Sunday, May 17, 2020
Study On Mortgage Lending Patterns In China - Free Essay Example
Sample details Pages: 9 Words: 2571 Downloads: 7 Date added: 2017/06/26 Category Finance Essay Type Essay any type Did you like this example? Introduction Objective Why study this issue organisation of the dissertation With Chinas rapid economic development, urbanization advance, driven by domestic demand and improved living standards, the residentsà ¢Ã¢â€š ¬Ã¢â€ž ¢ demand for housing improvement has been increasing. In the foreseeable future, China will have a thriving real estate development space and potential. Financial support is necessary for real estate development, especially housing mortgage loans. Don’t waste time! Our writers will create an original "Study On Mortgage Lending Patterns In China" essay for you Create order For Commercial Banks in China, this is a huge cake and cheese. The one with best risk-management abilities and tools will be able to gain more market share. This dissertation take China Merchants Bank as case study on the design, methods, processes, data, development and verification of housing mortgage loans scoring card, propose home mortgage loans scorecard model, and be used effective and widely. Literature Review à ¢Ã¢â€š ¬Ã¢â‚¬Å" Credit Scoring/Sub-prime crisis Mortgage contracts/types of mortgages Credit Scoring technologies are used to control levels of default within american consumer credit. And such technologies have been involved with its own methodological, procedural and temporal risks. And periodic renewal of models and constant reappraisal of methods and procedures are required in accessing the risk. Through testing a diffusion model of techbology adoption for the financial services industry, we find that banking organizations that are more centralized in their organizational structure and those located in the New York Federal Reserve district adpted small business credit scoring before their peers. The former is due to the influence of organizational structure on technology adoption, and the latter is consistent with theories of geography-dependent innovation diffusion. Race is influential to the mortgage lending disicion in USA. However, it is not important in China. Profession and income level have greater effect on the probability of getting the loan. I will dev elop another critiria to understand the pattern in China based on the study of à ¢Ã¢â€š ¬Ã…“Understanding Mortgage Lending Patternsà ¢Ã¢â€š ¬? by Issac F. Megbolugbe. Background of mortgage lending in China Strong growth in Chinas housing markets. The housing mortgage in China is not very old in comparison to others. 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In 2007, CMB developed its mortgage loan application scoring model, and the model was applied countrywide to all its 700 branches next year. In 2009, with the progress of Basel II Accord implementing in Chinese banking industry, CMB developed its application scoring model, behavior scoring model, collection scoring model of mortgage loan, auto loan, personal consumption loan in succession to measure and manage its risk in a more accurate way. As for now, scoring model systems are used in the bank to cover over 95 percent of loan business in retail banking sector through various process including loan application, marketing, pricing, after sale management, default loan collection, etc. CMBà ¢Ã¢â€š ¬Ã¢â€ž ¢s mortgage loan application scoring model uses the same methodology as that in those active European and American banks. By collecting debtorà ¢Ã¢â€š ¬Ã¢â€ž ¢s risk characteristics information, shaping its default definition and performance period, utilizing logistic regression based on 0/1 distribution of dependent variable, using KS statistical analysis to test the modelà ¢Ã¢â€š ¬Ã¢â€ž ¢s predictive capability, the scoring model was finally established. Due to the difference in Chinaà ¢Ã¢â€š ¬Ã¢â€ž ¢s political, economic and cultural environment with western countries, CMBà ¢Ã¢â€š ¬Ã¢â€ž ¢s credit scoring model also differs in its design details from European and American banks. With the relatively short history in studying an d adopting credit scoring model in Chinese banking industry, some shortfalls in date collection was also in existence and will be reflected in the independent risk variables as the result of the credit scoring model. For example, CMB generated different scoring model for different regional segmentation in its model designing period. The reason relies on the unbalanced economical development and different demographical characteristics and risk characteristics through over the country. The risk characteristics like age, income can have totally different impact to the credit scoring model. In some cities, elder applicant represents high income level and stable economic status, thus the possibility of loan default is low. While in some other cities, younger applicant can get financial support from the whole family, thus means lower risk of this type of applicants. However, European banks usually apply only one consistent model in one country. For some small banks, one consistent mode l will be applied even in several countries due to the lack of adequate sample date and similar economic and cultural environment. Another example is that the demographical information in CMB sample data is not so credible as that for Western Banksà ¢Ã¢â€š ¬Ã¢â€ž ¢. Most of the demographical information in CMB data comes from the application form which is filled out by applicants themselves. Some demographical information, like income, marital status, could not be verified through any official credit agency. In some occasions, applicants may exaggerate their income level or distort their marital status to meet the credit approval requirement of the bank. So the authenticity of the date could not guaranteed, and the bank must use those information cautiously. The relationship manager of the bank always need to assess their customersà ¢Ã¢â€š ¬Ã¢â€ž ¢ risk level by using the tools bank provided or with their own experience, but the assessment result are usually not quantitative ou tput and can not be used in building the credit scoring models. While for European and American banks, the authoritative credit agencies provided a transparent and credible information environment. Banks can cheaply and conveniently access to the credit agencies for demographical information of applicants, including age, dwelling address, telephone number, period in current employment, household income, other outstanding loan, default record and tax information, and those electric information can be downloaded and integrated into the banksà ¢Ã¢â€š ¬Ã¢â€ž ¢ database system for the purpose of building the credit scoring model. To compare the credit scoring model development process in CMB and CITI Bank of USA, (hereinafter referred to as à ¢Ã¢â€š ¬Ã…“CITIà ¢Ã¢â€š ¬?), we found the same basic methodology are adopted, both banks using logistic regression to create their mortgage application scoring models, the default definition and performance period are quite close, and KS tes ting, out-of-sample testing and cross-time testing are all applied to validate the modelà ¢Ã¢â€š ¬Ã¢â€ž ¢s effectiveness. The main discrepancy rest with the date sample date sector and can be sorted as follows: Firstly, the sample date is easily accessible from credit agencies for Citi bank, and the bank use extensively those date in its model building process. There are more than 1000 credit agencies in USA and mostly of them are subjected to three most authoritative credit agencies: Experian, TransUnion and Equifax. Citi bank receives credit information both directly from Experian and from their outsourcing credit enquiry companies in Georgia and South Dakota. But for Chinese banks, including CMB, the one and only credit information channel is the PBOC(Peopleà ¢Ã¢â€š ¬Ã¢â€ž ¢s Bank of China) Credit Center established few years ago. This official credit agency started to provide its credit query service to commercial banks only in 2008. Due to its limited history, more than ha lf of the nationà ¢Ã¢â€š ¬Ã¢â€ž ¢s population are still excluded from outside the system. For many applicants, Credit Center could neither verify their demographical information nor find credit record for them. Furthermore, the credit query service do not provide mass electronic date but only printable date, thus made the integration of query results with banks database an impossible mission. Secondly, for Citi bank, some demographical information, like race, gender, canà ¢Ã¢â€š ¬Ã¢â€ž ¢t be used in credit scoring model development due to the restriction of laws and regulations. Otherwise, the discrimination between loan applicants with different races or genders may cause serious consequences such as lawsuit against the bank. But there is not such limitation in both Chinaà ¢Ã¢â€š ¬Ã¢â€ž ¢s banking regulations and traditional morality, the bank could use such information to discriminate their customers in the credit scoring model if only they have enough predictive ability and business sense. Thirdly, in Citi bankà ¢Ã¢â€š ¬Ã¢â€ž ¢s credit scoring model, the information of refusal debtorsà ¢Ã¢â€š ¬Ã¢â€ž ¢ are also deemed as sample date, thus provide a new dimension to analysis the customersà ¢Ã¢â€š ¬Ã¢â€ž ¢ risk characteristics. The bank may summarize rules from the risk characteristics of those rejected applicants and adopted into the credit approval guidelines for further practice operations. CMB did not reserve any information about rejected applicant in past so that its credit scoring system did not involve any reject inference activity. Recently, CMB has started to collect information about rejected applicant, but the information canà ¢Ã¢â€š ¬Ã¢â€ž ¢t be used in adjust the model only when they accumulated to a certain amount after about five years. Generally speaking, CMB has already established a series of credit scoring model to cover its retail banking business including mortgage loan by using universal methodology. However, the date col lection is one of its main shortages for the bank to improve the quality of its modelling practice. 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¢Ãƒ £Ã¢â€š ¬Ã¢â‚¬ ¹Ãƒ ¯Ã‚ ¼Ã…’à ¥Ã¢â‚¬ ¦Ã‚ ¶Ãƒ ¤Ã‚ ¸Ã‚ à ¥Ã‚ ¯Ã‚ ¹Ãƒ ©Ã¢â‚¬Å" ¶Ãƒ ¨Ã‚ ¡Ã…’à ¥Ã‚ ºÃ¢â‚¬ à §Ã¢â‚¬  ¨Ãƒ ¤Ã‚ ¿Ã‚ ¡Ãƒ §Ã¢â‚¬  ¨Ãƒ ¨Ã‚ ¯Ã¢â‚¬Å¾Ãƒ §Ã‚ ºÃ‚ §Ãƒ ¦Ã‚ ¨Ã‚ ¡Ãƒ ¥Ã… ¾Ã¢â‚¬ ¹Ãƒ ¦Ãƒ ¥Ã¢â‚¬ ¡Ã‚ ºÃƒ ¤Ã‚ ºÃ¢â‚¬ à ¤Ã‚ »Ã‚ ¥Ãƒ ¤Ã‚ ¸Ã¢â‚¬ ¹Ãƒ ¨Ã‚ ¦?à ¦Ã‚ ±Ã¢â‚¬Å¡Ãƒ ¯Ã‚ ¼Ã… ¡ à §Ã¢â‚¬ ¢Ã‚ ¥Ãƒ ¯Ã‚ ¼Ã‹â€ à ¨Ã‚ ¯Ã‚ ¦ à ¨Ã‚ §?à ¨Ã¢â‚¬ ¹Ã‚ ±Ãƒ ¦Ã¢â‚¬â€œÃ¢â‚¬ ¡Ãƒ ©Ã†â€™Ã‚ ¨Ãƒ ¥Ã‹â€ †à ¯Ã‚ ¼Ã¢â‚¬ ° à ¥Ã‚ °Ã‚ ½Ãƒ §Ã‚ ®Ã‚ ¡Ãƒ ¤Ã‚ »Ã‚ ¥Ãƒ ¤Ã‚ ¸Ã… à ©Ã‹â€ à ¥Ã‚ ¯Ã‚ ¹Ãƒ ¤Ã‚ ¿Ã‚ ¡Ãƒ §Ã¢â‚¬  ¨Ãƒ ¨Ã‚ ¯Ã¢â‚¬Å¾Ãƒ §Ã‚ ºÃ‚ §Ãƒ ¤Ã‚ ½Ã¢â‚¬Å"à §Ã‚ ³Ã‚ »Ãƒ §Ã… ¡Ã¢â‚¬Å¾Ãƒ §Ã¢â‚¬ ºÃ¢â‚¬ËœÃƒ §Ã‚ ®Ã‚ ¡Ãƒ ¨Ã‚ ¦?à ¦Ã‚ ±Ã¢â‚¬Å¡Ãƒ ¦Ã‚ ¯Ã¢â‚¬ à ¨Ã‚ ¾Ã†â€™Ãƒ ¥Ã… ½Ã… ¸Ãƒ ¥Ã‹â€ â„ ¢Ãƒ ¦Ã¢â€š ¬Ã‚ §Ãƒ ¯Ã‚ ¼Ã…’à ¤Ã‚ ½Ã¢â‚¬ à ¤Ã‚ ¸Ã‚ à ¥Ã¢â‚¬ ºÃ‚ ½Ãƒ ©Ã¢â‚¬Å" ¶Ãƒ §Ã¢â‚¬ ºÃ¢â‚¬ËœÃƒ ¤Ã‚ ¼Ã… ¡Ãƒ ¥Ã‚ ¯Ã‚ ¹Ãƒ ¥Ã…’†¦Ãƒ ¦Ã¢â‚¬ ¹Ã‚ ¬Ãƒ ¦Ã¢â‚¬ ¹Ã¢â‚¬ ºÃƒ ¥Ã¢â‚¬ ¢Ã¢â‚¬ à ©Ã¢â‚¬Å" ¶Ãƒ ¨Ã‚ ¡Ã…’à ¥Ã…“ ¨Ãƒ ¥Ã¢â‚¬ †¦Ãƒ §Ã… ¡Ã¢â‚¬Å¾Ãƒ ¤Ã‚ ¸Ã‚ à ¥Ã¢â‚¬ ºÃ‚ ½Ãƒ ¥Ã¢â‚¬ °?à ¥Ã¢â‚¬ ¦Ã‚ à ¥Ã‚ ¤Ã‚ §Ãƒ ¥Ã¢â‚¬ ¢Ã¢â‚¬ à ¤Ã‚ ¸Ã… ¡Ãƒ ©Ã¢â‚¬Å" ¶Ãƒ ¨Ã‚ ¡Ã…’à §Ã… ¡Ã¢â‚¬Å¾Ãƒ ©Ã‚ £Ã… ½Ãƒ ©Ã¢â€ž ¢Ã‚ ©Ãƒ ¨Ã‚ ¯Ã¢â‚¬Å¾Ãƒ §Ã‚ ºÃ‚ §Ãƒ ¦Ã‚ ¨Ã‚ ¡Ãƒ ¥Ã… ¾Ã¢â‚¬ ¹Ãƒ ¥Ã‚ §Ã¢â‚¬ ¹Ãƒ §Ã‚ »Ã‹â€ à §Ã‚ ´Ã‚ §Ãƒ ¥Ã‚ ¯Ã¢â‚¬ à ¥Ã¢â‚¬ ¦Ã‚ ³Ãƒ ¦Ã‚ ³Ã‚ ¨Ãƒ ¯Ã‚ ¼Ã…’à ¥Ã‚ ¯Ã‚ ¹Ãƒ ¦Ã‚ ¨Ã‚ ¡Ãƒ ¥Ã… ¾Ã¢â‚¬ ¹Ãƒ ¤Ã‚ »Ã … ½Ãƒ ¦Ã¢â‚¬ ¢Ã‚ °Ãƒ ¦? ®Ãƒ ¦Ã¢â‚¬  ¶Ãƒ ©Ã¢â‚¬ ºÃ¢â‚¬ à £Ã¢â€š ¬?à ¨Ã‚ ®Ã‚ ¾Ãƒ ¨Ã‚ ®Ã‚ ¡Ãƒ ¦Ã¢â‚¬â€œÃ‚ ¹Ãƒ ¦Ã‚ ³Ã¢â‚¬ ¢Ãƒ ¥Ã‹â€  °Ãƒ ¦Ã…“â‚ ¬Ãƒ §Ã‚ »Ã‹â€ à §Ã… ¡Ã¢â‚¬Å¾Ãƒ ¥?‚à ¦Ã¢â‚¬ ¢Ã‚ °Ãƒ §Ã‚ »Ã¢â‚¬Å"à ¦Ã… ¾Ã…“à ©Ã†â€™Ã‚ ½Ãƒ ¨Ã‚ ¿Ã¢â‚¬ ºÃƒ ¨Ã‚ ¡Ã…’à ¤Ã‚ ºÃ¢â‚¬ à ¥Ã‚ ®Ã‚ ¡Ãƒ ¦Ã¢â‚¬ ¦Ã… ½Ãƒ ¨Ã¢â€š ¬Ã…’à ¤Ã‚ ¸Ã‚ ¥Ãƒ ¦Ã‚  ¼Ãƒ §Ã… ¡Ã¢â‚¬Å¾Ãƒ ¦Ã‚ £Ã¢â€š ¬Ãƒ ©Ã‚ ªÃ…’à ¨Ã‚ ¯Ã¢â‚¬Å¾Ãƒ ¤Ã‚ ¼Ã‚ °Ãƒ £Ã¢â€š ¬Ã¢â‚¬Å¡ à ¦Ã‚  ¤Ãƒ ¥Ã‚ ¤Ã¢â‚¬â€œÃƒ ¯Ã‚ ¼Ã…’2010à ¥Ã‚ ¹Ã‚ ´6à ¦Ã…“ˆÃ ¯Ã‚ ¼Ã…’à ¥Ã…“ ¨Ãƒ ¤Ã‚ ¸Ã‚ à ¥Ã¢â‚¬ ºÃ‚ ½Ãƒ ©Ã¢â‚¬Å" ¶Ãƒ §Ã¢â‚¬ ºÃ¢â‚¬ËœÃƒ ¤Ã‚ ¼Ã… ¡Ãƒ §Ã… ¡Ã¢â‚¬Å¾Ãƒ §Ã‚ »Ã… ¸Ãƒ ¤Ã‚ ¸Ã¢â€š ¬Ãƒ ¨Ã‚ ¦?à ¦Ã‚ ±Ã¢â‚¬Å¡Ãƒ ¥Ã…’à §Ã‚ »Ã¢â‚¬Å¾Ãƒ §Ã‚ »Ã¢â‚¬ ¡Ãƒ ¤Ã‚ ¸Ã¢â‚¬ ¹Ãƒ ¯Ã‚ ¼Ã…’à ¤Ã‚ ¸Ã‚ à ¥Ã¢â‚¬ ºÃ‚ ½Ãƒ ¤Ã‚ ¸Ã‚ »Ãƒ ¨Ã‚ ¦?à ¥Ã¢â‚¬ ¢Ã¢â‚¬ à ¤Ã‚ ¸Ã… ¡Ãƒ ©Ã¢â‚¬Å" ¶Ãƒ ¨Ã‚ ¡Ã…’à ¥Ã‚ ¯Ã‚ ¹Ãƒ ¤Ã‚ ½?à ¦Ã‹â€  ¿Ãƒ ¨Ã‚ ´Ã‚ ·Ãƒ ¦Ã‚ ¬Ã‚ ¾Ãƒ ¨Ã‚ ¿Ã¢â‚¬ ºÃƒ ¨Ã‚ ¡Ã…’à ¤Ã‚ ºÃ¢â‚¬ à ¥Ã… ½Ã¢â‚¬ ¹Ãƒ ¥Ã… †ºÃƒ ¦Ã‚ µÃ¢â‚¬ ¹Ãƒ ¨Ã‚ ¯Ã¢â‚¬ ¢Ãƒ ¯Ã‚ ¼Ã…’à §Ã‚ »Ã¢â‚¬Å"à ¦Ã… ¾Ã…“à ¦Ã‹Å" ¾Ãƒ §Ã‚ ¤Ã‚ ºÃƒ ¥Ã…“ ¨Ãƒ ©Ã¢â‚¬ ¡?à ¥Ã‚ ºÃ‚ ¦Ãƒ ¥Ã… ½Ã¢â‚¬ ¹Ãƒ ¥Ã… †ºÃƒ §Ã… ¡Ã¢â‚¬Å¾Ãƒ ¦Ã†â€™Ã¢â‚¬ ¦Ãƒ ¥Ã¢â‚¬  µÃƒ ¤Ã‚ ¸Ã¢â‚¬ ¹Ãƒ ¯Ã‚ ¼Ã‹â€ à ¦Ã‹â€  ¿Ãƒ ¤Ã‚ »Ã‚ ·Ãƒ ¤Ã‚ ¸Ã¢â‚¬ ¹Ãƒ ¨Ã‚ ·Ã…’30à ¯Ã‚ ¼Ã¢â‚¬ ¦Ãƒ ¯Ã‚ ¼Ã¢â‚¬ °Ãƒ ¯Ã‚ ¼Ã…’à ¤Ã‚ ½?à ¦Ã‹â€  ¿Ãƒ ¦Ã…’†°Ãƒ ¦? à ¨Ã‚ ´Ã‚ ·Ãƒ ¦Ã‚ ¬Ã‚ ¾Ãƒ §Ã… ¡Ã¢â‚¬Å¾Ãƒ ¤Ã‚ ¸?à ¨Ã¢â‚¬ °Ã‚ ¯Ãƒ §Ã… ½Ã¢â‚¬ ¡Ãƒ ¤Ã‚ ¸Ã… à ¥?†¡Ãƒ ¥Ã‚ ¹Ã¢â‚¬ ¦Ãƒ ¥Ã‚ ºÃ‚ ¦Ãƒ ©?Ã… ¾Ãƒ ¥Ã‚ ¸Ã‚ ¸Ãƒ ¦Ã…“†°Ãƒ ©Ã¢â€ž ¢?à £Ã¢â€š ¬Ã¢â‚¬Å¡Ãƒ ¦Ã¢â€ž ¢Ã‚ ®Ãƒ ©Ãƒ §Ã… ¡Ã¢â‚¬Å¾Ãƒ ¥Ã‹â€ †à ¦Ã… ¾?à ¨Ã‚ ®Ã‚ ¤Ãƒ ¤Ã‚ ¸Ã‚ ºÃƒ ¯Ã‚ ¼Ã…’à ¨Ã‚ ¿Ã¢â€ž ¢Ãƒ ¤Ã‚ ¸Ã… ½Ãƒ ¤Ã‚ ¸Ã‚ à ¥Ã¢â‚¬ ºÃ‚ ½Ãƒ ¨Ã‚ ¾Ã†â€™Ãƒ ©Ã‚ «Ã‹Å"à §Ã… ¡Ã¢â‚¬Å¾Ãƒ ©Ã‚ ¦Ã¢â‚¬â€œÃƒ ¤Ã‚ »Ã‹Å"à ¦Ã‚ ¯Ã¢â‚¬ à §Ã… ½Ã¢â‚¬ ¡Ãƒ ¥Ã…’à ¤Ã‚ ¸Ã… ½Ãƒ ¨Ã‚ ¾Ã†â€™Ãƒ ¤Ã‚ ¼Ã‚ à §Ã‚ »Ã… ¸Ãƒ §Ã… ¡Ã¢â‚¬Å¾Ãƒ ¤Ã‚ ¿Ã‚ ¡Ãƒ §Ã¢â‚¬  ¨Ãƒ ¦Ã¢â‚¬â€œÃ¢â‚¬ ¡Ãƒ ¥Ã…’–à ¦Ã…“†°Ãƒ ¥Ã¢â‚¬ ¦Ã‚ ³Ãƒ £Ã¢â€ š ¬Ã¢â‚¬Å¡ Chinaà ¢Ã¢â€š ¬Ã¢â€ž ¢s housing market reform started in year 1988, but it was not until 1995 that Chinaà ¢Ã¢â€š ¬Ã¢â€ž ¢s central bank PBOC issued its first regulation in individual household loan area. This Provisional Code of Housing Loan on Commercial Banksà ¢Ã¢â€š ¬Ã¢â€ž ¢ Account set the minimum mortgage down payment ratio at 30%, the maximum term of mortgage loan at 10 years, the mortgage interest rate is a preferential rate to the benchmark of fixed assets loan. In 1999, PBOC issued A Number of Views on Encouraging the Development of Consumption Loans, in which the loan to value rate loosened to 80%, the maximum term of mortgage loan to 30 years, and the lowest preferential interest rate can be 10% discount on benchmark. In 2003, PBOC issued Notice on Further Enhance Real Estate Loan Management, in which reaffirmed the 20% minimum down payment, raise the interest rate of mortgage loan to benchmark. The Notice brings forward the new concept of à ¢Ã¢â€š ¬Ã…†œsecond set of houseà ¢Ã¢â€š ¬?, to which the bank should raise the down payment and interest rate level to the debtor. In recent years, the skyrocketing real estate prices in China bring worries on assets bubbles in public and accumulated risks to mortgage loans and real estate loan. The central bank and CBRC (China Banking Regulatory Commission) constituted and enacted several regulations to guide the mortgage business with most of the measures hooked on down payment ratio and interest rate. Generally speaking, for purchase of the first set of house, the down payment requirement is at least 20% and the interest rate are relatively flexible; for purchase of the second set of house, the down payment requirement is at least 30% and the interest rate at benchmark. The relatively loosen policy was deems as one of the important drives to boost the house price to an irrational high level now in many Chinese big cities. To curb housing market speculation, the State Council announce d in April, 2010 that: 1. The minimum down payment ratio is lifted to 30% for the first set of house purchase if the area is more than 90 square meters; 2. Second set of house buyers must pay at least 50% of the value for mortgage down payment, and the interest rate are at least 1.1 times of benchmark; 3. Higher down payment ratio and interest rates are required for à ¢Ã¢â€š ¬Ã…“three of more setà ¢Ã¢â€š ¬? of house purchase. Analyst believe the mortgage loan demand should be negatively impacted but within a limited range, and the lifted down payment ratio would provide better buffer for housing pricing decline, which would benefit loan quality. As for the banking regulations specific in the credit scoring system, it was not until 1997 CBRC released several regulatory guidelines successively along with the Basel II Accord implementation progress in Chinese banking industry. One of the most important is the Internal Rating System Regulatory Guideline, in which principle guidel ines for building internal rating system are provided for commercial banks. Being a vital part of internal rating system, credit scoring system is also regulated by these guidelines, and the main principles on credit scoring system in the guidelines are as follows: The burden is on the bank to satisfy its supervisor that a model or procedure has good predictive power and that regulatory capital requirements will not be distorted as a result of its use. The variables that are input to the model must form a reasonable set of predictors. The model must be accurate on average across the range of borrowers or facilities to which the bank is exposed and there must be no known material biases. The bank must have in place a process for vetting data inputs into a statistical prediction model which includes an assessment of the accuracy, completeness and appropriateness of the data specific to the assignment of an approved rating. The bank must demonstrate that the data used to build the model are representative of the population of the bankà ¢Ã¢â€š ¬Ã¢â€ž ¢s actual borrowers or facilities. When combining model results with human judgement, the judgement must take into account all relevant and material information not considered by the model. The bank must have written guidance describing how human judgement and model results are to be combined. The bank must have procedures for human review of model-based rating assignments. Such procedures should focus on finding and limiting errors associated with known model weaknesses and must also include credible ongoing efforts to improve the modelà ¢Ã¢â€š ¬Ã¢â€ž ¢s performance. The bank must have a regular cycle of model validation that includes monitoring of model performance and stability; review of model relationships; and testing of model outputs against outcomes. The bank should clearly know the basic assumptions of the model and assess the consistency between the assumptions and current economic or market conditions. The bank must demonstrate that economic or market conditions that underlie the data are relevant to current and foreseeable conditions. If current conditions change, the bank should ensure that the model can adapt the changed conditions. If model can not meet the request, the bank must adjust model conservatively. The above are all regulation items about credit scoring system. We can see those regulation items are mostly principle-based. The process and method of building credit scoring system are in compliance with the guideline on the whole. Although the banking regulations on credit scoring system are roughly and fundamentally, CBRC has always kept a close watch on the credit scoring model construction in the countryà ¢Ã¢â€š ¬Ã¢â€ž ¢s biggest six commercial banks including CMB. Stringent and strict on-site assessment has been carried out by CBRC throughout the whole process of date collection, model design to parameter results to ensure the appropriate a doption of the models. In June 2010, CBRC urgently request various state-owned commercial banks, joint-stock commercial banks as well as the city commercial banks with asset size over 500 billion yuan to start self-examination for real estate loans, and conduct stress testings especially in mortgage loan business. The result shows that even under highest stress scenario that the house price drop 30% from present level, the real estate related loans will maintain good quality, and the NPL (non-performing loan) ratio for mortgage loans will increase less than 1% for the whole banking industry. It is believed that the relatively high down payment ratio and the traditional credit culture in China contributed to such a released consolable result. Comparison of China/US/UK banking regulation and default risk Mortgage lending in China is safer and more stable than that in US. Conclusions
Wednesday, May 6, 2020
Essay on The Benefits of Naps - 1275 Words
What do people think of when they first hear the word nap? Everyday sayings such as snatching a nap, being caught napping, snoozing, or stealing forty winks are all beneficial daily activities we need to add to our busy life. If we do, we will be more awake and capable to reach our full potential as an individual. People don’t realize how important a nap can be. Although popular beliefs suggest that naps are a waste of time, naps actually increase productivity by resting the brain. Nap Basics In order to obtain the full benefits of the nap, there are certain â€Å"rules†that need to be followed. Following these guidelines will ensure maximum effectiveness. One condition is that naps should be taken in the early afternoon. Naps can†¦show more content†¦You will be able to accomplish more.†(qtd. by Griffey 42) An afternoon nap helped him with his many responsibilities. Leonardo da Vinci used naps so much that he didn’t need to sleep at night. Every two hours, he would take a fifteen minute nap. Many believe this contributed to his seemingly endless supply of creativity (Griffey 10). Thomas Edison would take one to two naps per day, and once turned a patron away because he was taking a nap (Griffey 73). Bill Clinton was known for taking naps whenever he could (Griffey 52). These famous figures dispel the myth that taking naps means ones lazy. They accomplished so much, yet knew their individual limitations. They gave full effort when frequent occasions required, but they also refused to run too fast. We can learn from their examples, and restore the nap to our everyday routine. The Need for Naps In today’s busy world, fatigue in the early afternoon is nearly normal. Many believe that this slump is caused by a heavy lunch. However, in reality, this occurs because we were meant to have a mid-afternoon nap (Jacobs). Those who take twenty minutes to nap when this slump occurs receive special benefits because sleep during the day is more restful than extra sleep in the morning (Scott). For everyone this can be a tough to do, especially when you have something so beneficial. Society would do well to make room for naps. When you wake up in the morning dreading the day, not wanting toShow MoreRelatedPersuasive Essay On Naps1598 Words  | 7 PagesNaps. Everyone has taken naps at some point in their life. We take them after a long day of school, a long day of work, or when we didn’t get enough sleep the night before. We take naps all the time, but do we truly know how naps affect our body? Do we truly know how we benefit from naps?    Sleep is a complicated process that many of us take for granted. Without sleep, we would die. Sleep has many benefits, but unfortunately some people with sleep disorders or people with night shift jobs are unableRead MoreDaily Napping To Keep You Happy.With Only 24 Hours In A1260 Words  | 6 Pagesthat issue. To promote physical well-being and improve mood and memory, schools and workplaces should adjusts their schedules to accommodate naps. To many adults and teenagers, naps are a gift from the heavens and a rare occurrence. Although people don’t normally take daily naps once they grow up, there aren’t many reasons not to. Napping provides many benefits, including an â€Å"increase in relaxation, reduced fatigue, reduced risks of heart disease, increased alertness, improved mood, improved performanceRead MoreSpeech On Importance Of Nap Time1520 Words  | 7 PagesOscar Bencomo Mrs. Stanton English Comp II October 8, 2014 Importance of Nap Time People tend to get drowsy throughout the day and everyone has their way of dealing with the grogginess. The best and most natural way is to simply take a nap. It is like taking a mini-vacation. People close their eyes to get away from reality and awake with energy to push them through the day. A nap is essential to keep the mind sane, it contributes to good performance, alertness, productivity, and emotional balanceRead MoreWhy People Should Nap During The School Of Montgomery College Essay1665 Words  | 7 PagesAlong with this many students nap during the day to make up for the loss of sleep. Many studies have found that napping can actually improve moods, health, and academic performance. This is shown in different studies from surveys, to testing different reactions and moods. All the way to actually providing students with a place to nap. Napping can increase academic performance, mood, and have a positive effect on health. All of these being reasons why people should nap. The main campus of MontgomeryRead MoreWork And Adopt A Natural Energy Booster, The Common Nap Essay1607 Words  | 7 Pagestake a break from their work and adopt a natural energy booster, the common nap. Workplace napping is an innovative, low-cost method that is starting to be incorporating at people’s places of work. Many people associate naps with laziness, however, businesses are evaluating the importance of naps in the workplace, as they hold various benefits such as an increase in performance, attentiveness, and overall productivity. Naps have held many stigmas over the years and are often seen as very unprofessionalRead MoreWake Up! Sleep is Necessary Essay1187 Words  | 5 Pagesfull night’s rest. This is untrue because the amount of sleep you need has a large dependence on the many factors that influence healthy energy. Age is a large indicator of how much sleep is relevant to an individual. Studies done by Milner (2008), â€Å"Benefits of napping and an extended duration of recovery sleep on alertness and immune cells after acute sleep restriction†show that an adult needs nine hours a day in order to carry out work productively, feel rejuvenated, and maintain contented moods.Read MoreSleep, Sleep Disorders, and Biological Rhythms by Charles J Amlaner1247 Words  | 5 Pagesthe short periods of sleep, called naps, that some people take during the day. Throughout history there have been many famous and important people who made naps an important part of their day including John F. Kennedy, Ronald Reagan and Winston Churchill. In some cultures the nap is traditional part of everyday life. Spain is famous for its siesta, and other countries, like Japan, are discovering the benefits of a midday sleep period. For maximum effect the nap should be about 30 minutes becauseRead MoreSleep And Its Effect On Children1342 Words  | 6 Pageseffect on their learning development. Toddlers, ages 30-36 months, were tested on solving a challenging task of an unsolvable puzzle (Miller, Seifer, Crossin Lebourgeois, 2015). The toddlers in the no nap condition were having trouble figuring out the difficult task; however, the ones who were in the nap condition used self-regulation strategies, for example, they focused on one piece at a time. Miller et al. (2015), concluded that children who miss sleep can have a risk for social, emotional, behavioralRead MoreAfter A Long Seven-Hour Day, Have You Ever Noticed A Kindergartner1014 Words  | 5 Pagesfive-year-old’s memory foll owing a nap. According to Kurdziela, Duclosb, Spencer (2013), study results demonstrated that children had better memory recall following a nap than when they had been kept awake. Therefore, the study concluded that children functioned better when they received a nap during the day. Young children between the ages of five and six benefit emotionally, cognitively, socially, and physically after brief rest periods; therefore, twenty-minute naps during kindergarten should beRead MoreThe Distribution Of Watches962 Words  | 4 Pagesreceive a reminder email and text to resume wearing the watch. Nap Session Based on the previous evening’s email participants are directed to meet after the morning practice participants in the Sleep Psychology Research Lab Napping participants (total of 6) will be directed to the Sleep Room Participants will be explained the procedure and requested to not talk. A baby monitor will be in the room so as to insure compliance. After the nap session participants will be waken and directed to return to
Tuesday, May 5, 2020
Schema Mapping free essay sample
The approaches which are used by P2P systems for defining and creating the mappings between peers’ schemas can be classified as follows: 1- Pairwise schema mapping, 2-mapping based on machine learning techniques, 3- common agreement mapping, - 4-schema mapping using information retrieval (IR) techniques. 1-Pairwise Schema Mapping: In this approach, each user defines the mapping between the local schema and the schema of any other peer that contains data that are of interest. Relying on the transitivity of the defined mappings, the system tries to extract mappings between schemas that have no defined mapping. Piazza follows this approach : An Example of Pairwise Schema Mapping in Piazza The data are shared as XML documents, and each peer has a schema that defines the terminology and the structural constraints of the peer. When a new peer (with a new schema) joins the system for the first time, it maps its schema to the schema of some other peers in the system. We will write a custom essay sample on Schema Mapping or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Each mapping definition begins with an XML template that matches some path or subtree of an instance of the target schema. Elements in the template may be annotated with query expressions that bind variables to XML nodes in the source. Active XML [Abiteboul et al. , 2002, 2008b] also relies on XML documents for data sharing. The main innovation is that XML documents are active in the sense that they can includeWeb service calls. Therefore, data and queries can be seamlessly integrated. another example that follows this approach: The Local Relational Model (LRM): LRM assumes that the peers hold relational databases, and each peer knows a set of peers with which it can exchange data and services. This set of peers is called peer’s acquaintances. Each peer must define semantic dependencies and translation rules between its data and the data shared by each of its acquaintances. The defined mappings form a semantic network, which is used for query reformulation in the P2P system. Piazza Querying Reformulation Example: Hyperion [Kementsietsidis et al. , 2003]: generalizes this approach to deal with autonomous peers that form acquaintances at run-time, using mapping tables to define value correspondences among heterogeneous databases. Peers perform local querying and update processing, and also propagate queries and updates to their acquainted peers. Table from Airline ‘A’ Table from Airline ‘B’ Mapping Tables PGrid [Aberer et al. , 2003b]: also assumes the existence of pairwise mappings between peers, initially constructed by skilled experts. Relying on the transitivity of these mappings and using a gossip algorithm, PGrid extracts new mappings that relate the schemas of the peers between which there is no predefined schema mapping. 2-Mapping based on Machine Learning Techniques: This approach is generally used when the shared data are defined based on ontologies and taxonomies as proposed for the semantic web. It uses machine learning techniques to automatically extract the mappings between the shared schemas. The extracted mappings are stored over the network, in order to be used for processing future queries. * GLUE [Doan et al. , 2003b] uses this approach as the following: Given two ontologies,for each concept in one, GLUE finds the most similar concept in the other. It gives well founded probabilistic definitions to several practical similarity measures, and uses multiple learning strategies, each of which exploits a different type of information either in the data instances or in the taxonomic structure of the ontologies. To further improve mapping accuracy, GLUE incorporates commonsense knowledge and domain constraints into the schema mapping process. * The basic idea is to provide classifiers for the concepts. To decide the similarity between two concepts A and B, the data of concept B are classified using A’s classifier and vice versa. * The amount of values that can be succ essfully classified into A and B represent the similarity between A and B. - 3- Common Agreement Mapping: In this approach, the peers that have a common interest agree on a common schema description for data sharing. The common schema is usually prepared and maintained by expert users. APPA [Akbarinia et al. , 2006a; Akbarinia and Martins, 2007] makes the assumption that peers wishing to cooperate. * e. g. , for the duration of an experiment, agree on a Common Schema Description (CSD). * Given a CSD, a peer schema can be specified using views. This is similar to the LAV approach in data integration systems, except that queries at a peer are expressed in terms of the local views, not the CSD. Another difference between this approach and LAV is that the CSD is not a global schema, i. e. , it is common to a limited set of peers with a common interest (see Figure). Common Agreement Schema Mapping in APPA * Thus, the CSD does not pose scalability challenges. When a peer decides to share data, it needs to map its local schema to the CSD. Example: * Given two CSD relation definitions r1 and r2, an example of peer mapping at peer p is: In this example, the relation r(A;B;D) that is shared by peer p is mapped to relations r1(A;B;C), r2(C;D;E) both of which are involved in the CSD. In APPA, the mappings between the CSD and each peer’s local schema are stored locally at the peer. Given a query Q on the local schema, the peer reformulates Q to a query on the CSD using locally stored mappings. AutoMed [McBrien and Poulovassilis, 2003]: is another system that relies on common agreements for schema mapping. It defines the mappings by using primitive bidirectional transformations defined in terms of a low-level data model. 4- Schema Mapping using IR Techniques: This approach extracts the schema mappings at query execution time using IR techniques by exploring the schema descriptions provided by users. PeerDB [Ooiet al. , 2003a] follows this approach for query processing in unstructured P2P networks. * For each relation that is shared by a peer, the description of the relation and its attributes is maintained at that peer. The descriptions are provided by users upon creation of relations, and serve as a kind of synonymous names of relation names and attributes. When a query is issued, a request to find out potential matches is produced and flooded to the peers that return the corresponding metadata. By matching keywords from the metadata of the relations, PeerDB is able to find relations that are potentially similar to the query relations. The relations that are found are presented to the issuer of the query who decides whether or not to proceed with the execution of the query at the remote peer that owns the relations. Edutella [Nejdl et al. , 2003] also follows this approach for schema mapping in super-peer networks. Resources in Edutella are described using the RDF metadata model, and the descriptions are stored at super-peers. When a user issues a query at a peer p, the query is sent to p’s super-peer where the stored schema descriptions are explored and the addresses of the relevant peers are returned to the user. If the super-peer does not find relevant peers, it sends the query to other super-peers such that they search relevant peers by exploring their stored schema descriptions. In order to explore stored schemas, super-peers use the RDF-QEL query language, which is based on Datalog semantics and thus compatible with all existing query languages, supporting query functionalities that extend the usual relational query languages.
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