• Korean Security Journal
• /
• no.9
• /
• pp.27-68
• /
• 2005

Recently, because credit card crime using a personal credit information is increasing, professionalizing, and spreading the area, the loss occurring from credit card crime is enormous and is difficult to arrest and punish the criminals. At past, crime from forging and counterfeiting the credit card was originated by minority criminals, but at present, the types and appearance of credit card crime is very different to contrasting past crime. The numbers of people using credit card in the middle of 1990's was increasing and barometer of living conditions was evaluated by the number having credit card, therefore this bad phenomenon occurring from credit card crime was affected by abnormal consumption patterns. There is no need emphasizing the importance of personal credit card in this credit society. so, because credit card crime using personal credit card information has a bad effect, and brings the economic loss and harms to individuals, credit card company, and members joining credit card. Credit card crime using personal credit card information means the conduct using another people's credit card information(card number, expiring duration, secret number) that detected by unlawful means. And crime using dishonest means from another people's credit information is called a crime profiting money-making and a crime lending an illegal advance by making false documents. A findings on countermeasures of this study are as follows: Firstly, Diverting user's mind, improving the art of printing, and legitimating password from payment gateway was suggested. Secondly, Complementing input of password, disseminating the system of key-board protection, and promoting legitimations of immediate notification duty was suggested. Thirdly, Certificating the electronic certificates as a personal certificates, assuring the recognition by sense organ of organism, and lessening the ratio of crime occurrence, and restricting the ratio of the credit card crime was suggested.

• Journal of Information Technology Applications and Management
• /
• v.13 no.4
• /
• pp.273-290
• /
• 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.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.4
• /
• pp.83-90
• /
• 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)
• /
• v.15 no.10
• /
• pp.3627-3641
• /
• 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.

• Management & Information Systems Review
• /
• v.2
• /
• pp.295-310
• /
• 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)
• /
• v.16 no.2
• /
• pp.587-608
• /
• 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.

• The Journal of Information Systems
• /
• v.30 no.4
• /
• pp.203-226
• /
• 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.

• Journal of Families and Better Life
• /
• v.23 no.2 s.74
• /
• pp.77-91
• /
• 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 Families and Better Life
• /
• v.23 no.5 s.77
• /
• pp.15-26
• /
• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.273-276
• /
• 2014

In 2014, the leakage of personal information from 3 credit card companies resulted in divulging approximately 10,000 customers' personal information. Although the credit card companies concluded that there was no secondary loss due to the leakage of personal information, secondary financial losses resulting from the leakage of personal information currently occur. In particular, hackers who employ smishing masquerade acquaintances by using the divulged personal information to ask payment for Ms. Kim's Sochi Olympics legal processing or exposed traffic violations. The hackers cause secondary financial losses through smartphones. This study aims to conduct a forensic analysis of smishing incidents in smartphones through the leakage of personal information, and to make a forensic analysis of financial losses due to the smishing incidents.