• 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.

• Asia Marketing Journal
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• v.12 no.4
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• pp.55-78
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• 2011

Recently strategic alliance between business firms has become prevalent to overcome increasing competitive threats and to supplement resource limitation of individual firms. As one of allianced sales promotion activities, a new type of discount program, so called "Alliance Card Discount", is introduced with the partnership of credit cards and loyalty cards. The program mainly pursues short-term sales growth by larger discount scheme while spends less through cost share among alliance partners. Thus this program can be regarded as cost efficient discount promotion. But because there is no solid evidence that it can really deliver profitable sales growth, an empirical study for its effects on sales and profit should be conducted. This study has two basic research questions concerning the effects of allianced discount program ; 1)the possibility of sales increase 2) the profitability of the discount driven sales. In F&B industry, sales increase mainly comes from increased guest count. Especially in family restaurants, to increase the number of guests we need to enlarge the size of visitor group (number of visitors for one group) because customers visit by group in a special occasion. And because they pay the bill by group(table), the increase of sales per table is a key measure for sales improvement. The past researches for price & discount sensitivity and reference discount rate explain that price sensitive consumers have narrow reference discount zone and make rational purchase decision. Differently from all time discount scheme of regular sales promotions, the alliance card discount program only provides the right to get discount like discount coupon. And because it is usually once a month opportunity given by the past month usage level, customers tend to perceive alliance card discount as a rare chance to get. So that we can expect customers try to maximize the discount effect when they use the limited discount opportunity. Considering group visiting practice and low visit frequency of family restaurants, the way to maximize discount effect should be the increase the size of visit group. And their sensitivity to discount and rational consumption behavior defer the additional spending for ordering high price menu, even though they get considerable amount of savings from the discount. From the analysis of sales data paid by alliance discount cards for four months, we found the below. 1) The relation between discount rate and number of guest per table is positive : 25% discount results one additional guest 2) The relation between discount rate and the spending per guest is negative. 3) However, total profit amount per table is increased when discount rate is increased. 4) Reward point accumulation & redemption did not show any significant relationship with the increase of number of guests. These results suggest that the allianced discount program substantially contributes to sales increase and profit improvement by increasing the number of guests per table. Though the spending per guest is decreased by discount rate increase, the total amount of profit per table is improved. It seems the incremental profit by increased guest count offsets the profit decrease. Additional intriguing finding is the point reward system does not have any significant impact on the increase of number of guest, even if the point accumulation & redemption of loyalty program are usually regarded as another saving offers by customers. In sum, because it is proved that allianced discount program with credit cards and loyalty cards is effective to both sales drive and profit increase, the alliance card program could be recommended as strategically buyable program.

• Journal of The Korean Society of Grassland and Forage Science
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• v.3 no.2
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• pp.100-111
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• 1983

The research results reported herein had the objectives to understand and analyze the present problems of saemaeul woodland joint cattle grazing system in Kang Won Do and to take steps of improvement. The study results on actual management conditions, problems analyzed and improvement plan of total 208 joint cattle grazing area which was established 105 area in 1981 and 103 area in 1982 were summarized as follows: 1. the effectiveness of joint cattle grazing projects 1) Average daily weight gain of cattle during joint cattle grazing period was 0.4kg, showing higher daily than the conventional feeding of 0.33kg. 2) Increase of total farm income over the conventional feeding system were \1,031,357,320 during the grazing period from May to October in 1982 by adapting the 208 joint cattle grazing system, of which effectiveness of weight gain was \293,075,300 and labor saving was \543,838,750. 3) According to the results of questionaire investigation from 208 joint cattle grazing area, effectiveness of joint cattle grazing system over the conventional system were (1) labor saving, (2) feed cost saving, (3) reduced diseases, (4) increase of number of feeding, (5) inspiration of joint endeavor, (6) effect of more gain, (7) easiness of feeding and feed cost savings. 2. Problems of joint cattle grazing system. 1) Shortages of grass were a problem at second year of joint cattle grazing period due to the low regrowth rate of wild grass. 2) Proper land for woodland joint cattle grazing is belonging to land of Government ownership and it is very hard to get the permission from office of forestry for cattle grazing purpose. 3) It is also difficult to find a proper time of breeding in grazing area by the difficulty of estrus detection. 4) There are a difficulty to give a proper vaccination and medical examination for the grazing cattle. 3. Improvement plans for woodland joint cattle grazing projects. 1) Obtain sufficient roughages by hoof cultivation and oversowing pasture from the second year of joint cattle grazing period. 2) In order to increase the beef production and to use for a calf production area, Government should arrange that all proper grazing land of Government owned in Kang Won Do convert into woodland joint cattle grazing area. 3) Make a good reproductive record by mixed grazing with a excellent breeding cow in a remote area. And carry out the collective artificial insemination with synchronous puberty induced by injection of puberty stimulation hormone. 4) Make a preventive injection for blackleg, twice medication of fasciola hepatica in a year, and spray and medication of tick insecticide. 4. A policy towards upbringing of woodland joint cattle grazing area. 1) Government should thoroughly investigate about a proper land for woodland joint cattle grazing from all forests. 2) When the area is suitable for the woodland joint cattle grazing, though it is national forest or restricted area, government should make it possible to establish a grazing area. 3) On the proper land foe joint cattle grazing in the remote place, Government should support for the road construction and electric fence equipments by using of national funds. 4) There should be an administrative consideration for well promotion of the project that make woodland joint cattle grazing suitable to the characteristics of Kang Won Do. 5) In order to improve the reproduction record, Government should reform the insufficiency of artificial insemination in the joint cattle grazing area. 6) In order to maintain a proper price of cow, Government should carry out the price plan. 7) When there is any request for grassland formation in the woodland joint cattle grazing area, Government should permit it with preference.