دانلود مقاله ISI انگلیسی شماره 25288
عنوان فارسی مقاله

توسعه یک مدل تخصیص حد اعتباری برای بانک ها با استفاده از TOPSIS فازی یکپارچه و برنامه ریزی خطی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
25288 2012 7 صفحه PDF سفارش دهید 5330 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Development of a credit limit allocation model for banks using an integrated Fuzzy TOPSIS and linear programming
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 39, Issue 5, April 2012, Pages 5309–5316

کلمات کلیدی
غلظت ریسک اعتباری - تخصیص حد اعتبار - فازی - برنامه ریزی خطی -
پیش نمایش مقاله
پیش نمایش مقاله توسعه یک مدل تخصیص حد اعتباری برای بانک ها با استفاده از TOPSIS فازی یکپارچه و برنامه ریزی خطی

چکیده انگلیسی

In this study, a credit risk concentration allocation model is developed for the banks to determine the credit risk concentration limits of their regional head’s. The proposed model is based on the Fuzzy TOPSIS (FTOPSIS) and Linear Programming (LP) approaches. FTOPSIS is easy to use and capable to keep tract of decision made in reaching the overall score by combining different types of criteria. LP combines the results of FTOPSIS and other constraints and objectives determined by the bank. Using FTOPSIS and LP together in the same model brings uniformity and a structure in credit risk concentration decisions of the banks. The developed model is tested with a real case banking application and satisfactory results are obtained. An application is also provided in the paper for illustrative purposes.

مقدمه انگلیسی

The major causes of serious banking problems in the world are directly related to poor portfolio risk management, or to a lack of attention to changes in economical and regional conditions. These circumstances can lead to deterioration in the credit portfolios of the banks. Therefore banks need to manage the credit risk instrument in their portfolio. As exposure to credit risk continues to be the leading source of problems, banks need to identify, measure, manage and control credit risk as well as to determine the level of adequate capital against credit. A bank’s portfolio contains different types of customer-related concentrations such as particular economic sector, geographic region, type of credit facility and type of collateral. These concentration types should take into consideration potential changes in the credit portfolio (Risk Management Group of the Basel Committee on Banking Supervision, 2000). Credit risk concentration is one of the most special topics in finance. Concentrations are probably the single important cause of major credit problems (Uberti & Figini, 2010). Credit concentrations are viewed as any exposure where the potential losses are large relative to the bank’s capital and its total assets. Various systematic factors affecting portfolio losses are namely economical, regional or industrial. Therefore credit concentration limits should also be established for particular industries, economic sectors and regions (Risk Management Group of the Basel Committee on Banking Supervision, 2000). In this study, a regional credit concentration limit allocation model is developed for the banks. The proposed model is used to determine the credit concentration limits of a bank’s regional heads. The paper is organized as follows: In Section 2, a literature survey is presented. In Section 3, steps of the model are shown. In Section 4, a real case study application is illustrated. In Sections 5 and 6, the discussions and conclusions are presented.

نتیجه گیری انگلیسی

In this paper, a credit risk concentration allocation model is developed. As a practical tool for the banks in their credit risk management process. An example is also provided in the paper to illustrate a practical application of the developed model. A key issue in the model is that the success of the selection procedure is sensitive to the weights of the criteria. The weights are only subjectively evaluated, and hence their accuracies always depend on the users’ knowledge and familiarity with the economic environment of the country and banking industry (see Yurdakul, 2004 and Yurdakul and İç, 2004). The tests revealed that the model is a reliable and useful tool in the evaluation of regional head’s credit concentration limits. However additional tests are needed for a more sound justification of its practical significance. In addition, it should be noted that such a model requires continuous updating and improvement. The financial and other data have to be updated regularly to ensure correct scores and results. The ratios, threshold values or constraints, rules and other parts of the model can also be changed according to the specific needs of the banks. The advantages of this method in determining the credit concentration limits are: (1) Banking strategies can be reflected in credit risk management activities. (2) Real data are used, the calculation is simplified and the consistency of the system is improved. (3) The weights of criteria and the ranks of regional heads are both determined by the same systematic approach. (4) The FTOPSIS approach is simple and easy to implement.

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