• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.87-96
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• 2024

Information power has been a major criterion for wealth disparity in human history, and since the advent of the Fourth Industrial Revolution, referred to as the data economy era, personal information has also gained economic value. Additionally, companies collect and analyze customer information to use as a marketing tool, providing personalized services, making the collection of quality customer information crucial to a company's success. However, as the amount of data held by companies increases, crimes of stealing personal information for financial gain have surged, making corporate customer information a target for criminals. The leakage of personal information and its circumstances lead to a decline in corporate trust from the customer's perspective, threatening corporate sustainability with falling stock prices and decreased sales. Therefore, companies find themselves in a paradoxical situation where the utilization of personal information is increasing while the risk of personal information leakage is also growing. This study used the news big data analysis system, BIG KINDS, to analyze major keywords before and after media coverage on personal information leaks, examining domestic media coverage trends. Through this, we identified the impact of personal information leakage on corporate sustainability and analyzed the connection between personal information protection and sustainable corporate management. The results derived from this study are expected to serve as foundational data for companies seeking ways to enhance sustainable management while increasing the utilization of personal information.

• The Journal of Bigdata
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• v.7 no.2
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• pp.173-193
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• 2022

With the revision of the Data 3 Act, the financial MyData industry was created newly. MyData services collect the financial customers' data scattered in various financial companies and provide personalized services such as personal financial product recommendation, personal expenditure advice, etc. Although MyData service started in 2022, but the use of the service has not been significantly activated. This study attempted to analyze the factors affecting the use of MyData services from the perspective of financial consumers through VAM, UTAUT2 model. The factors related to the perceived value and intention to use MyData services of financial consumers were verified using benefit and sacrifice variables. Personal Innovativeness was used as a moderating variable. As a result of this study, it was found that personal product recommendation service has an important influence on the use of MyData services, and personal innovativeness has an effect as a modulating variable. It can be said that it is meaningful as a preceding study in terms of timing because it studied the perceived value of consumers less than a year after the MyData service began. From the practical perspectives, it was possible to show the change direction and marketing points of the MyData service. In practice, it was possible to confirm the direction of the service and the marketing point.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.101-102
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• 2014

Results of Investment mean not results of procedure but the final goal of an organization. That is to say, results focus on success or failure of investment. So, cost effectiveness means financial cost that is affected in order to attain the output of organizational goal. Many enterprises are investing in developing and redeveloping various projects of information systems. But, it is not generally considered to check values with monitoring and evaluating their projects. We propose a new value model for information systems investment.

• Korean Security Journal
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• no.62
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• pp.185-203
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• 2020

While overall crime has been on the decline since 2009, voice phishing has rather been on the rise. The government and academia have presented various measures and conducted research to eradicate it, but it is not enough to catch up with evolving voice phishing. In the study, researchers focused on catching criminals and preventing damage from voice phishing, which is difficult to recover from. In particular, a voice phishing prediction method using the Fraud Detection System (FDS), which is being used to detect financial fraud, was studied based on the fact that the victim engaged in financial transaction activities (such as account transfers). As a result, it was conceptually derived to combine big data such as call details, messenger details, abnormal accounts, voice phishing type and 112 report related to voice phishing in machine learning-based Fraud Detection System(FDS). In this study, the research focused mainly on government measures and literature research on the use of big data. However, limitations in data collection and security concerns in FDS have not provided a specific model. However, it is meaningful that the concept of voice phishing responses that converge FDS with the types of data needed for machine learning was presented for the first time in the absence of prior research. Based on this research, it is hoped that 'Voice Phishing Damage Prediction System' will be developed to prevent damage from voice phishing.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.45-54
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• 2019

This study examines whether auditors restrain the analysts' opportunistic behavior as reviewing the companies' interim reports. Analysts' forecasts show a walkdown pattern in which their optimism has decreased as the earnings announcement date has approached. At the beginning of the year, there is a lack of high-quality benchmark information that enables information users to judge the accuracy of analyst's earnings forecasts. Thus, early in the year, analysts are highly inspired to disseminate optimistic forecasts in order to gain manager's favor. In this study, we examine adequate benchmarks prevent analysts from disclosing optimistically biased forecasts. We conjecture that auditors' efforts might mitigate analysts' walkdown pattern. To test this hypothesis, we use data from Korea, where it is mandatory to disclose auditor's review hours. We find that the analyst forecast's walkdown decreases with the ratio as well as the number of audit hours. It implies that an auditor's effort in reviewing interim financial information has a monitoring function that reduces analysts' opportunistic optimism at the beginning of the year. We conjecture that the tendency will be more pronounced when BIG4 auditors review the interim reports. Consistent with the prediction, BIG4 auditors' interim review effort is more effective in suppressing the analysts' walkdown.

• The Journal of Bigdata
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• v.7 no.2
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• pp.43-73
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• 2022

In order to improve productivity, reduce costs, and improve decision-making efficiency, which are one of the main contents of the digital transformation promotion goal, many companies are promoting the introduction of various IT for digital transformation. Information technology (IT) is a key means of determining competitiveness, and the IT adoption worldwide is increasing every year. The financial industry is also actively introducing huge amounts of IT every year to generate profits, improve work efficiency, and secure a strategic competitive advantage. Compared to some studies on the IT adoption in the public and corporate sectors, empirical studies that reflect the characteristics of the financial industry are insufficient. In this study, the purpose of this study was to derive factors affecting the IT adoption in the financial industry for the promotion of digital transformation, and to analyze weights and priorities. By revealing through data analysis that there is a difference in the relative priorities of factors in the financial IT adoption for each group, it can be used as a reference model for which factors should be considered prior to IT adoption from the perspective of each group. It will be meaningful in that it exists.

• The Journal of Bigdata
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• v.6 no.1
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• pp.91-113
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• 2021

Despite the influence of real estate in the Korean asset market, it is not easy to predict market trends, and among them, apartments are not easy to predict because they are both residential spaces and contain investment properties. Factors affecting apartment prices vary and regional characteristics should also be considered. This study was conducted to compare the factors and characteristics that affect apartment prices in Seoul as a whole, 3 Gangnam districts, Nowon, Dobong, Gangbuk, Geumcheon, Gwanak and Guro districts and to understand the possibility of price prediction based on this. The analysis used machine learning algorithms such as neural networks, CHAID, linear regression, and random forests. The most important factor affecting the average selling price of all apartments in Seoul was the government's policy element, and easing policies such as easing transaction regulations and easing financial regulations were highly influential. In the case of the three Gangnam districts, the policy influence was low, and in the case of Gangnam-gu District, housing supply was the most important factor. On the other hand, 6 mid-lower-level districts saw government policies act as important variables and were commonly influenced by financial regulatory policies.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.181-189
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• 2022

The purpose of this study is to investigate the innovation of business model and the effectiveness of the data-driven model. the main concepts and policies related to the data economy are reviewed, and implications are drawn through the analysis of data-based convergence service creation cases. This study identified the existing data-driven business model of the creation of MyData service industry in the financial industry and concept of the data economy. According to the empirical analysis result, this study confirmed that t considering the mobile environment and consumer acceptance of data portability, the ripple effect of the implementation of My Data on the financial industry is expected to be significant.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.153-169
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• 2018

Previous e-financial anomalies analysis and detection technology collects large amounts of electronic financial transaction logs generated from electronic financial business systems into big-data-based storage space. And it detects abnormal transactions in real time using detection rules that analyze transaction pattern profiling of existing customers and various accident transactions. However, deep analysis such as attempts to access e-finance by insiders of financial institutions with large scale of damages and social ripple effects and stealing important information from e-financial users through bypass of internal control environments is not conducted. This paper analyzes the management status of e-financial security programs of financial companies and draws the possibility that they are allies in security control of insiders who exploit vulnerability in management. In order to efficiently respond to this problem, it will present a comprehensive e-financial security management environment linked to insider threat monitoring as well as the existing e-financial transaction detection system.

• The Journal of Small Business Innovation
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• v.20 no.3
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• pp.49-68
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• 2017

Platform finance is emerging as an alternative finance for SMEs by suggesting a new funding source based on a new technology named FinTech. The essence of this business is the adapting ICT challenges to the financial industry that can adequately reflect risk assessment using Big Data and effectively meet individual risk-return preference. Thus, this is evolving as an alternative to existing finance in the form of P2P loans for Micro Enterprises and supply-chain finance for SMEs that need more working capital. Platform finance in Korea, however, is still at an infant stage and requires policy support. This can be summarized as follows: "Participation of institutional investors and the public sector," meaning that public investors provide seed money for the private investors to crowd in for platform finance. "Negative system in financial regulations," with current regulations to be deferred for new projects, such as Sandbox in the UK. In addition, "Environment for generous use of data," allowing discretionary data sharing for new products," and "Spreading alternative investments," fostering platform finance products as alternative investments in the low interest-rate era.