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The Impact of Risk Management in Credit Rating Agencies

Author

Listed:
  • A. Seetharaman

    (SP Jain School of Global Management, 10, Hyderabad Road, Singapore 119579, Singapore)

  • Vikas Kumar Sahu

    (SP Jain School of Global Management, 10, Hyderabad Road, Singapore 119579, Singapore)

  • A. S. Saravanan

    (School of Communication, Taylors University, 57500 Petaling Jaya, Malaysia)

  • John Rudolph Raj

    (Faculty of Management, Multimedia University, 63000 Cyberjaya, Malaysia)

  • Indu Niranjan

    (SP Jain School of Global Management, 10, Hyderabad Road, Singapore 119579, Singapore)

Abstract

An empirical study was conducted to determine the impact of different types of risk on the performance management of credit rating agencies (CRAs). The different types of risks were classified as operational, market, business, financial, and credit. All these five variables were analysed to ascertain their impact on the performance of CRAs. In addition, apart from identifying the significant variables, the study focused on setting out a structured framework for future research. The five independent variables were tested statistically using structural equation modelling (SEM). The results indicated that market risk, financial risk, and credit risk have a significant impact on the performance of CRAs, whereas operational risk and business risk, though important, do not have a significant influence. This finding has a significant implication for the examination and inter-firm evaluation of CRAs.

Suggested Citation

  • A. Seetharaman & Vikas Kumar Sahu & A. S. Saravanan & John Rudolph Raj & Indu Niranjan, 2017. "The Impact of Risk Management in Credit Rating Agencies," Risks, MDPI, vol. 5(4), pages 1-16, September.
    • Handle: RePEc:gam:jrisks:v:5:y:2017:i:4:p:52-:d:112737
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    References listed on IDEAS

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    Cited by:

    1. Dominique Guegan & Peter Martey Addo & Bertrand Hassani, 2018. "Credit Risk Analysis Using Machine and Deep Learning Models," Post-Print halshs-01835164, HAL.
    2. Eka Sari Ayuningtyas & Iman Harymawan, 2022. "Risk Management Committee and Textual Risk Disclosure," Risks, MDPI, vol. 10(2), pages 1-15, February.
    3. Tamás Kristóf, 2021. "Sovereign Default Forecasting in the Era of the COVID-19 Crisis," JRFM, MDPI, vol. 14(10), pages 1-24, October.
    4. Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018. "Credit Risk Analysis Using Machine and Deep Learning Models," Risks, MDPI, vol. 6(2), pages 1-20, April.
    5. Dominique Guegan & Peter Martey Addo & Bertrand Hassani, 2018. "Credit Risk Analysis Using Machine and Deep Learning Models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01835164, HAL.

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