towards credit cards, and financial management practices. 3. The path-analysis model demonstrates the relationships among the antecedent variables, intervening variables (credit card attitude, financial management practices), and sound credit card use.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.273-276
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• 2014

2014년 카드3사의 개인정보유출로 약 1건의 고객정보가 유출되었다. 카드사는 개인정보유출로 인한 2차 피해는 없다고 단정지었지만, 실제로 개인정보유출 2차 피해가 발생하고 있다. 특히 스마트폰에서 Smishing은 유출된 개인정보를 이용하여 지인을 가장한 송금과 소치올림픽 김모양 소송, 차량단속대상적발 등 개인정보 유출로 인한 2차피해가 스마트폰에서 Smishing사고가 발생하고 있다. 본 논문에서는 스마트폰 Smishing사고에 대한 개인정보유출에 대한 Forensic 하고 스미싱 사고로 인한 금융피해에 대한 Forensic을 분석 하고자 한다.