• Industry Promotion Research
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• v.7 no.4
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• pp.109-119
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• 2022

In recent years, China's Internet finance industry is hot. There is no doubt that Internet finance has been fully integrated into China, forming a new form of financing, and rapidly becoming a new channel for investment and financing in China, shouldering the responsibility of inclusive financing and building China's real economy. However, with investment, there are risks. Based on the panel data of China's Internet financial platform, this paper uses the random effect model to study the influencing factors of Internet financial risks, and draws three conclusions: (1) The user funds and platform funds of the financial platform will be managed separately by the bank, which can effectively reduce the risk of financial transactions on the Internet; (2) The risk of Internet financial transactions can be effectively reduced by avoiding the concentration of platform funds in the hands of a few borrowers through regulatory policies; (3) The liquidity control of funds effectively reduces the risk of Internet financial transactions. Based on the conclusions, we propose optimization strategies for regulatory policies to achieve the healthy and sustainable development of Internet finance.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.431-444
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• 2023

Purpose - This study applies the traditional Structure-Conduct-Performance (SCP) model from industrial organization theory to investigate the relationship between market structure and performance in China's banking industry. Design/methodology/approach - For analysis, financial data from the People's Bank of China's "China Financial Stability Report" and financial reports of 6 state-owned banks and 11 joint-stock banks for the period 2010 to 2021 were collected to create a balanced panel dataset. The study employs panel fixed-effects regression analysis to assess the impact of changes in market structure and ownership structure on performance variables including return on asset, profitability, costs, and non-performing loan ratios. Findings - Empirical findings highlight significant differences in the effects of market structure between state-owned and joint-stock banks. Notably, increased market competition positively correlates with higher profits for state-owned banks and with lower costs for joint-stock banks. Research implications or Originality - State-owned banks demonstrate larger scale and stability, yet they struggle to respond effectively to market shifts. Conversely, joint-stock banks face challenges in raising profitability against competitive pressures. Additionally, the study emphasizes the importance for Chinese banks to strengthen risk management due to the increase of non-performing loans with competition. The results provide insights into reform policies for Chinese banks regarding the involvement of private sector in the context of market liberalization process in China.

• Journal of the Korean Society for Library and Information Science
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• v.4
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• pp.43-71
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• 1975

Operations research has developed rapidly since its origins in World War II. Practitioners of O. R. have contributed to almost every aspect of government and business. More recently, a number of operations researchers have turned their attention to library and information systems, and the author believes that significant research has resulted. It is the purpose of this essay to introduce the library audience to some of these accomplishments, to present some of the author's hypotheses on the subject of library management to which he belives O. R. has great potential, and to suggest some future research directions. Some problem areas in librianship where O. R. may play a part have been discussed and are summarized below. (1) Library location. It is usually necessary to make balance between accessibility and cost In location problems. Many mathematical methods are available for identifying the optimal locations once the balance between these two criteria has been decided. The major difficulties lie in relating cost to size and in taking future change into account when discriminating possible solutions. (2) Planning new facilities. Standard approaches to using mathematical models for simple investment decisions are well established. If the problem is one of choosing the most economical way of achieving a certain objective, one may compare th althenatives by using one of the discounted cash flow techniques. In other situations it may be necessary to use of cost-benefit approach. (3) Allocating library resources. In order to allocate the resources to best advantage the librarian needs to know how the effectiveness of the services he offers depends on the way he puts his resources. The O. R. approach to the problems is to construct a model representing effectiveness as a mathematical function of levels of different inputs(e.g., numbers of people in different jobs, acquisitions of different types, physical resources). (4) Long term planning. Resource allocation problems are generally concerned with up to one and a half years ahead. The longer term certainly offers both greater freedom of action and greater uncertainty. Thus it is difficult to generalize about long term planning problems. In other fields, however, O. R. has made a significant contribution to long range planning and it is likely to have one to make in librarianship as well. (5) Public relations. It is generally accepted that actual and potential users are too ignorant both of the range of library services provided and of how to make use of them. How should services be brought to the attention of potential users? The answer seems to lie in obtaining empirical evidence by controlled experiments in which a group of libraries participated. (6) Acquisition policy. In comparing alternative policies for acquisition of materials one needs to know the implications of each service which depends on the stock. Second is the relative importance to be ascribed to each service for each class of user. By reducing the level of the first, formal models will allow the librarian to concentrate his attention upon the value judgements which will be necessary for the second. (7) Loan policy. The approach to choosing between loan policies is much the same as the previous approach. (8) Manpower planning. For large library systems one should consider constructing models which will permit the skills necessary in the future with predictions of the skills that will be available, so as to allow informed decisions. (9) Management information system for libraries. A great deal of data can be available in libraries as a by-product of all recording activities. It is particularly tempting when procedures are computerized to make summary statistics available as a management information system. The values of information to particular decisions that may have to be taken future is best assessed in terms of a model of the relevant problem. (10) Management gaming. One of the most common uses of a management game is as a means of developing staff's to take decisions. The value of such exercises depends upon the validity of the computerized model. If the model were sufficiently simple to take the form of a mathematical equation, decision-makers would probably able to learn adequately from a graph. More complex situations require simulation models. (11) Diagnostics tools. Libraries are sufficiently complex systems that it would be useful to have available simple means of telling whether performance could be regarded as satisfactory which, if it could not, would also provide pointers to what was wrong. (12) Data banks. It would appear to be worth considering establishing a bank for certain types of data. It certain items on questionnaires were to take a standard form, a greater pool of data would de available for various analysis. (13) Effectiveness measures. The meaning of a library performance measure is not readily interpreted. Each measure must itself be assessed in relation to the corresponding measures for earlier periods of time and a standard measure that may be a corresponding measure in another library, the 'norm', the 'best practice', or user expectations.

• Journal of the Korean association of regional geographers
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• v.12 no.1
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• pp.154-171
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• 2006

By comparing to Chinese American banks, this research shows the uniqueness of Korean American banks. This article argues that instead of the cultural attributes and/or informal financial institutions, formal financial institutions, such as the ethnic banks studied here, are responsible for the business success of Asians abroad. However, ethnic banks have different development trajectories depending on their respective ethnic communities. Korean American banks are notably different from Chinese American banks in terms of growth, profitability, and banking strategies. Although both ethnic banks exercise relationship banking strategies in their loan portfolios, their deposit compositions are very different and cause significant differences in financial performance. The focus on business loans and high rates of non-interest deposits allow for higher growth rates in Korean American banks. Therefore, relationship banking does not adequately explain the differences of ethnic banks. This research attempts to understand the underlying factors in choosing banking strategies by mainly focusing on the unique examples found in Korean and Chinese immigrant societies. For Chinese Americans, the heterogeneity of their population composition and foreign influence dominate their bank structures. On the other hand, Korean American homogeneity and business orientation are distinctly different. The influence of Korean capital is not significant when compared to overseas Chinese capital.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.113-118
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• 2023

This study analyzed the effects of macroeconomic variables, including housing affordability, and bank loan-related variables on variation in housing prices using multiple regression models. As a result of the analysis, consumer price growth rate, the total currency growth rate, and the housing affordability growth rate had a significant positive effect on changes in housing prices. As a result of analyzing the period of rising and falling housing prices, consumer price growth rate and the total currency growth rate during the period of rising housing prices had a significant positive effect on housing prices. Unlike the period of rising housing prices, the growth rate of household loans was found to have a significant positive effect on changes in housing prices. On the other hand, unlike the period of rising housing prices, the growth rater of mortgage loans was found to have a significant negative effect on changes in housing prices. The growth rate of housing affordability index did not have a significant positive effect on changes in housing prices during a falling housing prices. The determinants of housing prices showed different patterns during the period of rising housing prices and falling housing prices.

• Economic Analysis
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• v.25 no.4
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• pp.1-24
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• 2019

This study examines the labor market performance of graduates who had student loans. Compared to earlier studies, we extended analyses to all jobs that were experienced for more than 18 months after graduation. First, we found that students who had student loans earned 2.81% less at their first job compared to their counterparts without student loans. Second, the wage gap decreased over time, a reduction of 0.66%p due to labor market turnovers. Third, when we compared cumulated labor income, however, the amount for borrowers were continuously higher. This is because the job searching period of a borrower was shorter, despite relatively lower wages at the first job, and borrowers also made more frequent job turnovers, accompanying relatively more wage increases. These results suggest that the negative effects of college loans on earnings, reported in previous studies, may have exaggerated the negative impact to some extent of having loans. However, when we look at the quality of jobs beyond simply wages, the proportion of borrowers working at large companies as regular workers was consistently low. Given that job conditions at the earlier stages of one's career may lead to gaps over time, our findings call for more systematic investigations into the effects that student loans have on long-term labor performance.

• Korean Association of Arts Management
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• no.51
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• pp.135-166
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• 2019

Recently, the Japan Cultural Agency announced a plan for revitalizing the art market represented by reading museums (advanced art museums) to promote industry through strengthening the sustainability and economics of art museums. Along with these policy announcements, the Japanese cultural system and Bypyeongje are divided into pros and cons, and there has been a heightened opposition, which is now in a state where policy promotion has been temporarily suspended. The opposite reason is that it does not meet the museum's inherent purpose of preservation and lore, and the reason for favoring that commercialism can ruin the art world is that the Japanese art society is other than art museums and museums Also, it consists of non-profit organizations, art festival administration organizations, support staff, volunteers, etc., but because of the high subsidy bias, no real labor costs are paid, which means that it is virtually neglected. Also, there is a vigilance that the art society itself, which reduces its reliance on subsidies in response to social changes, can survive. Seeing that the situation is not much different from Japan, Korea is also actively discussing new establishments of the National Art Bank, performing art appraisal and evaluation functions for revitalizing art works, art loan, art trust, etc. There is. As it is difficult to solve realistic problems with subsidies from the future situation, it is difficult for us to expand investment in culture, and culture and economy are united and linked. You will find a plan to make it operational. In this regard, it is thought that the examination of the cultural and economic agency's strategy, represented by the Japanese advanced art museums, gives us a meaningful suggestion.

• KDI Journal of Economic Policy
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• v.13 no.1
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• pp.35-63
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• 1991

Currently, Korea's banking industry holds a sizable amount of non-performing loans which stem from the government-led bailout of many troubled firms in the 1980s. Although this burden was somewhat relieved with the aid of banks' recapitalization in the booming securities market between 1986-88, the insolvent credits still resulted in low profitability in the banking sector and have been detrimental to the progress of financial liberalization and internationalization. This paper surveys the corporate bailout experiences of major advanced countries and Korea in the past and derives a rationale for readjustment measures against non-performing loans, in which rescue plans depend on the nature of the financial system. Considering the features of Korea's financial system and the banking sector's recent performance, it discusses possible means of liquidation in keeping with the rationale. The conflict of interests among parties involved in non-performing loans is widely known as one of the major constraints in writing off the loans. Specifically, in the case of Korea, the government's excessive intervention in allocating credits has preempted the legitimate role of the banking sector, which now only passively manages its past loans, and has implicitly confused private with public risk. This paper argues that to minimize the incidence of insolvent loan readjustment, the government's role should be reduced and that the correspondent banks should be more active in the liquidation process, through the market mechanism, reflecting their access to detailed information on the troubled firms. One solution is that banks, after classifying the insolvent loans by the lateness or possibility of repayment, would swap the relatively sound loans for preferred stock and gradually write off the bad ones by expanding the banks' retained earnings and revaluing the banks' assets. Specifically, the debt-equity swap can benefit both creditors and debtors in the sense that it raises the liquidity and profitability of bank assets and strengthens the debtor's financial structure by easing the debt service burden. Such a creditor-led or market-led solution improves the financial strength and autonomy of the banking sector, thereby fostering more efficient resource allocation and risk sharing.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.