طراحی مدل ریاضی سنجش ریسک اعتباری بوسیله رتبه‌‌‌بندی اعتباری با بهره‌برداری از مدل تحلیل پوششی داده‌‌‌ها

الموضوعات :

فرید حیدری فر ¹ , فرهاد حنیفی ² , غلامرضا زمردیان ³

1 - گروه مالی، دانشکده مدیریت، دانشگاه آزاد واحد تهران مرکزی، تهران، ایران
2 - گروه مالی، دانشکده مدیریت، دانشگاه آزاد اسلامی واحد تهران مرکزی، تهران، ایران
3 - گروه مالی، دانشکده مدیریت، دانشگاه آزاد واحد تهران مرکزی، تهران، ایران

تاريخ الإرسال : 18 الثلاثاء , رجب, 1442 تاريخ التأكيد : 15 الجمعة , ذو القعدة, 1442 تاريخ الإصدار : 28 السبت , جمادى الثانية, 1444

الکلمات المفتاحية: شاخص‌های ریسک اعتباری, تحلیل پوششی داده‌ها, صنعت بانکداری, رتبه‌بندی اعتباری,

ملخص المقالة :

نظام بانکی کارآمد، موثرترین وسیله برای توسعه اقتصادی بوده و مهم‌ترین وظیفه بانک‌ها تخصیص منابع در قالب تسهیلات بانکی است و طراحی و استقرار مدل رتبه‌بندی اعتباری نقش موثری در افزایش کارآمدی بانک‌ها در تجهیز منابع دارد. در پژوهش حاضر به طراحی و تبیین مدل رتبه‌‌‌بندی اعتباری با بهره‌برداری از مدل تحلیل پوششی داده‌‌‌ها، پرداخته شد. نمونه آماری مربوط به اطلاعات مشتریان حقوقی پذیرفته شده در بورس اوراق بهادار و دریافت کننده تسهیلات از بانک تجارت در طی سال‌های 1398 تا1399؛ بیان نمود. در این زمینه، 30 متغیرتوضیح دهنده شامل متغیرهای مالی و غیر مالی مورد بررسی قرار گرفت. از بین متغیرهای موجود نهایتاً با استفاده از تکنیک تجزیه و تحلیل عاملی و روش دلفی متغیرهای تأثیرگذار بر ریسک اعتباری انتخاب و وارد مدل تحلیل پوششی داده‌ها شده است و امتیازات کارایی شرکت‌های حقوقی با استفاده از آن‌ها به دست آمد. نتایج حاصل از مقایسه‌ی دو مدل تحلیل پوششی داده‌ها حاکی ازآن است که اعتبار مدل مالی 072/0 ازمدل ترکیبی بیشتر است. در رویکرد مالی 7 شرکت کارا بوده و در رویکرد ترکیبی 12 شرکت کارا تشخیص داده شد.

المصادر:

1. H Lotfi, M Navabakhs, A Tehranian, M Rostamy-Malkhalifeh, ... Ranking bank branches with interval data—the application of DEA International Mathematical Forum 2 (9), 429-440, 2007


2. A Barzegarinegad, G Jahanshahloo, M Rostamy-Malkhalifeh, A full ranking for decision making units using ideal and anti-ideal points in DEA, The Scientific World Journal 2014, 2014


3. S Razipour-GhalehJough, FH Lotfi, G Jahanshahloo, ..., Finding closest target for bank branches in the presence of weight restrictions using data envelopment analysis, Annals of Operations Research, 1-33, 2019


4. Saadi, Ali. 1397. Risk and Capital Management. Published by: Arad. Year of publication: 1397


5. Rajabzadeh Moghani, Nahid. 1396. Study of effective factors on credit risk of bank customers using survival analysis method (Case study of housing bank). Research. Government - Ministry of Science, Research, and Technology - Ferdowsi University of Mashhad - Faculty of Economics. 1396. PhD. Supervisor: Ahmad Seifi. Mohammad Reza Lotfalipour Consulting Professor: Mostafa Razmkhah.


6. R,1392, Presenting a Model for Predicting Bank Behavior Portfolio Behavior Using Discrete Markov Chain Model (Case Study: National Bank of Shahroud Branches). Research. Government - Ministry of Science, Research, and Technology - Semnan University - Faculty of Economics. 1392. Master's degree. Supervisor: Kazem Ebrahimi Advisor: Tahereh Heydari.


7. Parsaiyan, Ali (1378)” Risk Management. Dimensions of risk management, its definition and application in financial organizations ", Financial Research, Fourth Year, No. 13 and 1, pp. 125-144


8. Rai, Reza; Pouyanfar, Ahmad (1392). Advanced investment management. Tehran: Organization for the Study and Compilation of University Humanities Books (Position)


9. Fallah Shams, Mirfeiz, 2010. Credit risk management book in financial institutions and banks. Publisher: University of Economics


10. Hall, John. 2005. Fundamentals of Financial Engineering and Risk Management. Useful brokerage. Stock Publications.


11. Hu, Xiaolu, et al. 2019. Information asymmetry and credit rating: A quasi-natural experiment from China. Journal of Banking & Finance, Volume 106, September 2019, Pages 132-152.


12. Lv, Dayong & Wenfeng Wu. 2019. Margin-trading volatility and stock price crash risk. Pacific-Basin Finance Journal, Volume 56, September 2019, Pages 179-196.


13. Karimi, Elham and Shahrooz Bamdad, 1397, Presenting an Approach to Credit Ranking of Bank Customers Using the Data Mining Technique of Self-Organization Ten, Fourth International Conference on Industrial and Systems Engineering, Mashhad, Ferdowsi University of Mashhad.


14. Du, Wenti. 2018. Who carried more credibility?: An analysis of the market responses to news from the Japanese government, the Japanese central bank and international credit rating agencies. Journal of Economics and Business, Volume 98, July–August 2018, Pages 32-39


15. Turkan, Saeed, 2016, Presenting a Model for Predicting Bank Loan Portfolio Behavior Using Discrete Markov Chain Model, Fifth International Conference on Accounting and Management, and Second Conference on Open Entrepreneurship and Innovation, Tehran, Hamaghgaran


16. Mousavi, Seyed Behzad et al., Presenting a Model for Predicting Bank Loan Portfolios Using Discrete Markov Chain, First National Conference on Monetary and Banking Management Development, Bahman 92.


17. Basel committee on banking supervision (2000) Credit rating and complementary sources of credit quality information, working paper,N 3.


18. Auditing Organization, 1997


19. Kiss France (2003) Credit scoring process from a knowledge management prospective ,Budapest university of technology and economics , P:96-97.


20. Gholizadeh, Mohammad Hassan(2004) Designing the ranking model of companies in tehran stock exchange using data envelopment analysis,PhD thesis, faculty of Management ,Tehran University


21. Altman E et al (1968) «Financial rations discriminate analysis and the prediction of corporate bankruptcy», the Journal of Finance; 4:589-609.


22. Emel AB et al (2003) «A credit scoring approach for the commercial banking sector», Journal of Socio-Economic Planning Sciences37:103-123.


23. Min JH and Lee YC( 2007)«A practical approach to credit scoring», Journal of Expert systems with applications; doi:10.1016/j.eswa .2007.08.070.


24. Rostamian, Forough, Haji Babaei, Fatemeh. ,Measure the bank's liquidity risk using Value at risk model, Case study: Bank Financial accounting research and Audit. Article 1, Volume 0, Number 9, Page - .024 033


25. Fallah Shamsi, Mirfeiz(2004) Designing the credit risk model in the Iran's banking system, PhD thesis, faculty of Management ,Tehran University


26. Pedersen, Michael, 2018, Credit risk & monetary pass-through—Evidence from Chile, Journal of Financial Stability, Volume 36, June 2018, Pages 144-158.


27. Faghih, Mostafa(2004) Designing the credit ranking model of legal customer in the commercial bank, MS thesis, faculty of Management,Imam Sadegh Univercity


28. KIM J AN(1999) Application of factor analysis in social research with spss software commands,Tehran:Salman Publication


29. Mashayekhi,Alinaghi et al (2005)«Analysis of the key factors affecting the application of information technology in government organizations in Iran: Application of Delphi Metho» the Journal of Modarress;4:14-29


30. Mehregan,MohammadReza(2004) Quantitative models in performance assesment of organizations, Publication of faculty of Management of Tehran University


31. Ruintan ,Pooneh(2006) The study of effective factors on credit risk of banking client(case study:Keshavarzi Bank of Iran), MS thesis faculty of Economics and Political Science ,Shahid Beheshti University


32. Cheng EWL,Chaing YH,Tang BS (2007) «Alternative approach to the credit scoring by DEA :evaluating borrowers with respect to PFI project» , Journal of Building and Environment ;42:1752-1760.


33. Amini, Amir and Ali Nejad, Alireza, March 2017, Presenting a Combined Model of Two-Step Data Envelopment Analysis in Gray Environment for Performance Evaluation, Journal of New Mathematical Research, Islamic Azad University, Science and Research Branch, http: //jnrm.srbiau .ac.ir


34. Salehi, Fahima; Mojtaba Salehi and Meysam Jafari Eskandari, 2014, Optimization of the portfolio of facilities granted by financial institutions using mathematical planning and genetic algorithm (Case study of Tejarat Bank), Monetary and Banking Management Development Quarterly 2 (3)


35. Azazi, Reza. 2013. Dynamic Multi-Objective Model of Fuzzy Data Envelopment Analysis. Research. Government - Ministry of Science, Research, and Technology - Shahid Madani University of Azerbaijan - Faculty of Basic Sciences. 1392. Master's degree. Supervisor: Jafar Pourmahmoud | Consultant Professor: Alireza Ghaffari Hadigheh


36. Mohtashami, Toktam and Salami, Habibollah(2006) Factors discriminating low risk and high risk corporate credit applicants: the case of Keshavarzi bank, MS thesis ,faculty of economics and agricultural development,Tehran University.


37. Jahanshahloo, Gholamreza et al. 2011. Data Envelopment Analysis and Its Applications. Publisher: Nafis Works. Printing turn: 1


38. Hosseinzadeh Lotfi, Farhad, 2011. Introduction to GAMS and DEA modeling program. Islamic Azad University - Science and Research Branch, published in 201


39. Tahari, Mohammad Hossein, Farid, Daryoush, Babaei, Hamid, Summer 2011, Presenting a Combined Model of Data Envelopment Analysis and Ideal Planning to Improve the Measurement of Efficiency of Decision Units, Quarterly Journal of Industrial Management Studies, Pages 8, 21-37


40. Mirghfouri, Seyed Habibollah, Shafiee Rudpashti, Meysam, Nadafi, Ghazaleh, Summer 2011, Comparison and ranking of financial performance of provincial telecommunication companies with the collective model approach of data envelopment analysis and cross-efficiency method, Journal of Management and Development Process


41. Sedighi Hassan Kiadeh, Majid; Saati, Saber; Kordrostami, Sohrab, March 2017, Determining the size of Russell's technical efficiency with the presence of flexible textual indices on auxiliary variables, Journal of New Mathematical Research, Azad University, Science and Research Branch, http://jnrm.srbiau.ac