IDEAS home Printed from https://ideas.repec.org/a/col/000443/015408.html
   My bibliography  Save this article

Actualización del modelo de riesgo crediticio, una necesidad para la banca revolvente en México

Author

Listed:
  • José Carlos Trejo García
  • Humberto Ríos Bolívar
  • Francisco Almagro Vázquez

Abstract

Con el fin de mejorar la gestión del riesgo crediticio revolvente en la estimación de provisiones en México, específicamente en carteras administrada por grandes instituciones crediticias (bancos), en esta investigación se identificó un modelo logit alternativo que refleja niveles de riesgo más precisos. Indicadores financieros de la banca como el ahorro, los activos y las utilidades mostraron rendimientos del 2,20 %, mayor al registrado por la banca mexicana. Esta situación confirma la necesidad de implementar un modelo más capaz para medir el riesgo crediticio para dichas entidades.******In order to improve the management of revolving credit risk when estimating provisions in Mexico ‒specifically in the case of portfolios administered by credit institutions (banks)‒ this research employs an alternative logit model to reflect levels of risk with greater precision than is customary. Financial indicators for the banking sector, such as savings, assets and profits showed returns 2.2 %, above the rates registered in the Mexican banking system as a whole. This confirms the need to implement a model that is capable of measuring the credit risk of these institutions.

Suggested Citation

  • José Carlos Trejo García & Humberto Ríos Bolívar & Francisco Almagro Vázquez, 2016. "Actualización del modelo de riesgo crediticio, una necesidad para la banca revolvente en México," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 8(1), pages 17-30, March.
    • Handle: RePEc:col:000443:015408
    as

    Download full text from publisher

    File URL: http://editorial.ucatolica.edu.co/ojsucatolica/revistas_ucatolica/index.php/RFYPE/article/view/925/972
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Black, Fischer & Scholes, Myron S, 1972. "The Valuation of Option Contracts and a Test of Market Efficiency," Journal of Finance, American Finance Association, vol. 27(2), pages 399-417, May.
    2. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541, September.
    3. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    4. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. José Carlos Trejo-García & Miguel Ángel Martínez-García & Francisco Venegas-Martínez, 2017. "Credit risk management at retail in Mexico: An econometric improvement in the selection of variables and changes in their characteristics," Contaduría y Administración, Accounting and Management, vol. 62(2), pages 13-14, Abril-Jun.
    2. Dinh, K. & Kleimeier, S., 2006. "Credit scoring for Vietnam's retail banking market : implementation and implications for transactional versus relationship lending," Research Memorandum 012, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    3. Rasa Kanapickiene & Renatas Spicas, 2019. "Credit Risk Assessment Model for Small and Micro-Enterprises: The Case of Lithuania," Risks, MDPI, vol. 7(2), pages 1-23, June.
    4. Richard Chamboko & Jorge M. Bravo, 2016. "On the modelling of prognosis from delinquency to normal performance on retail consumer loans," Risk Management, Palgrave Macmillan, vol. 18(4), pages 264-287, December.
    5. Dinh, Thi Huyen Thanh & Kleimeier, Stefanie, 2007. "A credit scoring model for Vietnam's retail banking market," International Review of Financial Analysis, Elsevier, vol. 16(5), pages 471-495.
    6. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    7. Doruk Şen & Cem Çağrı Dönmez & Umman Mahir Yıldırım, 2020. "A Hybrid Bi-level Metaheuristic for Credit Scoring," Information Systems Frontiers, Springer, vol. 22(5), pages 1009-1019, October.
    8. Juan Laborda & Seyong Ryoo, 2021. "Feature Selection in a Credit Scoring Model," Mathematics, MDPI, vol. 9(7), pages 1-22, March.
    9. Hussein A. Abdou & John Pointon, 2011. "Credit Scoring, Statistical Techniques And Evaluation Criteria: A Review Of The Literature," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(2-3), pages 59-88, April.
    10. Rais Ahmad Itoo & A. Selvarasu & José António Filipe, 2015. "Loan Products and Credit Scoring by Commercial Banks (India)," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 5(1), pages 851-851.
    11. Andrea Bedin & Monica Billio & Michele Costola & Loriana Pelizzon, 2019. "Credit Scoring in SME Asset-Backed Securities: An Italian Case Study," JRFM, MDPI, vol. 12(2), pages 1-28, May.
    12. Anas Yassine & Abdelmadjid Ibenrissoul & Nawal Snoussi & Zakaria Benjouid, 2017. "The macroeconomics determinants of default of the borrowers: The case of Moroccan bank [Les déterminants macroéconomiques de la défaillance des emprunteurs : Le cas d'une banque marocaine]," Working Papers hal-01683225, HAL.
    13. Anas Yassine & Abdelmadjid Ibenrissoul, 2018. "The macroeconomics determinants of default of the borrowers: The case of Moroccan bank," Papers 1801.05770, arXiv.org, revised Mar 2018.
    14. Richard Chamboko & Jorge Miguel Bravo, 2020. "A Multi-State Approach to Modelling Intermediate Events and Multiple Mortgage Loan Outcomes," Risks, MDPI, vol. 8(2), pages 1-29, June.
    15. Maria Rocha Sousa & João Gama & Elísio Brandão, 2013. "Introducing time-changing economics into credit scoring," FEP Working Papers 513, Universidade do Porto, Faculdade de Economia do Porto.
    16. Scognamiglio, Elisabetta & Di Lorenzo, Emilia & Sibillo, Marilena & Trotta, Annarita, 2019. "Social uncertainty evaluation in Social Impact Bonds: Review and framework," Research in International Business and Finance, Elsevier, vol. 47(C), pages 40-56.
    17. Neuberg Richard & Hannah Lauren, 2017. "Loan pricing under estimation risk," Statistics & Risk Modeling, De Gruyter, vol. 34(1-2), pages 69-87, June.
    18. Raffaella Calabrese & Silvia Angela Osmetti, 2011. "Generalized Extreme Value Regression for Binary Rare Events Data: an Application to Credit Defaults," Working Papers 201120, Geary Institute, University College Dublin.
    19. Yiheng Li & Weidong Chen, 2020. "A Comparative Performance Assessment of Ensemble Learning for Credit Scoring," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    20. Dalila Boughaci & Abdullah A. K. Alkhawaldeh & Jamil J. Jaber & Nawaf Hamadneh, 2021. "Classification with segmentation for credit scoring and bankruptcy prediction," Empirical Economics, Springer, vol. 61(3), pages 1281-1309, September.

    More about this item

    Keywords

    banca; crédito; modelo de estimación; rendimientos ytécnicas de optimización;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:col:000443:015408. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Universidad Católica de Colombia (email available below). General contact details of provider: https://edirc.repec.org/data/feuccco.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.