• Journal of Information Technology Applications and Management
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• 제15권3호
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• pp.43-59
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• 2008

This paper studies small and medium sized financial agency's management states that take advantage of the Korea Federation of Saving Bank's data. It also presents the management state and the decision-making model that monitors progressive insolvency by standardizing transfer path between relevant groups. With this in mind, we extracted explanatory variables for predictions of insolvency by using existing studies of document related insolvency. First of all, we designed a state model based on demarcated groups to take advantage of the self organizing map that groups in line with a neural network. Secondly, we developed a transition model by standardizing the transfer path between individual banks in a state model. Finally, we presented a decision-making model that integrated the state model and the transition model. This paper will provide groundwork for methods of insolvency prevention to businesses in order for them to have a smooth management system in the financial agencies.

• 가족자원경영과 정책
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• 제23권2호
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• pp.99-115
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• 2019

This study examined the insolvency likelihood of young debtors from the 2018 Household Financial and Welfare Survey. This study used the Household Default Risk Index (HDRI), which considers the ratio of total debt to total assets (DTA), and a total debt service ratio (DSR) to examine the insolvency level of debtors. The descriptive analyses showed no difference in frequency of households with a high probability of insolvency between those less than 35 years of age and those over 35 years of age. However, the median HDRI value for those less than 35 years of age was higher than those over 35 years of age. The multivariate analyses indicated that educational expenses for young Korean debtors was a factor that increased their probability of insolvency, while income was the only variable that decreased their insolvency likelihood.

• 디지털융복합연구
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• 제11권1호
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• pp.13-25
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• 2013

FSMA 24 규정을 고찰한 결과, 금융기관의 도산과 관련된 규정은 임의정리, 관리명령, 재산관리인, 임의청산, 법정청산, 파산, 채무부인의 금지 규정, 보험업자에 관한 보칙 등으로 구성되며, 각 절차에 따른 FSA의 권한과 책임이 명시되어 있다. 절차마다 약간의 차이는 있으나 전체적으로 FSA는 채권자와 동일한 지위에서 각 도산절차에 관한 법원 청구권, 각종 집회참석권, 청취권 등을 행사할 수 있다. 영국과 우리나라의 금융기관 도산과 관련된 규정의 차이점 및 시사점을 요약하면, 첫째, 영국은 FSA의 금융기관 도산 절차와 관련된 권한의 행사 주체가 FSA(Financial Services Authority)로 통일되어 있으나, 우리나라의 경우, 각 특별법에 따라 금융기관 정리 방법이 여러 기관으로 분산되어 있어서 관련절차의 행사 주체가 금융위원회, 금융감독원, 예금보험공사 등으로 혼재되어 나타난다. 이는 외환위기 이후 금융개혁의 조속한 시행을 위해 금융기관 정리와 관련된 입법활동을 서둘러 시행하면서 나타난 특징으로 볼 수 있다. 둘째, FSA는 금융기관 도산과 관련된 보험업종의 특성을 고려하여 계약유지에 관한 특별규정이 포함되었으나 우리나라는 규정상 업종별 차이 또는 금융 계약의 특징 등을 고려하지 않고 있어 향후 이에 대한 보완이 필요할 것으로 판단된다.

• 가족자원경영과 정책
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• 제22권1호
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• pp.63-78
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• 2018

This study examined the insolvency of debtors using multiple-indicator approaches and compared the outcomes across income levels with the 2016 'Household Financial and Welfare Survey'. This study used (1) the total debt to total assets ratio (DTA), (2) the total debt service ratio (DSR), and (3) the Household Default Risk Index (HDRI) recently developed by the Bank of Korea. Households in the lowest income quintile were more likely to be insolvent than any other income group. Demographics, such as age and gender of the household head, and most of the financial variables significantly increased the likelihood of insolvency based on the DTA. The number of household members and job status increased the likelihood of insolvency based on the DSR. Also, age, gender of the household head, and most of the financial variables increased the likelihood of household insolvency based on the HDRI after controlling for other demographics and financial variables.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.319-329
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• 2021

The study examines the impact of bank-level factors like non-performing assets, capital adequacy, and insolvency risk on bank performance. This study employs a quantitative method with panel data regression. The data was taken from the annual financial statements of state-owned commercial banks and private commercial banks in Indonesia from 2015 to 2019 using a purposive sampling method with a total sample of 470 observations. The result of the study shows that non-performing assets (NPA) have a significant negative impact on bank performance. Capital adequacy has a significant negative impact on bank performance. Insolvency risk for a bank means it cannot repay its depositors because its liabilities are greater than its assets; therefore, it has a significant impact on bank performance. This study is expected to help banks to understand how to manage the risks they face and to maintain their performance. This study uses 'size' and 'age of bank' as control variables and for credit risk and insolvency risk, Z-Score is used.

• 한국항해항만학회지
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• 제48권2호
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• pp.109-115
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• 2024

To develop a shipping company insolvency prediction model, we sampled shipping companies that closed between 2005 and 2023. In addition, a closed company and a normal company with similar asset size were selected as a paired sample. For this study, data of a total of 82 companies, including 42 closed companies and 42 general companies, were obtained. These data were randomly divided into a training set (2/3 of data) and a testing set (1/3 of data). Training data were used to develop the model while test data were used to measure the accuracy of the model. In this study, a prediction model for Korean shipping insolvency was developed using financial ratio variables frequently used in previous studies. First, using the LASSO technique, main variables out of 24 independent variables were reduced to 9. Next, we set insolvent companies to 1 and normal companies to 0 and fitted logistic regression, LDA and QDA model. As a result, the accuracy of the prediction model was 82.14% for the QDA model, 78.57% for the logistic regression model, and 75.00% for the LDA model. In addition, variables 'Current ratio', 'Interest expenses to sales', 'Total assets turnover', and 'Operating income to sales' were analyzed as major variables affecting corporate insolvency.

• 한국수산경영학회:학술대회논문집
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• 한국수산경영학회 2007년도 추계학술발표회 및 심포지엄
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• pp.167-184
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• 2007

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut-down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t-test is used to identify the differences in financial variables between the distressed group and the non-distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990$\sim$1993), period 2(1994$\sim$1997), period 3(1998$\sim$2002). The final model built from whole sample appled each three sub-samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub-sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• 수산경영론집
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• 제39권2호
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• pp.61-79
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• 2008

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut - down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t - test is used to identify the differences in financial variables between the distressed group and the non - distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990 - 1993), period 2(1994 - 1997), period 3(1998 - 2002). The final model built from whole sample appled each three sub - samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub - sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• 경영과정보연구
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• 제34권1호
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• pp.211-225
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• 2015

본 연구의 목적은 부실기업에서 회생과정을 거쳐 정상기업으로 전환된 회생기업을 대상으로 기업부실 원인과 기업이 선택하는 회생전략 사이의 관련성을 확인하고, 기업이 추구하는 회생전략에 따라 회생성과가 어떻게 달라지는지를 확인하는 데 있다. 국내 상장된 제조기업 중 2000년부터 2012년까지 법원에 법정관리 및 화의신청을 한 기업과 워크아웃 기업중 기업회생에 성공한 113개 기업을 대상으로 설문조사를 실시하였고 회수된 55개 설문과 공시자료를 바탕으로 다중회귀모형에 의해 실증 분석한 결과를 요약하면 다음과 같다. 먼저, 내부부실원인은 자산감축과 비용절감, 즉 효율성제고전략에 긍정적인 영향을 미치는 것으로 나타났고, 반대로 외부부실원인은 수익창출전략(제품/서비스감축, 제품/서비스확대)에 긍정적인 영향을 미치는 것으로 나타났다. 다음으로, 기업이 추구하는 회생전략에 따라 회생성과가 달라지는 지를 실증 분석한 결과, 효율성제고전략(자산감축과 비용절감)은 부채비율감소에 긍정적인 영향을 미치고, 반대로 수익창출전략(제품/서비스감축과 제품/서비스확대)은 매출액증가율에 긍정적인 영향을 미치는 것으로 나타났다. 본 연구는 기존의 부실원인과 회생전략, 회생전략이 회생성과에 미치는 포괄적 분석모형을 넘어 회생원인에 따라 기업이 보다 주안점을 두는 회생전략이 어떻게 달라지며, 회생전략에 따라 회생성과도 달라질 수 있음을 실증적으로 규명해 보았다는데 연구의 의의를 찾을 수 있다.

• 한국산학기술학회논문지
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• 제15권5호
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• pp.3260-3269
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• 2014

타 산업들과의 연계성이 강한 건설업체가 도산할 경우 타 산업시장의 경기악화를 초래할 수 있어, 시장 환경 변화에 따른 건설업체의 부실화 예측모형 연구가 중요하게 다뤄지고 있다. 하지만 건설업체 부실화 예측에 앞서 부실화에 기인하는 요소에 관한 연구가 선행되어야 함에도 불구하고 이와 같은 영향 변수들에 대한 연구가 부족한 실정이다. 이에 본 논문에서는 건설업체 포트폴리오의 큰 비중을 차지하는 주택시장 변화가 규모별 건설업체의 부실화에 미치는 영향을 벡터오차수정모형을 통해 분석하고자 한다. 이에 건설업체를 규모별로 2011년 시공능력평가순위 50위권 기업 중 상위 10개와 하위 10개로 구분하였으며, 각 업체의 부실화를 나타내는 예상부도확률을 KMV 모형을 통해 측정하였다. 주택시장의 변화를 대리하는 변수로 2001년부터 2010년까지의 주택매매가격지수, 주택전세가격지수, 전세매매가격비율을 활용하였다. KMV모형을 활용하여 규모별 건설업체의 예상부도확률을 산출한 결과 선험적으로 인지하고 있듯이 상위 10개의 대규모 건설업체들이 상대적으로 규모가 작은 건설업체에 비해 경영상태가 양호한 것을 확인 할 수 있었다. 또한 벡타오차수정모형을 구성, 충격반응분석을 수행한 결과 주택시장 경기변동에 따라 대규모 업체의 부실화 정도가 중소 건설업체에 비해 더 심각함을 확인할 수 있었다.