• Journal of Preventive Medicine and Public Health
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• v.30 no.2 s.57
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• pp.381-391
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• 1997

In an epidemiological study of metal workers exposed to metalworking fluids (MWF), the prevalence time of Evolution, seasonal occurrence and clinical type of contact dermatitis were investigated. Compostional analysis of MWF with HPLC, dermatological examination and two consecutive questionnaire surveys were conducted. Study population was divided into two groups ; workers contact to cutting oil and workers contact to rust preventive oil. In the analysis of MWF, aliphatic hydrocarbons, having 12-20 carbons, was most common composition(49.04%) of cutting oil otherwise, major contents (90.99%) of the rust preventives oil were aliphatic hydrocarbons composed of 6-9 carbons. The frequency (point prevalence) of contact dermatitis(CD) was 7(12.7 per 100 subjects) in the dermatological examination of 55 workers. As the result of second survey for contact dermatitis, cumulative prevalence of oil working full-time and recent 1 year prevalence in two groups were 28.0, 16.7 and 15.1, 12.5 per 100 subjects. There were no difference in the prevalence of CD by oil, age, oil contact duration. Summer is the most common evolution season in workers exposed to cutting oil, but not in workers exposed to rust preventive oil. Major clinical type of CD was erythematous papules in both groups. It presents the importance of preventive measures that 51.1% suffer from contact dermatitis had medical care at their own expense, and 47.1% of them felt serious about their contact dermatitis. From the fact that 68.6% think cotton gloves protective apparatus, we emphasize the need for health education.

• Journal of Preventive Medicine and Public Health
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• v.30 no.2 s.57
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• pp.437-461
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• 1997

Because of a significant improvement in the economic situation and development of scientific techniques in Korea during the last 30 years, the life expectancy of the Korean people has lengthened considerably and as a result, the number of the elderly has markedly increased. Such an increase of the number of aged population brought about many social, economic, and medical problems which were never seriously considered before. This study was conducted to assess the trend of medical care utilization and medical expenditure of the elderly. The data of each patient in the study were taken from computer database maintained for administrative purpose by the Korea Medical Insurance Corporation. The study population was 132,670 who were 60 years old or more and registered in Korean Medical Insurance Corporation from 1989 to 1993. The study subjects were predominantly female(56.3%) and 10,000-20,000 Won premium group(50.6%). The following are summaries of findings : The total increase of the number of inpatient cases was 40.5% from 1989 through 1993. The average annual increase was 3.7% in inpatient medical expenditures per case, 4.4% in inpatient medical expenditures per day and 0.08% in length of stay per case from 1989 through 1993. Cataract was the most prevalent disease of 10 leading frequent diseases in all ages from 1989 through 1993. The case mix in 1993 compared to 1989 revealed that cataract and ischemic cerebral disease were increased whereas essential hypertension and pulmonary tuberculosis were decreased . The average annual increase of medical expenditures was 3.8% in general hospitals, 6.3% in hospitals and 2.4% in clinics. From 1989 through 1993, medical expenditures used by high-cost patients accounted for about 14% to 20% of all expenditures for inpatient care, while they represented less than 2.5% of the elderly population. Time series analysis revealed that total medical expenditures and doctor's fee for inpatient will be progressively increased whereas drug expenditures for inpatient will be decreased. And there will be no change in length of stay. Based on the above results, the factors increasing medical cost and utilization should be identified and the method of cost containment for the elderly health care should be developed systematically.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.2 no.2
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• pp.169-177
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• 1999

Purpose: To evaluate the efficacy of interferon alpha therapy with or without prednisolone in children with chronic hepatitis B. Methods: Twenty-eight children (22 boys, 6 girls, mean age 130 months) had seropositive results for HBsAg, HBeAg and HBV DNA; 11 had chronic persistent hepatitis and 17 had chronic active hepatitis. The patients were divided into two groups depending upon their inflammatory activity on liver biopsy, pretreatment serum ALT levels and HBV DNA levels. Fourteen children (group 1: chronic active hepatitis, ALT ${\geq}$ 100 IU/L and HBV DNA ${\leq}$ 100 pg/$300\;{\mu}L$) received interferon alpha 2a 5 $MU/m^2$ of body surface three times weekly for 6 months. Fourteen children (group 2: chronic persistent hepatitis or chronic active hepatitis with ALT < 100 IU/L or HBV DNA > 100 pg/$300\;{\mu}L$) received prednisolone in decreasing daily doses of 60 mg/$m^2$, 40 mg/$m^2$, and 20 mg/$m^2$, each for 2 weeks, followed after 2 weeks by interferon alpha 2a on the same schedule. At the end of therapy, 3 end points were analyzed: HBeAg seroconversion, serum ALT normalization rate and clearance of serum HBV DNA. Results: At the end of treatment, HBe antigen-to antibody seroconversion was higher but not more significant in group 1 than group 2 (71.4% vs. 50.0%). Only one patient in group 2 who lost HBeAg, also cleared HBsAg. ALT normalization was similar in both groups (64.3% in group 1 vs. 55.6% in group 2). Clearance of serum HBV DNA was observed in 78.6% of patients in group 1 and 64.3% in group 2, but no significant differences. Complete response was similarly achieved in both groups (57.1% in group 1 vs. 50.0% in group 2). Interferon alpha therapy with prednisolone priming was well tolerated and all children finished therapy. Conclusion: The combined therapy with prednisolone followed by interferon alpha may be safe and effective in inducing a serological and biochemical remission of the disease in approximately 50% of children with chronic hepatitis B and with a high level of viral replication and less active disease. However, a controlled study should be performed to confirm these results.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.2 no.2
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• pp.153-163
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• 1999

Purpose: The purpose of our study is to provide useful information for diagnostic methods of fatty liver by childhood simple obesity and to provide correlation between serum alanine aminotransferase (ALT) for screening test and abdominal computerized tomography (CT) and liver biopsy for confirmative diagnostic methods of fatty liver. Methods: Among 78 obese childrens who visited our hospital, CT was carried out in 26 childrens. Of these, liver biopsy was carried out in 15 childrens who had high obesity index or severe elevated ALT. Based on the level of serum ALT, 26 cases were classified into 3 groups, and compared with physical measurements and degree of fatty infiltration on CT and liver biopsy. Results: 1) Correlation between ALT and physical measurements: Of 26 obese children, ALT was abnormally elevated (>30 IU/L) in 17 cases (67.4%) but there was no significant correlation between ALT and physical measurements (p>0.05). 2) Correlation between degree of fatty infiltration on CT and ALT: Of 26 cases, 13 cases (50%) revealed fatty liver on CT. The degree of fatty liver on CT had significant correlation with elevation of ALT (p<0.05). 3) Correlation between the degree of fatty infiltration on liver biopsy and ALT: Liver biopsy was performed in 15 cases of which 14 cases revealed fatty liver. But one case had normal hepatic histology with severe obesity and normal ALT. Fourteen fatty liver cases on liver biopsy were classified into 3 groups by the degree of fatty infiltration and analysed with obesity index and ALT. The histologic hepatic steatosis had no significant correlation with obesity index (p>0.05), but significant correlation with ALT (p<0.05). 4) Correlation between CT and liver biopsy finding: Both CT and liver biopsy were performed in 15 cases of which 6 cases revealed normal finding on CT and 9 cases manifested fatty liver. There was significant correlation between CT and liver biopsy findings (r=0.6094). Conclusion: The results of our study suggest that abdominal CT and liver biopsy are useful and accurate methods of estimating fatty liver in the childhood obesity. But biochemical abnormalities of routine liver function tests dot not correlate well with severity of the fatty liver and liver injury.

• Journal of Preventive Medicine and Public Health
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• v.35 no.2
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• pp.141-146
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• 2002

Objectives : This study was peformed in order to assess the incidence of hypertension based on two-years follow-up of a rural hypertension-free cohort in Korea. Methods : The study cohen comprised 2,580 subjects aged above 20 (1,107 men and 1,473 women) of Chung-Song County in Kyungpook Province judged to be hypertensive-free at the baseline examination in 1996. For each of two examinations in the two-year follow-up, those subjects free of hypertension were followed for the development of hypertension to the next examination one year (1997) and two years later (1998). The drop-out rate was 24.7% in men and 19.6% in women. Hypertension was defined as follows 1) above mild hypertension as a SBP above 140 mmHg or a DBP above 90 mmMg,2) above moderate hypertension as a SBP above 160 mmHg or a DBP above 100 mmHg or when the participant reported having used antihypertensive medication after beginning this survey. Results : The age-standardized incidence of above mild hypertension was 6 per 100 person years (PYS) in men and that of above moderate hypertension was 1.2. In women, the age-standardized rate for above mild hypertension was 5.7 and 1.5 for above mild and moderate hypertension, respectively. However, the rates of incidence as calculated by the risk method were 4.8% and 1.0% in men and 4.6%, 1.2% in women, respectively. In both genders, incidence was significantly associated with advancing age(p<0.01), In men, the incidences of above moderate hypertension by age group were 0.5 per 100 PYS aged 20-39, 0.7 aged 40-49, 1.7 aged 50-59, 3.6 aged 60-69, and 5.8 aged above 70(p<0.01). In women, those the incidence measured 0.6 per 100 PYS aged 20-39, 1.8 aged 40-49, 1.3 aged 50-59, 3.3 aged 60-69, and 5.6 aged above 70(p<0.01). After age 60, the incidence of hypertension increased rapidly. Conclusions : The incidence data of hypertension reported in this study may serve as a reference data for evaluating the impact of future public efforts in the primary prevention of hypertension in Korea.

• Journal of Preventive Medicine and Public Health
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• v.30 no.3 s.58
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• pp.630-642
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• 1997

The purpose of this study was to examine the mortality risk associated with cognitive impairment among the rural elderly. The subjective of study was 558 of 'A Study on the Depression and Cognitive Impairment in the Rural Elderly' of Jung Ae Rhee and Hyang Gyun Jung's study(1993). Cognitive impairment and other social and health factors were assessed in 558 elderly rural community residents. For this study, a Korean version of the Mini-Mental State Examination(MMSEK) was used as a global indicator of cognitive functioning. And mortality risk factors for each cognitive impairment subgroup were identified by univariate and multivariate Cox regression analysis. At baseline 22.6% of the sample were mildly impaired and 14.2% were severely impaired. As the age increased, the cognitive function was more impaired. Sexual difference was existed in the cognitive function level. Also the variables such as smoking habits, physical disorders had the significant relationship with cognitive function impairment. Across a 3-year observation period the mortality rate was 8.5% for the cognitively unimpaired, 11.1% for the mildly impaired, and 16.5% for the severly impaired respendents. And the survival probability was .92 for the cognitively unimpaired, .90 for the mildly impaired, and .86 for the severly impaired respondents. Compared to survival curve for the cognitively unimpaired group, each survival curve for the mildly and the severely impaired group was not significantly different. When adjustments models were not made for the effects of other health and social covariates, each hazard ratio of death of mildly and severely impaired persons was not significantly different as compared with the cognitively unimpaired. But, as MMSEK score increased, significantly hazard ratio of death decreased. Employing Cox univariate proportional hazards model, statistically other significant variables were age, monthly income, smoking habits, physical disorders. Also when adjustments were made for the effects of other health and social covariates, there was no difference in hazard ratio of death between those with severe or mild impairment and unimpaired persons. And as MMSEK score increased, significantly hazard ratio of death did not decrease. Employing Cox multivariate proportional hazards model, statistically other significant variables were age, monthly income, physical disorders. Employing Cox multivariate proportional hazards model by sex, at men and women statistically significant variable was only age. For both men and women, also cognitive impairment was not a significant risk factor. Other investigators have found that cognitive impairment is a significant predictor of mortality. But we didn't find that it is a significant predictor of mortality. Even though the conclusions of our study were not related to cognitive impairment and mortality, early detection of impaired cognition and attention to associated health problems could improve the quality of life of these older adults and perhaps extend their survival.

• Journal of Nutrition and Health
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• v.30 no.5
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• pp.465-477
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• 1997

The purpose of this article is to know the effects on bowel function of the kind of fiber and the amount of fiber in SD-rats. To do this experiment, we select of $\alpha$-cellulose as n insoluble cellulose source and alginic acid and pectin as soluble cellulose source. The rats diets contained callolose camcentrations of 1.0%, 3.6%, 6.0% and 10.0%. After that, we raised the SD-rats for 4weeks and measured the amount of food intake, body weight, the food effciency ratio, the length of liver and stomach the weight of the intestines, the transit time through the intestines, pH in feces, and the amount of bile acid and Ca, Mg, pp. 1) The amount of food intake was 15.75-31.00g/day. It was highest in the 10.0% cellulose group and the lowest in the 3.6% and 6.0% alginic acid group (p<0.05). The body weights of rats were 277.50-349.809. It was highest in the 1.0% pectin group and lowest in the 3.6% alginic acid group, 6.0% cellulose group, and 10.0% pectin group. It had differences according to the content fiber and the kind of dietary(p<0.01). The food efficiency ratio was (p<0.01). The higher the content of dietary fiber, the lower the calory and the food efficiency ratio. 2) Transit time was 446.0-775.0 minutes and it showed signidicant ifferences according to the content and kind of dietary fiber(p<0.01). It was long in the 1.0% cellulose group and 1.0% pectin group but short in the 10.0% alginic acid group. As the content of dietary fiber increased, the transit time through the intestines was shortened. The length of small intestine was 101.03-120.40cm and there were no difference cegardloss of the content and kind of fiber. The length of the large intestine was 20.92-25.42cm and there were significant differences according to the content and kind of the fiber. High-fiber diets resulted in increases in the length of the large intestine. 3) The weight of the liver was 8.68-10.96g and there were no differences according to the content and kind of fiber. The weight of stomach was 1.28-1.74g and there were no differences resulting from the kind of dietary fiber, but it was highest in the 10.0% alginic acid group. The weight of the small intestine was 5.52-8.04g with no difference resulting from to the kind of fiber. It was highest in the 10.0% the alginic acid group and lowest in the 1.0% alginic acid group(p<0.05). The weight of large intestine was 2.50-3.30g with no differences related to the kind of dietary fiber. It was heaviest in the 6.0% and 10.0% alginic acid groups and in the 10.0% pectin group with differences related to the content of fiber(p<0.05). 4) The pH of the feces was 5.82-6.86 according to the kind of dietary fiber, alginic acid group was high at 6.66, the cellulose group was 6.26. but the pectin group was low at 6.30. There were difference according to the content of fiber, but no consistency. The content of bile acid was 6.25-34.77umol per 1g of dry feces. According to the kind of dietary fiber, the alginic acid group was low at 12.91umol, cellulose group was 18.64umol and, the pectin group was the highest at 27.78umol(p<0.001). Based on the content of dietary fiber, alginic acid group was low at 1.0%, but high at 3.6% pectin group(p<0.001). 5) The amount of feces was 1.00-5.10g/day. The weight of rat feces was 2.23g/day in the alginic acid goup, 2.75g/day in the cellulose group, and 1.82g/day in the pectin group. According to the content of fiber, cellulose group was high at 10.0% but alginic acid group was 1.0%, and there were significant difference according to the dietary fiber. The more the content of fiber, the more increase the content of feces in alginic acid, cellulose and pectin group. The content of Ca in the feces was 80.10-207.82mg/1g of dry feces. In the dietary fiber, alginic acid group was 193.08mg, cellulose group was 87.5mg, pectin group was 138.16mg. In the content of fiber, alginic acid group was high at 1.0% and 3.6% but low at 10.0% of Pectin group. The content of Mg was 19.15-44.72mg/1g of dry feces. According to the kind of dietary fiber, alginic acid group was 35.33mg, cellulose group was 23.60mg, and pectin was 36.93mg. According to the content of fiber, pectin group was high at 1.0% and low at 10.0% of cellulose group. The content of P was 1.65-4.65mg/1g of dry feces. According to the kind of dietary fiber, alginic acid group 2.23mg/g dry feces, cellulose group was 2.29mg/g, pectin group wa 4.08mg/g dry feces. In the content of fiber, pectin group was high at 6.0% and low at 6.0% alginic acid group, but there were significant difference among the analysis value. The conetnt of Ca and MG was higher in soluble alginic acid group and pectin group than in insoluble cellulose group. The high the content of the dietary fiber, the lower the food efficiency ratio and the short the transit time through intestine with the increase of the length of large intestin as well as the higher level of the stomach, the small intestine and the large intestine. According to the content of the dietary fiber, the amount of the feces, Ca, Mg and P was increased but the length the small intestin, the weight of liver, pH of the feces and the amount of bile acid showed no differences and consistency.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.4
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• pp.599-607
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• 1998

To clarify annual reproductive cycle of Korean dark sleeper, Odontobutis platycephala (Iwata et Jeon), we examined the seasonal changes of gonadosomatic index (GSI), the proportional frequency of oocyte development stages in the ovary and the changes of sex steroid hormone levels in blood from December 1995 to November 1997. In July and August, GSI was 0.35 to 0.72 and most oocytes in the ovary were chromatin-nucleolus stage and perinucleolar stage (proportional frequency: $87\%\~96\%$). In September, GSI was 1.20 $\pm$ 0.12, some oocytes in the ovary were yolk vesifle stage (proportional frequency: $22.8\%$) and vitellogenic stage which appeared very rarely(proportional frequency: $2.2\%$). GSI increased gradually from October and reached 4.59± 0.61 to December. During this period, oocytes of vitellogenic stage increased slightly (proportional frequency in December: $22.1\%$). In January, GSI was 4.32 $\pm$ 0.72 but the proportional frequency of oocytes in vitellogenic stage increased (proportional frequency: $51.2\%$). from February, GSI was increased sharply and reached to 10.51 $\pm$ 1.04 in March, the highest value throughout the year and the proportional frequency of oocytes in vitellogenic stage also reached the highest levels (proportional frequency: $60\%$). From April, GSI was gradually decreased and fell down to 1.11 $\pm$ 0.35 in June. During this period, the proportional frequency of mature oocytes was the highest in April (proportional frequency of mature oocyte stage: $40\%$ in April, $12\%$ May, $5\%$ June) throughout the year, and atretic ovarian follicles were appeared. The blood level of estradiol-17$\beta$ ($E_2$), which stimulates the hepatic synthesis and secretion of vitellogenin, was $0.84{\pm}0.20\;ng/m{\ell}$ in August, and thereafter was not changed until December. from January, it increased sharply and reached the highest level of $ 2.85{\pm}0.35\;ng/m{\ell}$ in March throughout the year, but fell to $0.14{\pm}0.02\;ng/m{\ell}$ in July(P<0.05), 17$\alpha$-hydroxprogesterone(17$\alpha$-OHP) was the peak $13.37{\pm}0.52ng/m{\ell}$ in March, but no significant changes in other period(below $3ng/m{\ell}$, P<0.05). 17$\alpha$, 20$\beta$-dihydroxy-4-pregnen-3-one(17$\alpha$, 20$\beta$-P), which was known as the final maturation inducing hormone in teleost, was $0.74{\pm}0.09ng/m{\ell}$ in April and $0.54{\pm}0.07ng/m{\ell}$ in May, but no significant changes in other period (below $0.26\;ng/m{\ell}$, p<0.05). Taken together these results, the annual reproductive cycle of O. platycephala divided into 4 periods as follows: 1) ripe and spawning period from April to June, main spawning period was from April to May, 2) Resting period from July to August, 3) Growing period from September to December, 4) Maturing period from January to March. Moreover, It was showed that the changes of sex steroid hormone in blood played a important roles in the annual reproductive cycle of O. platycephala.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.