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The revised Credit Information Act reorganized the structure of the credit information-related industry and renewed the definition of business by reducing the scope of its own work while dividing the credit inquiry business into individual credit evaluation business, individual business credit evaluation business, and corporate credit inquiry business. The credit inquiry business is losing its own significance because the tasks defined as incidental services of the business, which were excluded from the definition of a subdivided business and the scope of the unique work, overlap with the unique work of the credit inquiry business. It is deemed reasonable to abolish the credit-related business (personal credit evaluation, personal business credit evaluation, corporate credit inquiry) or credit information business, and to absorb any overlap with credit-related business in the relationship between the principal credit information inquiry business and the collection business, and to hand over other business to the private sector or the law on detective work. The revised Act excluded the collection business from the scope of the credit information business, but it remains in the Credit Information Act. The collection, which is difficult to see as an industry related to credit information, is considered desirable to transfer to the Act on the Fair Collection or the Act on the Registration of Loan Business, etc. and the Protection of Financial Users.

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The recent development of information and telecommunication technologies made both the access to and the distribution of personal data extremely diverse and complicating. This caused numerous events of misuse accidents regarding personal data, which brought about society's full attention to the issues on the personal data protection. However, since sharing personal credit information also has various benefits, it is an important decision how to balance between protecting personal privacy and promoting data sharing. Contributing to find a best decision on this matter, this paper investigates the credit information sharing systems and the personal credit data protection regulations of other major countries such as US, Japan, Germany, France and Italy. We finds that those countries are not only very strict in protecting personal data but also equipped with various routes for individuals to actively participate in the process of sharing and utilizing credit information, which suggests many valuable implications to restructuring personal data protection regulations of Korea in recent years.

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This paper studies the effects of negative and/or positive credit information sharing between two heterogeneous banks that compete in price for the lending on each bank's profit. The model predicts that negative credit information sharing benefits all banks. We also find that positive credit information sharing is more easily added to existing negative credit information sharing than introduced independently. All these findings are consistent with the facts about the current private credit information sharing system over the world.

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This study analyzed the pattern of changes in the credit informationindustry following the enactment and amendment of Credit InformationAct. Especially, the revised bill of Credit Information Act(November 15,2018) has actively accommodated the global environmental change of thetransition to Data Economy and adopted overseas legislation cases ofdata regulation in accordance with domestic circumstances. When thisamendment is enacted, the scope of credit information business issegmented, new players in business enter the market, I expect majorchanges in the existing credit information industry. In addition, it isalso anticipated that different strategies among existing and newbusinesses will be implemented and the market size of the creditinformation industry will be expanded significantly as the sales of creditbureaus increase. However, refined policy supplement is highly necessaryto minimize side effects from rapid changes while watching the transitionand growth of credit information industry as data industry.

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Credit ratings play important roles in financial markets such as financial intermediation, risk reduction, and mitigating information asymmetry. However, in terms of providing information regarding a firm¡¯s future credit situation, credit ratings might not be a perfect indicator because of their static nature. Beside credit ratings, rating agencies, such as Moody¡¯s and Standard & Poors, also publish rating watches and rating outlooks. They convey slightly different credit information and can compliment credit ratings. While previous studies cover the role of credit watches in Korea, to our knowledge, it is the first study on how credit rating outlooks affect credit ratings using Korean database. First, we are interested in whether rating outlooks, such as positive, stable, and negative outlooks, indicate how a firm¡¯s future rating looks like. Then, if a firm receives a negative outlook from a rating agency, the firm needs to fix its problems. Otherwise, the agency may downgrade the firm¡¯s credit rating and the downgrade would be critical especially if the firm sits in certain thresholds in ratings, such as A or BB. We consider this chain of actions as a function of credit rating improvement. With credit rating outlooks information from NICE Information Service, we first conduct event studies to examine how the financial markets respond to different rating outlooks. Consistent with previous studies, we find that the stock market negatively responds to negative outlooks with a statistical significance. However, the market¡¯s reaction to positive rating outlooks is not statistically significant. Therefore, bad news may deliver some valuable information to the market, while good news may not. We further investigate how each rating outlook affects under different evaluations of main, scheduled, and unscheduled. Among them, main evaluations have the biggest impacts on stock price. Thus it would be difficult to analyze the effects of scheduled and unscheduled evaluations without considering main evaluations. Then, we analyze factors regarding actual rating downgrades after firms¡¯ receiving negative or positive outlooks. We apply a probit model regression and find the following results. First, firms with higher leverage are more likely to be actually downgraded after receiving a negative outlook, and the result is consistent with previous literature. Second, firms with a credit rating of A+, A0, or A- are more likely affected by ¡°negative outlooks.¡± We conjecture that if a firm belongs to ¡°A¡± or higher rating, outside investors may consider the firm as a reliable one because of its ¡°A¡± status. Finally, we examine factors affecting firms intermediate cumulative abnormal returns(CARs) after receiving downgrading outlooks in multiple regression settings. We find that firms with a relatively higher leverage, a lower growth potential, a higher market risk and a greater probability of falling to default grade suffer from intermediate CARs. However, we observe a strange phenomenon that firms likely to be downgraded to below B- somehow improve their intermediate CARs. We consider this as a potential for credit rating improvements, and believe why credit rating outlooks can complement credit ratings.

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Credit information sharing system is the set of laws and institutions that enables efficient and effective access to credit information of clients of financial institutions. Credit registries (CR) and credit bureaus (CB) are the main players of the credit information systems. They enable financial institutions to access to complete, accurate, and reliable information on potential borrowers, contributing to the growth of credit-based economy. Countries over the world have various models for the credit information sharing system, and there is no one correct answer. Korea started with only a CR, but today it has both a CR and two CBs. Since it can take a very long time for CBs to emerge in the market, the Korean experience of establishing CR and allowing information sharing between the CR and CBs can be a good example for developing countries. Another merit of the Korean credit information system is that it guarantees fair competition among private information providers. This paper examines the historical development of the Korean credit information system and suggests future policy tasks.

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In the Age of Information, the sucess of business depends on getting useful informations. It's also suggested that management of credit-information is important factor for the competitiveness in the world of finance. To Strengthen credit-information management, we need an apt attitude to handle credit-information and the innovative system management is also needed. By doing theses it is possible for finance institution to deal with limited resource and time efficently. 1. It is required to convert to customer - Oriented credit evaluation system. Fiance Institutions break from simplicity of rating, and broden to develop would-be excellent customer. Of course, to do this, credit material should be valuable and decisive. 2. We have to make the rest use of processed information. Processed information should be remain valuable, and approchable by computer system. And it should be brand-new information that is continousally followed up according to business situations. It is necessary that On-Line information system is broadly developed, and nence, credit business information should be thought as public owned and exchangeable. Public-owned menas cutting of cost in collecting information. That could be achieved easily by establishment of collection center of credit information. 3. Establishment of General Credit Information Insititution, that gather and evaluate all kinds of credit information, should be propelled. Would-be customer of credit information including Finance Institution wants to become some believable Institution in, collecting, evaluating, offering and expressing credit situation and credit ability for a enterprise. Ideal Model of Institution will be supported by Government, so that it stands no prejudiced. When Government needs some information of a business it can use objective information offered by the special institution with transporency. As we see in capital encroachment in some company casued by profit aggravation it is really required to institutionalize credit information processing system. We know it is impossible to institutionalze without government support. In conclusion, to realize credit firt society, the normalization of Finance and the bringing into open in Finance transaction are needed. And normalization of Finance and opress in finance transation will be accomplished by demand increase in credit information and understanding credit-mangement importance.

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Recently, in Korea, Kakao Corp. and KT Corp. have won preliminary licenses to run Internet-only banks. The two consortiums are expected to focus primarily on providing medium-cost loans to people with low credit standings. To serve these people, the two banks should be able to analyze their creditworthiness. Therefore, It is expected that the necessity of collecting and using non-financial data as well as traditional credit data for credit scoring would be increased.In fact, until now, underwriting credit risk of consumer has relied heavily on financial data inputs. But for micro-enterprises we focus on in this study, the traditional financial data inputs are generally unavailable in the financial market, so it has served as an obstacle to evaluate consumer credit risk.Under this circumstance, this paper examined, using micro-enterprises data of credit-guarantee foundations, the efficiency of adding non-financial data to a traditional credit scoring model (CB) on micro-enterprise consumers, and could not find the improvement in scoring model performance with inclusion of non-financial data in CB credit-rating information.

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Due to the recent event in January 2014 that the customer information of major 3 card companies has been mass-released occured, the Act on Use and Protection of Credit Information (hereinafter 'the new revised Act') was comprehensively revised and the amendments taken into effective from September 12, 2015. The new revised Act contains quite innovative regulation contents such as reenforcement of agreement procedure on collection, use and provide of credit information, reorganization of integrated management system on credit information, insuring obligation of liability insurance, etc. On the other hand the new revised Act was focused on protection of principals of credit information, and consequently credit information company's business activities or effective use was relatively handled carelessly. I am sorry that the new revised Act was not revised in a balanced way between credit information companies and credit information proposals. In this connection, I will review the new revised Act's main contents, regulatory effectiveness, etc., find problems and suggest improvement proposals. I hope this study will be of help to the balanced development between protection of credit information proposals and sound development of credit information companies.

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Ever since central-local governments and public agencies claimed that they would have their databases available and publicly open in 2013, not only has it led to economic ripple effects such as creating jobs and start-up opportunities, but to social values making government more open and enhancing civic participation. In particular, consumer credit data is expected to have economic value more than ever, especially, when analyzed along with upstream and downstream sector information. However, such personal information has relatively high risk of exposure of privacy. As an alternative to releasing real credit data, synthetic data generation, which preserves the statistical characteristics of raw data but does not include actual data, or includes only the insensitive data, has been suggested and practiced. In this study, we use R package synthpop to investigate the possibility of generating credit data reflecting the characteristics of time series and individual financial activities.

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