• 한국병원경영학회지
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• 제13권3호
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• pp.1-16
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• 2008

According to Myers (1984) and Myers and Majluf(1984), there exists a financial hierarchy from internal to external financing, from long-tenn debt to equity, due to information costs. The purpose of this study is to assess the profit-making corporation of healthcare institutions. Data was collected from 130 hospital presidents and financial managers. We analysed the frequency and one way ANOVA by SPSS Windows 14.0K. The major findings of the study were as follows: We found that the priorities which a healthcare institutions financing were internal financial, other allowance, a credit loan, a security loan, and a lease through this study. The priorities which a healthcare institutions raised the capital differed as to the number of beds and revenues. The priorities were no difference from ownership, location and an annual business.

• 한국정보시스템학회지:정보시스템연구
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• 제18권4호
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• pp.41-57
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• 2009

Although financial information is a great influence upon determining of the group which use them, detection of management fraud and earning manipulation is a difficult task using normal audit procedures and corporate credit evaluation processes, due to the shortage of knowledge concerning the characteristics of management fraud, and the limitation of time and cost. These limitations suggest the need of systemic process for !he effective risk of earning manipulation for credit evaluators, external auditors, financial analysts, and regulators. Moot researches on management fraud have examined how various characteristics of the company's management features affect the occurrence of corporate fraud. This study examines financial characteristics of companies engaged in fraudulent financial reporting and suggests a model and system for detecting GAAP violations to improve reliability of accounting information and transparency of their management. Since the detection of management fraud has limited proven theory, this study used the detecting method of outlier(upper, and lower bound) financial ratio, as a real-field application. The strength of outlier detecting method is its use of easiness and understandability. In the suggested model, 14 variables of the 7 useful variable categories among the 76 financial ratio variables are examined through the distribution analysis as possible indicators of fraudulent financial statements accounts. The developed model from these variables show a 80.82% of hit ratio for the holdout sample. This model was developed as a financial outlier detecting system for a financial institution. External auditors, financial analysts, regulators, and other users of financial statements might use this model to pre-screen potential earnings manipulators in the credit evaluation system. Especially, this model will be helpful for the loan evaluators of financial institutes to decide more objective and effective credit ratings and to improve the quality of financial statements.

• International Journal of Human Ecology
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• 제14권2호
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• pp.79-91
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• 2013

The market for a payday advance, regarded as both a convenient and short term-loan for immediate financial help, has grown incredibly since the 1990's. Despite its popularity by borrowers and the possible benefits, it has received negative publicity. Some borrowers have been caught in a debt trap for a long-term period and at tripledigit interest rates. The objective of this study is to shed light on the borrowers' profiles and their demand for a payday advance. Based on the 2010 household level data from the U.S. Federal Reserve Board, this study finds that payday advance users are pronounced as seemingly risky people. Payday advance users tend to be college drop-outs, African Americans, and non-homeowners compared to non-payday advance users. They are more likely to overspend above their income and have a favorable attitude toward conspicuous spending than non-payday advance users. They tend not to shop at all nor perform even moderate shopping for credit before using a payday advance service as opposed to non-payday advance users.

• Journal of applied mathematics & informatics
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• 제9권1호
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• pp.197-211
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• 2002

In this paper, we propose a multi-Criteria decision making approach to address the problem of finding the best possible solution in credit unions. Sensitivity analysis on the priority structure of the goals has been performed to obtain all possible solutions. The study uses the Euclidean distance method to measure distances of all possible solutions from the identified ideal solution. The possible optimum solution is determined from the minimum distance between the ideal solution and other possible solutions of the Problem.

• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.197-212
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• 2022

The study uses the audited financial statements of 26 Vietnamese commercial banks listed on the Ho Chi Minh City Stock Exchange (HOSE) and Hanoi Stock Exchange (HOSE) during the 2008-2018 period to estimate the system GMM model, which provides empirical evidence on the effect of the variables of customer deposit to total assets (DEPO) ratio, loan to assets (LTA) ratio, liquidity of commercial banks (LIQ), credit development (CRD) ratio, external funding (EFD) ratio, and credit loss provision (LLP) ratio on liquidity risk. The study confirms that commercial banks' internal factors play the most important role, and there is no empirical evidence on macro variables that affect liquidity risk. Finally, in accordance with the theoretical framework, the study uses an estimation method with the R language and the bootstrap methodology to give empirical proof of the nonlinear correlation and U-shaped graph between commercial bank size and liquidity risk. The importance of commercial bank size in absorbing and moderating the effects of liquidity shocks is demonstrated, however, excessive growth in commercial bank size would increase liquidity risk in commercial bank operations.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 공동추계학술대회
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• pp.509-515
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• 2005

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved it more powerful than traditional artificial neural networks (ANNs)(Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al, 2005; Kim, 2003). The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is cost-sensitive. Therefore, it is necessary to convert the output of the classifier into well-calibrated posterior probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create probabilities (Platt, 1999; Drish, 2001). This study applies a method to estimate the probability of outputs of SVM to bankruptcy prediction and then suggests credit scoring methods using the estimated probability for bank's loan decision making.

• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.829-837
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• 2021

The study investigates the impact of the Counter-Cyclical Buffer Policy (CCB) on regional development bank profitability in Sumatra, Indonesia. CCB requires banks to hold capital at times when credit is growing rapidly so that the buffer can be reduced if the financial cycle turns down or the economic and financial environment becomes substantially worse. This study employs time series data of regional development banks (RDBs) in Sumatra Island, Indonesia. The methodology applied in this study is a panel dynamic model with Generalized Methods of Moments (GMM). The results show that increasing capital through the implementation of CCB did not have a significant effect on RDBs' profitability. The findings of this study suggest that the activation and implementation of CCB lead to an increase in the amount and cost of loans to companies but do not affect the profitability of RDBs. The value of a Non-Performing Loan (NPL) proved to have a negative and significant effect on bank profitability. The CCB policy aims to overcome the pro-cyclicality of credit growth and improve bank resilience through increased capital which is expected to reduce excessive credit growth as a source of systemic risk. This causes a lack of lending to the community so that the profits obtained by the bank decrease.

• 한국지역지리학회지
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• 제11권6호
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• pp.620-639
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• 2005

우리나라 금융시장에서 주택담보대출이 차지하는 비중이 매우 크기 때문에 부동산가격정책의 중요한 수단으로 주택담보대출을 활용하여 왔다. 그러나 소비자의 편익을 증진시키기 위한 미시적 금융제도의 발전에는 다소 소홀한 측면이 있으며, 상품정보의 비교분석, 안정적인 대출상품거래 등의 측면에서 소비자의 입장을 반영하고 주택금융상담서비스 품질의 제고를 위해서 모기지 브로커의 역할이 중요해지고 있다. 역할의 중요성에도 불구하고 외국의 경우 모기지브로커 활성화에 따른 대리인 문제가 늘 존재하고 있기 때문에 안정적인 제도적 기반 구축이 모기지 브로커의 활성화에 앞서 중요한 과제라고 할 수 있다. 이에 따라 본 논문에서는 모기지 브로커의 기능과 경제적 존립근거, 외국의 모기지 브로커 제도, 우리나라 주택담보대출금융의 특성과 대출모집인 제도 등을 검토하고, 이를 토대로 소비자의 편익증진 수단으로서 모기지 브로커 제도 도입방안을 제시한다. 제도 도입을 위한 주요 구성내용으로는 자격형태는 국가공인민간자격의 형태로 도입하고, 업무실무 및 윤리규정, 수수료 규정, 공인중개사 역할 부여, 교육요건을 기본적으로 둘 것을 제시한다.

• 한국콘텐츠학회논문지
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• 제17권9호
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• pp.145-158
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• 2017

최근 가계부채의 급증과 경제적 변화는 가구의 현금 흐름에 많은 영향을 미치고 있고, 높은 원리금 상환부담으로 부실위험이 증가하였다. 이에 선행연구들은 가계부채에 대한 객관적 상환부담지표를 구성하여 다양한 논의를 진행하고 있지만, 수요자 인식에 대한 연구는 상대적으로 부족하였다. 본 연구는 2016년 가계금융복지조사를 이용하여 가구의 소득분위별 가계부채 주관적 상환부담요인을 도출하여 비교 분석하였다. 연구결과는 소득 1 2분위에서 월세, 신용카드대출, 주거마련 대출비율이 높을수록 원리금 상환에 대한 부담이 높은 것으로 나타났다. 소득 3 4분위는 60대 이상, 가구원수, 부동산담보대출이 많을수록 원리금 상환에 대한 부담이 높은 것으로 나타났다. 소득 5분위는 부채상환마련 대출비율이 높을수록 원리금 상환에 대한 부담이 높은 것으로 나타났다.

• 아태비즈니스연구
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• 제14권2호
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• pp.51-61
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• 2023

Purpose - Since COVID-19, the government's expansion of liquidity to stimulate the economy has resulted in an increase in private debt and an increase in asset prices of such as real estate and stocks. The recent sharp rise of the US Federal fund rate and tapering by the Fed have led to a fast rise in domestic interest rates, putting a heavy burden on the Korean economy, where the level of household debt is very high. Excessive household debt might have negative effects on the economy, such as shrinking consumption, economic recession, and deepening economic inequality. Therefore, now more than ever, it is necessary to identify the causes of the increase in household debt. Design/methodology/approach - Main methodology is regression analysis. Dependent variable is household loans from depository institutions. Independent variables are consumer price index, unemployment rate, household loan interest rate, housing sales price index, and composite stock price index. The sample periods are from 2017 to May 2022, comprising 72 months of data. The comparative analysis period before and after COVID-19 is from January 2017 to December 2019 for the pre-COVID-19 period, and from Jan 2020 to December 2022 for the post-COVID-19 period. Findings - Looking at the results of the regression analysis for the entire period, it was found that increases in the consumer price index, unemployment rate, and household loan interest rates decrease household loans, while increases in the housing sales price index increase household loans. Research implications or Originality - Household loans of depository institutions are mainly made up of high-credit and high-income borrowers with good repayment ability, so the risk of the financial system is low. As household loans are closely linked to the real estate market, the risk of household loan defaults may increase if real estate prices fall sharply.