• 대기
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• 제34권1호
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• pp.1-21
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• 2024

Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.

• 기술혁신학회지
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• 제8권3호
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• pp.1087-1116
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• 2005

This research examines performance evaluatees' opinions regarding the institutional performance evaluation systems of Government S&T Research Institutes (GRI). Research methodology is as follows: first, four perspectives of Kaplan & Norton (1992) Balanced Scorecard Model are revised into six perspectives suitable to GRI's characteristics. Second, experts classify current performance evaluation measures into the six perspectives. This enables different evaluation systems of three GRI evaluation groups to be compared under the same evaluation measures. Third, GRI's evaluatees are asked to allocate ideal weights on the performance measures. The evaluatees' weights are compared with the weights of current performance measures, and the characteristics of evaluatees' opinions about current performance evaluation systems are analyzed. Results are as follows; first, six perspectives for Korean GRIs are financial, long-term outcome, short-term outcome, strategic direction, project management, human resources perspectives. second, GRI evaluation systems put the most weights on the long- and short-term outcome perspectives and the least weights on the financial perspective. This result complies with theoretical model: in performance evaluation of GRIs, the customer perspective is the most important one while the financial perspective is the least important one. Third, evaluatees think that the long-term outcome perspective of the Basic-technology GRI group and the short-term outcome perspective of the Applied-technology GRI Group needs more weight. Fourth, it is found that the current systems have more weights on the project management and strategic direction perspectives than evaluatees think. The possible explanation of this result would be that since the measures of these perspectives are relatively easier to set up than those of other perspectives, the current systems contains larger number of measures and, accordingly more weights.

• Journal of Information Technology Applications and Management
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• 제22권3호
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• pp.1-18
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• 2015

Financial markets are characterized by large numbers of complex and interacting factors which are ill-understood and frequently difficult to measure. Mathematical models developed in finance are precise formulations of theories of how these factors interact to produce the market value of financial asset. While these models are quite good at predicting these market values, because these forces and their interactions are not precisely understood, the model value nevertheless deviates to some extent from the observable market value. In this paper we propose a framework for augmenting the predictive capabilities of mathematical model with a learning component which is primed with an initial set of historical data and then adjusts its behavior after the event of prediction.

• Asia pacific journal of information systems
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• 제28권4호
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• pp.308-319
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• 2018

This paper aims at providing valuable insights on Financial Fraud Detection on a mobile money transactional activity. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure and Spark ML, which are traditional systems and Big Data respectively. Experimenting with sample dataset in Azure, we found that the Decision Forest model is the most accurate to proceed in terms of the recall value. For the massive data set using Spark ML, it is found that the Random Forest classifier algorithm of the classification model proves to be the best algorithm. It is presented that the Spark cluster gets much faster to build and evaluate models as adding more servers to the cluster with the same accuracy, which proves that the large scale data set can be predictable using Big Data platform. Finally, we reached a recall score with 0.73, which implies a satisfying prediction quality in predicting fraudulent transactions.

• 한국정보통신학회논문지
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• 제19권9호
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• pp.2044-2055
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• 2015

금융정보시스템은 다수의 거래고객과 다양한 정보를 기반으로 서비스를 제공하는 특징이 있다. 금융관련 고객 정보는 유출시 불법적인 목적으로 사용될 수 있어, 이를 사전에 방지하고자 많은 투자와 노력을 기울인다. 고객 정보 유출은 외부 서비스 이용자에 의한 유출은 물론 내부 정보시스템 사용자에 의해서도 빈번히 발생하고 있다. 이에 본 연구에서는 2채널을 이용한 강화된 내부 사용자 인증모델을 제시하여 금융정보시스템의 안정적 운영을 도모하고자 한다.

• 경영과학
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• 제18권1호
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• pp.135-145
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• 2001

In recent environment of dynamic management, there is growing recognition that information and knowledge management systems are essential for efficient/effective decision making by CEO. To cope with this situation, we suggest the Data-Miming scheme as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder’s point of view and EVA (Economic Value-Added), which represents shareholder’s point of view. To mine the new information & Knowledge discovery, we applied the improved genetic algorithms that consider predictability, understandability (lucidity) and reasonability factors simultaneously, we use a linear combination model for GAs learning structure. Although this model’s predictability will be more decreased than non-linear model, this model can increase the knowledge’s understandability that is meaning of induced values. Moreover, we introduce a random variable scheme based on normal distribution for initial chromosomes in GAs, so we can expect to increase the knowledge’s reasonability that is degree of expert’s acceptability. the random variable scheme based on normal distribution uses statistical correlation/determination coefficient that is calculated with training data. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS (Korea Investors Services Financial Analysis System).

• 경영정보학연구
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• 제18권2호
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• pp.173-198
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• 2016

본 연구의 목적은 비즈니스 인텔리전스 연구 관점에서 기업부실화 예측 성능을 향상키시는 것이다. 이를 위해 본 연구는 기존 연구들에서 미흡하게 다루어졌던 1) 데이터셋을 구성하는 과정에서 발생하는 바이어스 문제, 2) 거시경제위험 요소의 미반영 문제, 3) 데이터 불균형 문제, 4) 서술적 바이어스 문제를 다루어 경기순환국면을 반영한 기업부실화 예측 프레임워크를 제안하고, 이를 바탕으로 기업부실화 예측 모델을 개발하였다. 본 연구에서는 경기순환국면별로 각각의 데이터셋을 구성하고, 각 데이터셋에서 의사결정나무, 인공신경망 등 단일 분류기부터 앙상블 기법까지 다양한 데이터마이닝 알고리즘을 적용하여 실험하였다. 또한 본 연구는 데이터불균형 문제를 해결하기 위해, 오버샘플링 기법인 SMOTE(synthetic minority over-sampling technique) 기법을 통해 초기 데이터 불균형 상태에서부터 표본비율을 1:1까지 변화시켜 가며, 기업부실화 예측 모델을 개발하는 실험을 하였고, 예측 모델의 변수 선정 시에 선행연구를 바탕으로 재무비율을 추출하고, 여기서 파생된 IT 산출물인 재무상태변동성과 산업수준상태변동성을 예측 모델에 삽입하였다. 마지막으로, 본 연구는 각 순환국면에서 만들어진 기업부실화 예측 모델의 예측 성능 비교와 경기 확장기와 수축기에서의 기업부실화 예측 모델의 유용성에 대해 논의하였다. 본 연구는 비즈니스 인텔리전스 연구 측면에서 기존 연구에서 미흡하게 다루어졌던 4가지 문제점을 검토하고, 이를 해결할 프레임워크를 제안함으로써 기존 연구 대비 기업부실화 예측률을 10% 이상 향상시켰다는 점에서 연구의 의의를 찾을 수 있다.

• 산업경영시스템학회지
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• 제35권1호
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• pp.93-100
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• 2012

The purpose of this study is to present the green management requisites effect on corporate performance. Corporate performance consists of customer and green performance, work satisfaction and financial performance. In order to carry out this research we obtained 175 survey sheets, inspect the twelve assumptions focused on reliability, appropriateness of the model. Validation results of hypothesis are summarized as follows. First, the green management components : system, resource/energy affect significantly to the customer and green performance. Second, the green management components : system, resource/energy influence significantly to work satisfaction. Finally, the strategy has on effect to the financial performance. This paper shows that the green management requisites have an effect on the corporate performance directly and significantly.

• Asia pacific journal of information systems
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• 제22권1호
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• pp.53-77
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• 2012

Financial firms, especially large scaled firms such as KB bank, NH bank, Samsung Card, Hana SK Card, Hyundai Capital, Shinhan Card, etc. should be securely dealing with the personal financial information. Indeed, people have tended to believe that those big financial companies are relatively safer in terms of information security than typical small and medium sized firms in other industries. However, the recent incidents of personal information privacy invasion showed that this may not be true. Financial firms have increased the investment of information protection and security, and they are trying to prevent the information privacy invasion accidents by doing all the necessary efforts. This paper studies how effectively a financial firm will be able to avoid personal financial information privacy invasion that may be deliberately caused by internal staffs. Although there are several literatures relating to information security, to our knowledge, this is the first study to focus on the behavior of internal staffs. The big financial firms are doing variety of information security activities to protect personal information. This study is to confirm what types of such activities actually work well. The primary research model of this paper is based on Theory of Planned Behavior (TPB) that describes the rational choice of human behavior. Also, a variety of activities to protect the personal information of financial firms, especially credit card companies with the most customer information, were modeled by the four-step process Security Action Cycle (SAC) that Straub and Welke (1998) claimed. Through this proposed conceptual research model, we study whether information security activities of each step could suppress personal information abuse. Also, by measuring the morality of internal staffs, we checked whether the act of information privacy invasion caused by internal staff is in fact a serious criminal behavior or just a kind of unethical behavior. In addition, we also checked whether there was the cognition difference of the moral level between internal staffs and the customers. Research subjects were customer call center operators in one of the big credit card company. We have used multiple regression analysis. Our results showed that the punishment of the remedy activities, among the firm's information security activities, had the most obvious effects of preventing the information abuse (or privacy invasion) by internal staff. Somewhat effective tools were the prevention activities that limited the physical accessibility of non-authorities to the system of customers' personal information database. Some examples of the prevention activities are to make the procedure of access rights complex and to enhance security instrument. We also found that 'the unnecessary information searches out of work' as the behavior of information abuse occurred frequently by internal staffs. They perceived these behaviors somewhat minor criminal or just unethical action rather than a serious criminal behavior. Also, there existed the big cognition difference of the moral level between internal staffs and the public (customers). Based on the findings of our research, we should expect that this paper help practically to prevent privacy invasion and to protect personal information properly by raising the effectiveness of information security activities of finance firms. Also, we expect that our suggestions can be utilized to effectively improve personnel management and to cope with internal security threats in the overall information security management system.

• 산업경영시스템학회지
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• 제38권3호
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• pp.39-48
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• 2015

In this study, granting the optimal loan limit on SME (Small and Medium Enterprise) loans of financial institutions was proposed using the traditional newsvendor model. This study was the first domestic case study that applied the newsvendor model that was mainly used to calculate the optimum order quantity under some uncertain demands to the calculation of the loan limit (debt ceiling) of institutions. The method presented in this study made it possible to calculate the loan limit (debt ceiling) to maximize the revenue of a financial institution using probability functions, applied the newsvendor model setting the order volume of merchandise goods as the loan product order volume of the financial institution, and proposed, through the analysis of empirical data, the availability of additional loan to the borrower and the reduction of the debt ceiling and a management method for the recovery of the borrower who could not generate profit. In addition, the profit based loan money management model presented in this study also demonstrated that it also contributed to some extent to the prediction of the bankruptcy of the borrowing SME (Small and Medium Enterprise), as well as the calculation of the loan limit based on profit, by deriving the result values that the borrowing SME (Small and Medium Enterprise) actually went through bankruptcy at later times once the model had generated a signal of loan recovery for them during the validation of empirical data. accordingly, The method presented in this study suggested a methodology to generated a signal of loan recovery to reduce the losses by the bankruptcy.