• 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.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.8 no.1
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• pp.129-177
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• 1970

For the purpose of establishing the systematized technical scheme of the cooperative rice cultivation which has most significant impact to improve rice productivity and the farm management, the author have studied the cultivation practices, and the variation of rice growth and yield between the cooperative rice cultivation and the individual rice cultivation at random selected 18 paddy fields. The author also have investigated through comparative method on the cultivation practices, management, organization and operation scheme of the two different rice cultivation methods at 460 paddy fields. The economic feasibility has been ana lysed and added in this report. The results obtained from this study are summarized as follows; 1. In the nursery, the average amount of fertilizer application, especially, phosphate and potassium, and the frequency of chemicals spray for the disease, insect and pest control at the cooperative rice cultivation are significantly higher than those of the individual rice cultivation. 2. The cultivation techniques of the cooperative rice farming after the transplanting can be characterized by a) the earlier transplanting of rice, b) the denser hills per unit area and the lesser number of seedlings per hill, c) the application of larger quantities of fertilizer including nitrogen, phosphate and potassium, d) more divided application of fertilizers, split doses of the nitrogen and potassium, e) the increased frequencies of the chemicals spray for the prevention of disease, insect and pest damages. 3. The rate of lodging in the cooperative rice cultivation was slightly higher than that of the individual rice cultivation, however, the losses of rice yield owing to the occurrence of rice stem borer and grass leaf roller in the cooperative rice cultivation were lower than that of the individual rice cultivation. 4. The culm length, panicle length, straw weight and grain-straw ratio are respectively higher at the cooperative rice cultivation, moreover, the higher variation of the above factors due to different localities of the paddy fields found at the individual rice cultivation. 5. The number of panicles, number of flowers per panicle and the weight of 1, 000 grains, those contributing components to the rice yield were significantly greater in the cooperative rice cultivation, however, not clear difference in the maturing rate was observed. The variation coefficient of the yield component in the cooperative cultivation showed lower than that or the individual rice cultivation. 6. The average yield of brown rice per 10 are in the cooperative rice cultivation obtained 459.0 kilograms while that of the individual rice cultivation brought 374.8 kilograms. The yield of brown rice in the cooperative rice cultivation increased 84.2 kilogram per 10 are over the individual rice cultivation. With lower variation coefficient of the brown rice yield in the cooperative rice cultivation, it can be said that uniformed higher yield could be obtained through the cooperative rice cultivation. 7. Highly significant positive correlations shown between the seeding date and the number of flowers per panicle, the chemical spray and the number of flowers per panicle, the transplanting date and the number of flowers per panicle, phosphate application and yield, potassium application and maturing rate, the split application of fertilizers and yield. Whilst the significant negative correlation was shown between the transplanting date and the maturing rate 8. The results of investigation from 480 paddy fields obtained through comparative method on the following items are identical in general with those obtained at 18 paddy fields: Application of fertilizers, chemical spray for the control of disease, insects and pests both in the nursery and the paddy field, transplanting date, transplanting density, split application of fertilizers and yield n the paddy fields. a) The number of rice varieties used in the cooperative rice cultivation were 13 varieties while the individual rice cultivation used 47 varieties. b) The cooperative rice cultivation has more successfully adopted improved cultivation techniques such as the practice of seed disinfection, adoption of recommended seeding amount, fall ploughing, application of red soil, introduction of power tillers, the rectangular-type transplanting, midsummer drainage and the periodical irrigation. 9. The following results were also obtained from the same investigation and they are: a) In the cooperative rice cultivation, the greater part of the important practices have been carried out through cooperative operation including seed disinfection, ploughing, application of red soil and compost, the control of disease, insects and pests, harvest, threshing and transportation of the products. b) The labor input to the nursery bed and water control in the cooperative rice cultivation was less than that of the individual rice cultivation while the higher rate of labor input was resulted in the red soil and compost application. 10. From the investigation on the organization and operation scheme of the cooperative rice cultivation, the following results were obtained: a) The size of cooperative rice cultivation farm was varied from. 3 ha to 7 ha and 5 ha farm. occupied 55.9 percent of the total farms. And a single cooperative farm was consisted of 10 to 20 plots of paddies. b) The educational back ground of the staff members involved in the cooperative rice cultivation was superior than that of the individual rice cultivation. c) All of the farmers who participated to the questionaires have responded that the cooperative rice cultivation could promise the increased rice yield mainly through the introduction of the improved method of fertilizer application and the effective control of diseases, insects and pests damages. And the majority of farmers were also in the opinion that preparation of the materials and labor input can be timely carried out and the labor requirement for the rice cultivation possibly be saved through the cooperative rice cultivation. d) The farmers who have expressed their wishes to continue and to make further development of the cooperative rice cultivation was 74.5 percent of total farmers participated to the questionaires. 11. From the analysis of economical feasibility on the two different methods of cultivation, the following results were obtained: a) The value of operation cost for the compost, chemical fertilizers, agricultural chemicals and labor input in the cooperative rice cultivation was respectively higher by 335 won, 199 won, 288 won and 303 won over the individual rice cultivation. However, the other production costs showed no distinct differences between the two cultivation methods. b) Although the total value of expenses for the fertilizers, agricultural chemicals, labor input and etc. in the cooperative rice cultivation were approximately doubled to the amount of the individual rice cultivation, the net income, substracted operation costs from the gross income, was obtained 24, 302 won in the cooperative rice cultivation and 20, 168 won was obtained from the individual rice cultivation. Thereby, it can be said that net income from the cooperative rice cultivation increased 4, 134 won over the individual rice cultivation. It was revealed in this study that the cooperative rice cultivation has not only contributed to increment of the farm income through higher yield but also showed as an effective means to introduce highly improved cultivation techniques to the farmers. It may also be concluded, therefore, the cooperative rice cultivation shall continuously renovate the rice production process of the farmers.