• The Journal of Information Systems
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• v.32 no.3
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• pp.151-164
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• 2023

Purpose This study aims to analyze the current status of consumer awareness on Internet banks by conducting a full investigation and collecting user opinions presented on Google Play. After cateogorizing the current dissatisfaction, we would like to present not only the direction of the Internet bank service of but also the improvements of the platform. Design/methodology/approach Using opinion mining, subjectivity analysis, polarity analysis, and polarity information analysis of comments were conducted step by step to extract negative and positive keywords. The extracted keywords analyzed the weights of the frequently appearing positive and negative keywords using the TF-IDF model. Based on previous studies that negative information is more sensitive to positive information, we tried to confirm the connection, proximity, and mediation of negative keywords. Semantic Network Analysis (SNA) was used to visualize the connection relationship between the negative comment keywords of the three Internet banks. Findings Domestic Internet banks such as Kakao Bank, K-Bank, and Toss Bank have attracted a lot of attention even before they were established, and after establishment, they have secured a wide range of users through platforms that are completely different from existing banks. This study found out that the convenience of the app affects the opening and transaction of non-face-to-face accounts, which are characteristics of domestic Internet banks, which also affects the bank's business strategy. In addition, this study shows that the business characteristics of the company can be identified.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.232-234
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• 2022

Big data is widely used in customer relationship management, relationship marketing, financial business improvement, credit information and risk management. Moreover, as non-face-to-face financial transactions have become more active recently due to the COVID-19 virus, the use of financial big data is more demanded in terms of relationships with customers. In terms of customer relationship, financial big data has arrived at a time that requires an emotional rather than a technical approach. In relational marketing, it was necessary to emphasize the emotional aspect rather than the cognitive, rational, and rational aspects. Existing traditional financial data was collected and utilized through text-type customer transaction data, corporate financial information, and questionnaires. In this study, the customer's emotional image data, that is, atypical data based on the customer's cultural and leisure activities, is acquired through SNS and the customer's activity image is analyzed with an artificial intelligence CNN algorithm. Activity analysis is again applied to the annotated AI, and the AI big data model is designed to analyze the behavior model shown in the annotation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1148-1157
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• 2022

In 2019, COVID-19 changed many people's lives. Among them, metaverse supports non-face-to-face services through various methods, replacing daily tasks. This phenomenon was created and formed like a culture due to the prolonged COVID-19. In this paper, the fun elements used in the existing game were organized to find out the fun factors of the metaverse, and the items and contents were reclassified according to the metaverse with five experts. Classification was classified using reproducibility, sensory fun [graphic, auditory, text, manipulation, empathy, play, perspective], challenging fun [absorbedness, challenging, discovery, thrill, reward, problem-solving], imaginative fun [new story, love, freedom, agency, expectation, change], social fun[rules, competition, social behavior, status, cooperation, participation, exchange, belonging, currency transaction], interactive fun[decision making, communication sharing, hardware, empathy, nurturing, autonomy], realistic fun[sense of unity in reality, easy of learning, adaptation, intellectual problems solving, pattern recognition, sense of reality, community], and creative fun[application, creation, customizing, virtual world].

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.53-79
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• 2021

With the revitalization of non-face-to-face transactions, the difference between the size of branches and transaction costs among securities firms has decreased, and the importance of the stock trading system has increased. In particular, the mobile trading system has become more important due to the increase in the proportion of transactions in the mobile trading system, which is widely used by individual investors, and the increase in the number of individual investors after COVID-19. However, user-centered usability studies are insufficient as usability studies on mobile trading systems are conducted through literature surveys or survey methods. Therefore, in this study, a repertory grid technique that finds user's empirical perception was used to find out user-centered usability attributes. The usability attributes of the mobile trading system from the user's point of view were elicited, and the difference in the usability attributes in terms of frequency and importance between the user group and the developer group was identified.

• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.119-134
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• 2014

Financial companies are providing electronic financial transactions through a variety of user terminals for non-face-to-face services such as Internet banking, smart phone banking, or etc. However, in these services users' security awareness and the limitations of technical responses has frequently caused the financial loss so that fundamental protection measures are required from financial authorities. Accordingly, financial industry is planning and establishing systems that block unusual financial transactions by comprehensively analyzing and detecting user's electronic information, access information, transaction information, and so on in accordance with "Guide for building Unusual financial transactions detection system" to prevent the financial loss that happens in electronic financial transactions. In this paper, we analyze case studies of unusual financial transactions detection and prevention system that is built and operated in financial companies and current operating status and propose effects of the accident prevention and security measures later.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Journal of Distribution Science
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• v.10 no.2
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• pp.29-41
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• 2012

This paper undertakes a conceptual review of transaction cost to broaden the understanding of the transaction cost analysis (TCA) approach. More than 40 years have passed since Coase's fundamental insight that transaction, coordination, and contracting costs must be considered explicitly in explaining the extent of vertical integration. Coase (1937) forced economists to identify previously neglected constraints on the trading process to foster efficient intrafirm, rather than interfirm, transactions. The transaction cost approach to economic organization study regards transactions as the basic units of analysis and holds that understanding transaction cost economy is central to organizational study. The approach applies to determining efficient boundaries, as between firms and markets, and to internal transaction organization, including employment relations design. TCA, developed principally by Oliver Williamson (1975,1979,1981a) blends institutional economics, organizational theory, and contract law. Further progress in transaction costs research awaits the identification of critical dimensions in which transaction costs differ and an examination of the economizing properties of alternative institutional modes for organizing transactions. The crucial investment distinction is: To what degree are transaction-specific (non-marketable) expenses incurred? Unspecialized items pose few hazards, since buyers can turn toalternative sources, and suppliers can sell output intended for one order to other buyers. Non-marketability problems arise when specific parties' identities have important cost-bearing consequences. Transactions of this kind are labeled idiosyncratic. The summarized results of the review are as follows. First, firms' distribution decisions often prompt examination of the make-or-buy question: Should a marketing activity be performed within the organization by company employees or contracted to an external agent? Second, manufacturers introducing an industrial product to a foreign market face a difficult decision. Should the product be marketed primarily by captive agents (the company sales force and distribution division) or independent intermediaries (outside sales agents and distribution)? Third, the authors develop a theoretical extension to the basic transaction cost model by combining insights from various theories with the TCA approach. Fourth, other such extensions are likely required for the general model to be applied to different channel situations. It is naive to assume the basic model appliesacross markedly different channel contexts without modifications and extensions. Although this study contributes to scholastic research, it is limited by several factors. First, the theoretical perspective of TCA has attracted considerable recent interest in the area of marketing channels. The analysis aims to match the properties of efficient governance structures with the attributes of the transaction. Second, empirical evidence about TCA's basic propositions is sketchy. Apart from Anderson's (1985) study of the vertical integration of the selling function and John's (1984) study of opportunism by franchised dealers, virtually no marketing studies involving the constructs implicated in the analysis have been reported. We hope, therefore, that further research will clarify distinctions between the different aspects of specific assets. Another important line of future research is the integration of efficiency-oriented TCA with organizational approaches that emphasize specific assets' conceptual definition and industry structure. Finally, research of transaction costs, uncertainty, opportunism, and switching costs is critical to future study.

• Korea Trade Review
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• v.42 no.5
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• pp.233-252
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• 2017

The fast changes of global financial environment in recent years increase the risk of trade settlement. This means are required to minimize risk of non payment and to maximize secure payment. Open Account trade accounts for 90% of global trade flows. The O/A system means that the goods, along with all the necessary documents, are shipped and delivered before payment is due, usually within a time frame from 30 to 90 days. Meanwhile, Korean small and medium-sized export enterprises are compelled to globalize their activities owing to limitation and competitiveness of domestic marketplace. To keep face with the global trade settlement system and to support globalization of small and medium-sized export firms, the BPO together with Supply Chain Finance will be solutions. The introduction of the BPO system will allow banks to broaden O/A offerings to their client base and due to secure safety, sellers could ship the goods without delay according to orders and buyers could settle promptly by payment undertaking of correspondent banks. Therefore, it is more effective for companies which have sustainable customers and stable transaction. This study take a look at the trend of the global payment systems and suggested limitation of existed payment in order to derive improvement measures of electronic payment for small and medium-sized export enterprises.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.143-151
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• 2008

74% of Internet users use the UCC, and You Tube using firearms in a crime occurred. Internet crime occurred in the online, non-face transaction, anonymous, encapsulation. In this paper, we are studied a Network Forensic Way and a technique analyze an aspect criminal the Internet haying appeared at Internet UCC, and to chase. Study ID, IP back-tracking and position chase through corroborative facts collections of the UCC which used UCC search way study of the police and a public prosecutor and storage way and network forensic related to crimes of Internet UCC. Proof data encrypt, and store, and study through approach control and user authentication so that they are adopted to legal proof data through integrity verification after transmission and storages. This research via the Internet and criminal conspiracy to block the advance promotion, and for the criminal investigative agencies of the Internet will contribute to the advancement forensics research.