• The Korean Journal of Financial Management
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• v.23 no.2
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• pp.209-237
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• 2006

Since previous default forecasting models for the firms evaluate the probability of default based upon the accounting data from book values, they cannot reflect the changes in markets sensitively and they seem to lack theoretical background. The market-information based models, however, not only make use of market data for the default prediction, but also have strong theoretical background like Black-Scholes (1973) option theory. So, many firms recently use such market based model as KMV to forecast their default probabilities and to manage their credit risks. Korean firms also widely use the KMV model in which default point is defined by liquid debt plus 50% of fixed debt. Since the debt structures between Korean and American firms are significantly different, Korean firms should carefully use KMV model. In this study, we empirically investigate the importance of debt structure. In particular, we find the following facts: First, in Korea, fixed debts are more important than liquid debts in accurate prediction of default. Second, the percentage of fixed debt must be less than 20% when default point is calculated for Korean firms, which is different from the KMV. These facts give Korean firms some valuable implication about default forecasting and management of credit risk.

• Journal of the Society of Disaster Information
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• v.11 no.1
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• pp.121-133
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• 2015

A classical commercial insurance, which is used widely as the risk management methods for risk transferring and risk financing, includes the factors of interests, gambling and uncertainty, In 1985 Islamic Fiqc Academy declared that the classical commercial insurance violates the Islamic fundamental principles and beliefs, alteratively recommending a mutual insurance and takaful. A basic principle of takaful is the mutual aid in the Islamic community. On the basis of mutual aid, takaful participants (insurance policyholder) establishes the takaful fund, which is cooperation fund by participant contribution. Takaful fund is separated from shareholders' fund, and the profit and loss of takaful fund are responsible for takaful policyholder. Ownership and operation right of takaful belong to the takaful participants. In takaful, takaful company takes a role of agent or management operator. Comparing to the classical insurance, takaful has the rights of profit dividend, voting of executives, access to accounting books etc. which are additional favors for business company or individuals as takaful participants. Business companies and individuals should consider to use takaful to transfer risk and to enjoy takaful's additional advantages.

• Korean Journal of Construction Engineering and Management
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• v.11 no.1
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• pp.113-121
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• 2010

Since the cut-down of the purchasing price of the feed in tariff(FIT) in 2008, the numbers of photovoltaic projects get decreased, contrary to investment expansion policy of government on renewable energy. The root cause of the decrease is the irrationality of the current purchasing price structure of FIT as well as the adversity of fund raising due to the global financial crisis. This study proposes the FIT calculating model (Cost & Benefit Risk Based Purchase Price Process : CBRP3) reflecting the fluctuation of cost and benefit risks. The first step is to establish the photovoltaic generation alternatives, and to calculate each distribution data of the investment and the power generation quantity. The FIT for each alternative is, then, assessed through simulations. Finally the proposed FIT scheme is compared to the present FIT scheme and future study subjects are derived.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.123-131
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• 2016

Process mining in big data environment utilize a number of data were generated from the business process. It generates lots of knowledge and insights regarding implementation and improvement of the process through the event log of the company's enterprise resource planning (ERP) system. In recent years, various research activities engaged with the audit work of company organizations are trying actively by using the maximum strength of the mining process. However, domestic studies on applicable sales auditing system for the process mining are insufficient under big data environment. Therefore, we propose process-mining methods that can be optimally applied to online and traditional auditing system. In advance, we propose continuous monitoring information system that can early detect and prevent the risk under the big data environment by monitoring risk factors in the organizations of enterprise. The scope of the research of this paper is to design a pre-verification system for risk factor via practical examples in sales auditing. Furthermore, realizations of preventive audit, continuous monitoring for high risk, reduction of fraud, and timely action for violation of rules are enhanced by proposed sales auditing system. According to the simulation results, avoidance of financial risks, reduction of audit period, and improvement of audit quality are represented.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.109-121
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• 2023

This paper examines whether angel investors affect startup's financial performance (profitability and growth ratios) in the Korean startup market over 10 years period from 2009 to 2018. In particular, we consider not only the behavior of angel investor such as the investment amount or the type of investments (stocks, bonds) but also the type of angle investor (individual or corporation). Our empirical results are as follows. First, we find that the startup's profitability ratios are higher after the investment of angel investors. However, the growth ratios show different results in assets and sales. Second, we identify that the investment amount of angel investors negatively affects on the startup's growth ratios. Lastly, we find that equity investment such as common stock or preferred stock and the individual angel investors such as personal investment association or professional angels show higher financial performance than bond investment or corporate angel investors. Overall, our findings imply that angel investors positively affect startup's financial performance. In particular, we infer that the superior financial performance is largely attributed to monitor startups by participating as shareholders or to select more carefully by the individual angel investors who may be exposed to more investment risk. In conclusion, our findings support that angel investors play a positive role in the Korean venture investment market.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.229-249
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• 2022

This paper investigates machine learning models for predicting the designation of administrative issues in the KOSDAQ market through various techniques. When a company in the Korean stock market is designated as administrative issue, the market recognizes the event itself as negative information, causing losses to the company and investors. The purpose of this study is to evaluate alternative methods for developing a artificial intelligence service to examine a possibility to the designation of administrative issues early through the financial ratio of companies and to help investors manage portfolio risks. In this study, the independent variables used 21 financial ratios representing profitability, stability, activity, and growth. From 2011 to 2020, when K-IFRS was applied, financial data of companies in administrative issues and non-administrative issues stocks are sampled. Logistic regression analysis, decision tree, support vector machine, random forest, and LightGBM are used to predict the designation of administrative issues. According to the results of analysis, LightGBM with 82.73% classification accuracy is the best prediction model, and the prediction model with the lowest classification accuracy is a decision tree with 71.94% accuracy. As a result of checking the top three variables of the importance of variables in the decision tree-based learning model, the financial variables common in each model are ROE(Net profit) and Capital stock turnover ratio, which are relatively important variables in designating administrative issues. In general, it is confirmed that the learning model using the ensemble had higher predictive performance than the single learning model.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.577-580
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• 2003

The purpose of this study was to make a database model for financial feasibility study of buildings offered for sale which is helpful for improvement of business ability in construction and confidence of a project from a related participant. At first, we studied several thesis and met some professionalist which work for construction and did a first survey for examining latest situation of a feasibility study in construction. As a result, even though feasibility study is important, factors for information management wasn't systemized. So we did a second survey for fixing Factors of the database model. The database model was composed of the factors that we got from the second survey. ER(Entity-Relationship) analysis was used to making it. We expect thar we can get more reasonable information to study financial feasibility study and can diminish risks of project through the database model. So the result of this study was to make a database model for more reasonable financial feasibility study of building offered for sale.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.405-408
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• 2005

현대 기업 환경에서 리스크 관리의 중요성이 증가함에 따라 기업도산예측을 위한 다양한 통계모형들이 개발되었다. 그러나 이러한 모형들은 기업도산에 영향을 미치는 변수들에 대한 사후적 정보와 함께 도산여부에 대한 사전적 정보를 반드시 필요로 하는 한계가 있다. 이에 따라 DEA가 기업도산예측을 위한 대안으로 연구되고 있다. DEA는 도산여부에 대한 사전적 정보 없이 사후적인 정보만을 가지고 의사결정단위(DMU)의 효율성(재무신뢰도)을 측정할 수 있는 장점이 있다. 그러나 지금까지 기업도산예측에 활용된 DEA 모형은 바람직하지 않은 산출물(negative outputs)은 다루지 못하는 한계가 있었다. 이에 본 논문에서는 Negative DEA 방법을 소개하고, 이를 기존의 DEA 방법과 병행하여 기업도산예측에 적용함으로써 기업도산예측을 위한 대안적 방법을 제시하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.354-357
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• 2018

본 연구의 목적은 저축은행 부실에 영향을 미치는 주요 변수를 선정하고, 기존 전통적인 통계기법에 국한된 국내 부실 예측 연구를 벗어나 기계학습을 활용하여 부설 예측모형에 대한 성능을 향상시키는 것이다. 이를 위해 본 연구는 2010년부터 2014년까지의 부실저축은행 297개사와 건전 저축은행 88 개사의 재무정보 1,5067개 분기자료를 기반으로 로지스틱회귀분석 뿐만 아니라, ANN, SVM 및 Decision Tree와 같은 알고리즘을 이용하여 보다 정교한 부실 예측 모형을 개발하고 활용함으로써 금융기관에 대한 리스크 상시 감시를 통해 부실을 사전에 예방하고 시장의 안정화 및 금융질서를 유지함을 목적으로 하고 있다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.635-647
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• 2006

Korean construction companies first advanced to the international markets in 1960's and so far have brought more than 4,900 projects which account for 193 billion dollars approximately. With the large increase of national employment and income being followed by the achievement, Korea's construction industry has made an enormous contribution to the improvement of domestic economy for the last 40 years. However, recently the increased risk in international markets as well as the sharpening competition with foreign companies promising in terms of advanced technologies and low labor cost have been driving Korean construction away from the market shares. According to ENR (Engineering News Record, 1994~2003), it is revealed that 15.1% of top 225 global contractors are suffering from loss in international construction markets. This phenomenon is largely due to the highly uncertain characteristics of international projects, which are inherently exposed to various and complicated risky situations. Furthermore, especially for Korean construction companies, it is often the case that the failure in an international construction project cannot be offset by even a sufficient number of successful domestic achievements. Therefore, not only the selective screening among the nominated projects which have strong possibility of collapse but the systematic strategies for controlling potential risk factors are also considered indispensable in international construction portfolio management. The purpose of this study is to first analyze the causal relationships of the profit-influencing variables and the project success, and develop the profitability forecasting model in international construction projects.