• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.207-217
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• 2010

It is taken a violent fall of the international stocks market that was an American Subprime Mortgage Situation. The loss rate of individual investor judged than foreigner and institution by bigger thing. Therefore, further scientific and mechanical investment is needed at the stock investment using Internet HTS. This dissertation is stocks profit rate analysis which uses individual engine foreigner Knowledge Base HTS at the Bear Period the Bear Wave Period the Bull Period the Bull Wave Period. Knowledge Based e-friend HTS was Installed. HTS does composite stock exchange index in actuality stock trading and engine's fund earning rate, yield that is abroad comparative analysis using trend line that is HTS tool, MACD, Bollinger Bands, Stochastic slow's function. Usually, each subjects suppose that deal 5 stocks, and comparative study of the profit(loss)rate of the down to earth falling rate and rising rate, by comparing the earning rate of 5 Small capital stocks with 5 medium capital stocks and 5 Large capital stocks during the bear period, the bear wave period, the bull period, the bull wave period has meaning at the making research of the financial IT field.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.307-332
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• 2022

One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.365-385
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• 2022

The easy payment service is a payment and remittance service that uses a simple authentication method. As online transactions have increased due to COVID-19, the use of an easy payment service is increasing. At the same time, electronic financial industries such as Naver Pay, Kakao Pay, and Toss are diversifying the competition structure of the easy payment market; meanwhile overseas fintech companies PayPal and Alibaba have a unique market share in their own countries, while competition is intensifying in the domestic easy payment market, as there is no unique market share. In this study, the participants in the easy payment market were classified as electronic financial companies, mobile phone manufacturers, and financial companies, and a SWOT analysis was conducted on the representative services in each industry. The analysis examined the user reviews of Google Play Store via a topic modeling analysis, and it employed positive topics as strengths and negative topics as weaknesses. In addition, topic modeling was conducted by dividing news articles into political, economic, social, and technology (PEST) articles to derive the opportunities and threats to easy payment services. Through this research, we intend to confirm the service capabilities of easy payment companies and propose a service activation strategy that allows gaining the upper hand in the market.

• KDI Journal of Economic Policy
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• v.32 no.2
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• pp.171-216
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• 2010

With the payment and settlement systems becoming more and more complex and interconnected, the issue of their interdependency rises as an important academic issue as well as a policy topic. This study examines causes, forms, and risk management of interdependencies of payment and settlement systems in Korea, and presents their current situation. By way of simulations using BOF-PSS2 developed by the Bank of Finland, we quantify the effects of an operational disruption on the payment and settlement systems so as to figure out the degree of interdependency. As a result, the secondary round effect reaches up to ￦13.6 trillion a day, which amounts to 7.8% of the daily settlement value. Furthermore, if we also consider the amount of direct operational disruption, the volume of operational disruption occupies 22.3% of total value of the daily settlement, evidencing that the interdependencies of the payment and settlement systems in Korea is enormously widespread. The secondary round effects are found to be more severe with security companies rather than with banks, and to be more depended upon when it is perceived rather than it actually happens. In case that we expand the liquidity to include cash holdings and deposits as assets, the secondary round effect dramatically decreases in all types of financial institutions while foreign banks account for more share of all the secondary round effects increases. Based on these results, we suggest various policy tasks and directions to improve the risk management of settlement systems: expansion of off-setting settlements, introduction of a new settlement system for securities transactions, rapid provision of liquidity to financial institutions, more effective monitoring on participant institutions, and intensified information sharing and cooperation among the systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.43-54
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• 2016

The occurrence of cyber crime is on the rise every year, and the security control center, which should play a crucial role in monitoring and early response against the cyber attacks targeting various information systems, its importance has increased accordingly. Every endeavors to prevent cyber attacks is being attempted by information security personnel of government and financial sector's security control center, threat response Center, cyber terror response center, Cert Team, SOC(Security Operator Center) and else. The ordinary method to monitor cyber attacks consists of utilizing the security system or the network security device. It is anticipated, however, to be insufficient since this is simply one dimensional way of monitoring them based on signatures. There has been considerable improvement of the security control system and researchers also have conducted a number of studies on monitoring methods to prevent threats to security. In accordance with the environment changes from ESM to SIEM, the security control system is able to be provided with more input data as well as generate the correlation analysis which integrates the processed data, by extraction and parsing, into the potential scenarios of attack or threat. This article shows case studies how to detect the threat to security in effective ways, from the initial phase of the security control system to current SIEM circumstances. Furthermore, scenarios based security control systems rather than simple monitoring is introduced, and finally methods of producing the correlation analysis and its verification methods are presented. It is expected that this result contributes to the development of cyber attack monitoring system in other security centers.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.141-154
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• 2014

The adoption of International Financial Reporting Standards (IFRS) is the one of important issues in the recent accounting research because the change from local GAAP (Generally Accepted Accounting Principles) to IFRS has a substantial effect on accounting information. Over 100 countries including Australia, China, Canada and the European Union member countries adopt IFRS (International Financial Reporting Standards) for financial reporting purposes, and several more including the United States and Japan are considering the adoption of IFRS (International Financial Reporting Standards). In Korea, 61 firms voluntarily adopted Korean International Financial Reporting Standard (K-IFRS) in 2009 and 2010 and all listed firms mandatorily adopted K-IFRS (Korea-International Financial Reporting Standards) in 2011. The adoption of IFRS is expected to increase financial statement comparability, improve corporate transparency, increase the quality of financial reporting, and hence, provide benefits to investors This study investigates whether recognized accounts receivable discounting (AR discounting) under Korean International Financial Reporting Standard (K-IFRS) is more value relevant than disclosed AR discounting under Korean Generally Accepted Accounting Principles (K-GAAP). Because more rigorous standards are applied to the derecognition of AR discounting under K-IFRS(Korea-International Financial Reporting Standards), most AR discounting is recognized as a short term debt instead of being disclosed as a contingent liability unless all risks and rewards are transferred. In this research, I try to figure out industrial responses to the changes in accounting rules for the treatment of accounts receivable toward more strict standards in the recognition of sales which occurs with the adoption of Korea International Financial Reporting Standard. This study examines whether accounting information is more value-relevant, especially information on accounts receivable discounting (hereinafter, AR discounting) is value-relevant under K-IFRS (Korea-International Financial Reporting Standards). First, note that AR discounting involves the transfer of financial assets. Under Korean Generally Accepted Accounting Principles (K-GAAP), when firms discount AR to banks before the AR maturity, firms conventionally remove AR from the balance-sheet and report losses from AR discounting and disclose and explain the transactions in the footnotes. Under K-IFRS (Korea-International Financial Reporting Standards), however, most firms keep AR and add a short-term debt as same as discounted AR. This process increases the firms' leverage ratio and raises the concern to the firms about investors' reactions to worsening capital structures. Investors may experience the change in perceived risk of the firm. In the study sample, the average of AR discounting is 75.3 billion won (maximum 3.6 trillion won and minimum 18 million won), which is, on average 7.0% of assets (maximum 38.6% and minimum 0.002%), 26.2% of firms' accounts receivable (maximum 92.5% and minimum 0.003%) and 13.5% of total liabilities (maximum 69.5% and minimum 0.004%). After the adoption of K-IFRS (Korea-International Financial Reporting Standards), total liabilities increase by 13%p on average (maximum 103%p and minimum 0.004%p) attributable to AR discounting. The leverage ratio (total liabilities/total assets) increases by an average 2.4%p (maximum 16%p and minimum 0.001%p) and debt-to-equity ratio increases by average 14.6%p (maximum 134%p and minimum 0.006%) attributable to the recognition of AR discounting as a short-term debt. The structure of debts and equities of the companies engaging in factoring transactions are likely to be affected in the changes of accounting rule. I suggest that the changes in accounting provisions subsequent to Korea International Financial Reporting Standard adoption caused significant influence on the structure of firm's asset and liabilities. Due to this changes, the treatment of account receivable discounting have become critical. This paper proposes an intelligent diagnostic system for estimating negative impact on stock value with self-organizing maps and case based reasoning. To validate the usefulness of this proposed model, real data was analyzed. In order to get the significance of this proposed model, several models were compared to the research model. I found out that this proposed model provides satisfactory results with compared models.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.98-108
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• 2004

The concept of community capacity is regarded as the ability of people and communities to do works associated with the determinant factors and indicators of the circumstances of socio-economic, environmental and physical contexts. Building capacity of communities to effectively analyze our problematic issues and planning of community development is often required to scrutinize current status of community of socio-economic and infrastructural capacity development with GIS. We consider community development as a planned effort to build assets that increase the capacity of communities. Spatial asset mapping is the process enabling to identify and make inventories of tangible and intangible assets. This mapping requires developing a capacity inventory that collects individual organizational and community capacities in view of human, socio-cultural, natural, financial, digital, and physical capacity. The purpose of this research is not only designed to suggest a new concept capacity building, but also proposes a more creative framework of asset-based community cap linking to parcel-based spatial asset mapping and capacity mapping process.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.287-308
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• 2022

The explosive growth of cryptocurrency, led by Bitcoin has emerged as a major issue in the financial market recently. As a result, interest in cryptocurrency investment is increasing, but the market opens 24 hours and 365 days a year, price volatility, and exponentially increasing number of cryptocurrencies are provided as risks to cryptocurrency investors. For that reasons, It is raising the need for research to reduct investors' risks by dividing cryptocurrency which is not suitable for recommendation. Unlike the previous studies of maximizing returns by simply predicting the future of cryptocurrency prices or constructing cryptocurrency portfolios by focusing on returns, this paper reflects the tendencies of investors and presents an appropriate recommendation method with interpretation that can reduct investors' risks by selecting suitable Altcoins which are recommended using Apriori algorithm, one of the machine learning techniques, but based on the similarity and association rules of Bitocoin.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.869-874
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• 2005

In the recent years there has been an increase of service competition in the activity of product selling, especially in the extension of warranty coverage and qualify. The variables in connection with the service competition are not crisp, and required the expertise of the production line. It thus becomes all the more necessary to use subtler tools as decision supports. These problems are typical not only of product companies but also of financial organizations, credit institutions, insurance, which need predictions of credibility for firms or persons in which they have any kind of interest. A suitable approach for minimizing the risk is to use a knowledge-based system. Most often expert systems are not standalone programs, but are embedded into a larger application. The aim of this paper is to discuss an approach for developing an embedded fuzzy expert system with respect to the product selling policy, especially to present the decision system of automobile selling activity around the extension of warranty coverage and quality. We use the MATLAB tools which integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation. Also, we present the API functions embedding into the existing application.

• Maritime Security
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• v.4 no.1
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• pp.115-138
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• 2022

The Korean military is preparing for successful manpower reduction using advanced science and technology, in addition to carrying out the initiative of the Defense Innovation 4.0. Accordingly, studies on core technologies related to defense reform have been conducted both internally and externally in the military, and the corresponding results have also been applied. Nevertheless, compared to the development of such technologies, it is considered necessary to have more preparation for the policies related to the operation of the newly introduced equipment. As for the placement of personnel and the organization of time in service (TIS) with respect to the operation of surveillance equipment, there has been a tendency to sustain the conventional practice. Therefore, this study intends to suggest the schemes for facilitating policy improvements in the operation of manpower and security regulations in the field of information for the purpose of introducing a successful next-generation coastal guard system. To do this, the approach of this study was focused on the policies for the operation of the guard system. This is in contrast to previous studies that centered on its equipment and technologies. In addition, how to efficiently operate the guard system was also studied in view of cognitive science by deriving the most efficient time for a person to execute surveillance through the monitor based on the previous studies.