• Journal of Information Technology Services
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• v.19 no.2
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• pp.109-124
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• 2020

Facing the 4^th Industrial Revolution era, researches on artificial intelligence have become active and attempts have been made to apply machine learning in various fields. In the field of finance, Robo Advisor service, which analyze the market, make investment decisions and allocate assets instead of people, are rapidly expanding. The stock price prediction using the machine learning that has been carried out to date is mainly based on the prediction of the market index such as KOSPI, and utilizes technical data that is fundamental index or price derivative index using financial statement. However, most researches have proceeded without any explicit verification of the prediction rate of the learning data. In this study, we conducted an experiment to determine the degree of market prediction ability of basic indicators, technical indicators, and system risk indicators (AR) used in stock price prediction. First, we set the core parameters for each financial indicator and define the objective function reflecting the return and volatility. Then, an experiment was performed to extract the sample from the distribution of each parameter by the Markov chain Monte Carlo (MCMC) method and to find the optimum value to maximize the objective function. Since Robo Advisor is a commodity that trades financial instruments such as stocks and funds, it can not be utilized only by forecasting the market index. The sample for this experiment is data of 17 years of 1,500 stocks that have been listed in Korea for more than 5 years after listing. As a result of the experiment, it was possible to establish a meaningful trading strategy that exceeds the market return. This study can be utilized as a basis for the development of Robo Advisor products in that it includes a large proportion of listed stocks in Korea, rather than an experiment on a single index, and verifies market predictability of various financial indicators.

• Journal of Korean Society of Archives and Records Management
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• v.20 no.4
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• pp.1-17
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• 2020

Along with the development of information technology, the digitalization of archives has also been accelerating. However, digital archives have limitations in effectively searching, interlinking, and understanding records. In response to these issues, this study proposes a knowledge graph that represents comprehensive relationships among heterogeneous entities in digital archives. In this case, the knowledge graph organizes resources in the archives on the Korean financial crisis of 1997 by transforming them into named entities that can be discovered by machines. In particular, the study investigates and creates an overview of the characteristics of the archives on the Korean financial crisis as a digital archive. All resources on the archives are described as entities that have relationships with other entities using semantic vocabularies, such as Records in Contexts-Ontology (RiC-O). Moreover, the knowledge graph of the Korean Financial Crisis of 1997 is represented by resource description framework (RDF) vocabularies, a machine-readable format. Compared to conventional digital archives, the knowledge graph enables users to retrieve a specific entity with its semantic information and discover its relationships with other entities. As a result, the knowledge graph can be used for semantic search and various intelligent services.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.4
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• pp.705-719
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• 2014

Recently the importance of operational risk is gradually increasing in risk management of financial institute. Especially the service interruption caused by system failure can lead to customer complaints, decrease of profit and customer secession. Thus, financial industry makes diverse effort to minimize the impact caused by the system failure of IT application. Common modules are used in IT system in financial industry to exclude redundant development and to use the system efficiently. However, when a failure in common module is occurred, the risk that affects all the tasks using the common module exists. In this study, the damage affected by a failure in application program is prevented separating common module which has a large risk by task in the perspective of IT operational risk. In order to cope with damage, the research on the factors related to common module is conducted and proposes the separating common module standard for decrease of operational risk of the financial IT.

• Convergence Security Journal
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• v.15 no.5
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• pp.17-22
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• 2015

As financial deregulation policies implemented by the government, electronic financial service is improved but security concerns are increasing and ultimately weaken trust in the financial service. Electronic financial service becomes more and more dependant on the IT platform and the initiatives of access device is also gradually shift to that platform. As biometric sensor is mounted on the smartphone, structural change in the access device is coming. It must be a positive signs in terms of fintech development, in the other side, it can cause many problems such as weakness of regulation and ambiguity of principals of responsibility. So in this paper, by analysing this problem-the shift of service initiative-on the access device I'll propose the best way to the the legal amendments.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.223-233
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• 2021

MyData industry became possible with the revision of the three data-related bills on August 2020, and from February 2021, each individual can make MyData financial service through the app provided by MyData providers. In this study, in order to understand the user experience trend of MyData-based financial asset management apps in the user-centered financial service era, the usability evaluation of 11 apps from 8 MyData providers was conducted for 300 adults, then average value comparison, radial graph analysis, and heatmap analysis were conducted. In app design preference, asset list type was the most preferred type, followed by asset comparison·list type. As for the expected perception of the future benefits that can be enjoyed through My Data, 'diversification of convenient services' was the highest at 45.3%, and as a negative factor felt by users, personal information-related factors were the highest at 71.4%. The results of this study can be used as basic data for the development and improvement of user interfaces for MyData platforms.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1563-1583
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• 2018

With the deregulation of electronic finance, FinTech has been revitalized. The discussion on artificial intelligence is active in the financial industry. However, there is a problem of increasing security threats behind new technologies. Security vulnerabilities have increased because we are more connected than before, and the channels and entities of the financial industry have diversified. Although there are technical and policy discussions on security, the essence of all discussions is human. Fundamentals of finance are trust and security, and attention to human factors is important. This study presents the role of human and artificial intelligence for financial security, respectively. Furthermore, this derives a collaborative model in which human and artificial intelligence complement each other's limitations. To support this, it first discusses the development of finance and IT, AI, human factors, and financial security threats. This study suggests that the security threats will intensify in the era of new technology, but it can overcome them by using machinery and technology.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.1
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• pp.83-95
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• 2021

In this study, major research trends at home and abroad were compared and analyzed in order to derive key research fields in the financial security field and to suggest directions. To this end, 689 domestic and 20,736 foreign data were collected from domestic and international academic journal DB, and major research fields related to financial security were extracted through LDA analysis. After that, hot & cold topics were derived through time series linear regression analysis. As a result of the analysis, studies related to government policy issues, personal information, and accredited certification were derived as promising research fields in Korea. In the case of foreign countries, related studies were drawn to develop advanced security systems such as cryptographic protocols and quantum security. Recently, it has become possible to apply various security technologies in Korea through the abolition of public certification. Accordingly, as changes in promising research fields are expected, the results of this study are expected to contribute to the establishment and development of a successful roadmap for domestic financial security.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.335-356
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• 2022

Universities contribute to the development of the country and society by cultivating professional manpower with knowledge and qualifications as democratic citizens through education and research activities. To this end, the government is improving the basic capabilities of universities and supporting autonomous innovation through university financial support projects. Since the financial support project differentially supports the government's finances limited to universities with a comparative advantage through fair evaluation, the role and function of the university library, a basic educational facility and core institution that supports education and research, is important. However, university libraries have not been able to actively participate in the government's financial support projects due to financial and manpower shortages, poor environments such as facilities, facilities, and spaces, and low participation rates for students. Therefore, this study investigated and analyzed the program operation cases of 18 university libraries in which libraries participated among 45 universities selected for the ACE project (2010-2016), derived problems and implications, and questioned the roles and achievements of university libraries. Based on the results, strategies and measures to be considered by university libraries in preparation for the government's university financial support projects were proposed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.32-41
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• 2023

Recently, many studies are being conducted to extract emotion from text and verify its information power in the field of finance, along with the recent development of big data analysis technology. A number of prior studies use pre-defined sentiment dictionaries or machine learning methods to extract sentiment from the financial documents. However, both methods have the disadvantage of being labor-intensive and subjective because it requires a manual sentiment learning process. In this study, we developed a financial sentiment dictionary that automatically extracts sentiment from the body text of analyst reports by using modified Bayes rule and verified the performance of the model through a binary classification model which predicts actual stock price movements. As a result of the prediction, it was found that the proposed financial dictionary from this research has about 4% better predictive power for actual stock price movements than the representative Loughran and McDonald's (2011) financial dictionary. The sentiment extraction method proposed in this study enables efficient and objective judgment because it automatically learns the sentiment of words using both the change in target price and the cumulative abnormal returns. In addition, the dictionary can be easily updated by re-calculating conditional probabilities. The results of this study are expected to be readily expandable and applicable not only to analyst reports, but also to financial field texts such as performance reports, IR reports, press articles, and social media.

• Journal of Korea Port Economic Association
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• v.19 no.2
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• pp.159-175
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• 2003

The purpose of this paper is to investigate the development strategy for the Hub of Northeast Asia. Those countries such as Singapore, Taiwan, Hong Kong and China competing us are trying to concentrate on their core capacity. Based on the severe competition surrounding us, we are confronting with a transitional period to upgrade competitiveness. It is acknowledged that the building of economic hub of Northeast Asia is essential to become an advanced country. Therefore, it is becoming an urgent task that Korean government should formulate the development strategy of building efficient transportation network, economic special zone and financial hub.