• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1293-1308
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• 2014

The cause of privacy extrusion in credit card company at 2014 is usage of the original data in test system. By Electronic banking supervision regulations of the Financial Supervisory Service and Information Security business best practices of Finance information technology (IT) sector, the data to identify the customer in the test system should be used to convert. Following this guidelines, Financial firms use converted customer identificaion data by loading in test system. However, there is some risks that may be introduced unintentionally by user mistake or lack of administrative or technical security in the process of testing. also control and risk management processes for those risks did not studied. These situations are conducive to increasing the compliance violation possibility of supervisory institution. So in this paper, we present and prove the process to eliminate the compliance violation possibility of supervisory institution by controlling and managing the unidentified conversion customer identification data and check the effectiveness of the process.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.145-158
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• 2017

Lately, rapid increase of household debt and economic change has affected cash flow of household, insolvent risk has increased by high repayment burden of the principal and interest. Previous researches was progressing various discussion, composed objective repayment burden index about household debt. But it was relatively insufficient about perception of consumer. This research compare and analysis determinants of subjective repayment burden in household debt by income quintile, using 2016 Household Financial Welfare Survey. The research result is follows. The income 1 and 2 quartile groups have the higher monthly rent and credit card loan and the housing preparation loan ratio, the higher burden on repayment of the principal and interest. The Income 3 and 4 quartile groups have the higher 60s or older and member of household and real estate mortgage loan, the higher burden on repayment of the principal and interest. The Income 5 quartile group has the higher loan ratio for debt repayment preparation, the higher burden on repayment of the principal and interest.

• Journal of Platform Technology
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• v.8 no.1
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• pp.10-15
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• 2020

Recently, various industrial sectors have introduced cloud service actively in their business because cloud computing technology enables storage·management and analysis·utilization of data easily in anytime, anywhere. Especially in financial sector, the business provocatively adopted the service and creates various innovative cases; furthermore, already in abroad, the sector has been accelerating digitization of analysis in cases of credit risk, financial fraud data, stock trading etc. On the contrary, in the domestic financial industry, not only the cloud service introduction and innovation cases are underperformed, but most of them are focused on the back-office service. Most Korean financial corporations are burdened with the adoption of cloud service due to various conservative regulatory requirements, such as regulations on data storage and management, regulations on privacy, and other tasks such as developing decision models and establishing responsibility standard for security incidents and service failures. In this study, it would be aimed to contribute to promote the introduction of the cloud in the domestic financial sector by drawing up preemptive challenges and inspecting priorities.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.109-116
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• 2022

The article is devoted to perfecting the system of management of the financial potential of transport enterprises. It is established that transport as an integral part of the state economy has to organically enter the market economy and provide sustainable transport services to national economy enterprises regardless of ownership, as well as ensure passenger transportation. It is also determined that in the conditions of market relations, transport highways must perform their functions with sufficient economic benefit to keep their material and technical resources in good order, conduct an investment policy with extensive use of scientific and technological progress, as well as a social policy guaranteeing the conditions for employees' motivated work. The study reveals an association between the financial and strategic goals of transport enterprises and the minimization of their economic risks, the prevention of bankruptcy and profit margin shortfalls. It is found that transport enterprises need to strive for the overall improvement of their financial potential through increasing the components of financial potential and assessing the impact of risk factors on them: the capacity of fixed assets, the capacity of financial resources, the capacity of services, and the capacity of credit opportunities. These are the elements of transport enterprises' financial potential that ensure its desired level. It is demonstrated that of critical importance in managing the financial potential of a transport enterprise is the role of financial resources, as a subject cannot reach the desired strategic goals without them.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.405-416
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• 2022

Current AI technology is improving the quality of life by using machine learning based on data. When using machine learning, transmitting distributed data and collecting it in one place goes through a de-identification process because there is a risk of privacy infringement. De-identification data causes information damage and omission, which degrades the performance of the machine learning process and complicates the preprocessing process. Accordingly, Google announced joint learning in 2016, a method of de-identifying data and learning without the process of collecting data into one server. This paper analyzed the effectiveness by comparing the difference between the learning performance of data that went through the de-identification process of K anonymity and differential privacy reproduction data using actual financial data. As a result of the experiment, the accuracy of original data learning was 79% for k=2, 76% for k=5, 52% for k=7, 50% for 𝜖=1, and 82% for 𝜖=0.1, and 86% for Federated learning.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.45-59
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• 2022

Purpose - This study investigates the performance of investment strategies incorporating estimated stock market cycle based on a lead-lag relationship between business cycle and stock market cycle, thereby deriving empirical implications on risk management. Design/methodology/approach - The data period ranges from June 1953 to September 2022 and de-trended short rate, term spread, credit spread, stock market volatility are considered as major input variables to estimate business cycle and stock market cycle by applying probit model. Based on the estimated stock market cycle, two types of strategies are constructed and their performance relative to the benchmark is empirically examined. Findings Two types of strategies based on stock market cycle are considered: The first strategy is to long(short) on stocks when stock market stage is expected to be an expansion(a recession), and the second one is to long on stocks(bonds) when expecting an expansion(a recession). The empirical results show that the strategies based on stock market cycle outperforms a simple buy and hold strategy in both in-sample and out-of-sample investigation. Also the out-of-sample evidence suggests that the second strategy which is in line with asset allocation is more profitable than the first one. Research implications or Originality The strategies considered in this study are based on the estimated stock market cycle which only depends on a few easily available financial variables, thereby making easier to establish such a strategy. It implies that investors enhance investment performance by constructing a relatively simple trading strategies if they set their position on stocks or choose which asset class to buy conditioning on stock market cycle.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.5 no.4
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• pp.1-34
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• 2010

Recently, failure rates of Kosdaq IPO firms are increasing and their survival rates tend to be very low, and when these firms do fail, often times backed by a number of governmental financial supports, they may inflict severe financial damage to investors, let alone economy as a whole. To ensure investors' confidence in Kosdaq and foster promising and healthy businesses, it is necessary to precisely assess their intrinsic values and survivability. This study investigates what contributed to the failure of IPO firms and analyzed how these elements are factored into corresponding firms' stock returns. Failure risks are assessed at the time of IPO. This paper considers factors reflecting IPO characteristics, a firm's underwriter prestige, auditor's quality, IPO offer price, firm's age, and IPO proceeds. The study further went on to examine how, if at all, these failure risks involved during IPO led to post-IPO stock prices. Sample firms used in this study include 98 Kosdaq firms that have failed and 569 healthy firms that are classified into the same business categories, and Logit models are used in estimate the probability of failure. Empirical results indicate that auditor's quality, IPO offer price, firm's age, and IPO proceeds shown significant relevance to failure risks at the time of IPO. Of other variables, firm's size and ROA, previously deemed significantly related to failure risks, in fact do not show significant relevance to those risks, whereas financial leverage does. This illustrates the efficacy of a model that appropriately reflects the attributes of IPO firms. Also, even though R&D expenditures were believed to be value relevant by previous studies, this study reveals that R&D is not a significant factor related to failure risks. In examing the relation between failure risks and stock prices, this study finds that failure risks are negatively related to 1 or 2 year size-adjusted abnormal returns after IPO. The results of this study may provide useful knowledge for government regulatory officials in contemplating pertinent policy and for credit analysts in their proper evaluation of a firm's credit standing.

• Management & Information Systems Review
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• v.28 no.3
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• pp.1-23
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• 2009

Prior bankruptcy studies have established that bankrupt firm's pre-filing financial ratios are different from those of healthy firms or of randomly selected going concerns. However, they may not be sufficiently different from the financial ratios of other firms in financial distress to allow the development of a ratio-based model that predicts bankruptcy with reasonable accuracy. As the result, in the multiple discriminant model, independent variables divided firms into bankrupt firms and healthy firms are retained earnings to total asset, receivable turnover, net income to sales, financial expenses, inventory turnover, owner's equity to total asset, cash flow to current liability, and current asset to current liability. Moreover four variables Retained earnings to total asset, net income to sales, total asset turnover, owner's equity to total asset indicate that these valuables classify bankrupt firms and distress firms. On the other hand, Owner's Equity to borrowed capital, Ordinary income to Net Sales, Operating Income to Total Asset, Total Asset Turnover and Inventory Turnover are selected to predict bankruptcy possibility in the Logistic regression model.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.1
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• pp.133-141
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• 2016

Although construction of any new nuclear power projects had not been launched since mid-1970s until recently in the USA, many new nuclear power plants have been constructed in many countries with the support of their governments mainly as part of their national energy security and electric source diversification policies. For many reasons, the nuclear power industry seemed to reclaim their renaissance from the beginning of this century and the investment in the nuclear power projects draw positive concern from the private financial sector. But the global financial crisis in 2008 and subsequent economic slow-down together with tighter bank credit regulations caused commercial banks, the main source of financing, to lose appetite for investing in new nuclear power projects. But the nuclear power economics shows that the nuclear power is viable in terms of the environmental benefit and long-term average cost compared to other power generation sources. Also doubt about nuclear power safety was much mitigated due to technology development and reinforced safety-related tests and monitoring. Therefore, the prospect for nuclear power market expansion remains positive although there are comparatively big differences among different scenarios. After Korea Electric Power Corp. won the UAE nuclear power project in December of 2009, the competition in nuclear power markets is undergoing huge changes. Competitors backed by the support of their own governments are now entering the market with many aggressive and innovative financing packages to win bids of new nuclear power projects. This report analyzed the nuclear power market prospects, competitive edges of nuclear power, risk management measures, and financing challenges and recommends alternative solutions to promote competitive edges in winning bids of new nuclear power projects.