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Elements of Credit Rating: A Hybrid Review and Future Research Agenda

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  • Prashant Ubarhande
  • Arti Chandani

Abstract

Creditworthiness is acknowledged worldwide as focal point of debt processing. Credit Rate, an output of credit-rating process, reflects such creditworthiness. We reviewed literature on elements of credit rating, viz. Credit Rate, credit-rating agencies (CRAs) and credit-rating model. Credit Rating is an independent evaluation of creditworthiness. CRAs perform this evaluation to support financial institutions in processing debts. Literature added in credit-rating domain from January 2001 to November 2020 is analyzed to explore the opportunities for further research. Bibliometric analysis is used to comprehend the existing literature. Subsequently, through structured review theories, methodologies used by researchers and CRAs are explored. Further, a hybrid literature review is developed by integrating bibliometric and structured review of research papers from widely recognized databases. A sample of 153 papers is constructed and studied to identify gaps in credit-rating domain and to develop suitable remedy to fill such gaps. We found that most of the studies emerged as after-effects of financial crisis reported in 2008 and 2016. The review revealed that 48% studies focused on development of new credit-rating mechanism without evaluating existing structure in-depth. This paper contributes to existing literature by encouraging researchers and CRAs to develop a sector-specific credit-rating system by evaluating existing models and improvising them by adopting advanced techniques like Multiple Regression, Neural Networking and Artificial Intelligence. We have provided a feasible research agenda to further explore credit-rating domain. In this study we have identified that the factors determining creditworthiness are different for different sectors.

Suggested Citation

  • Prashant Ubarhande & Arti Chandani, 2021. "Elements of Credit Rating: A Hybrid Review and Future Research Agenda," Cogent Business & Management, Taylor & Francis Journals, vol. 8(1), pages 1878977-187, January.
  • Handle: RePEc:taf:oabmxx:v:8:y:2021:i:1:p:1878977
    DOI: 10.1080/23311975.2021.1878977
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    Cited by:

    1. Davidescu Adriana AnaMaria & Agafiței Marina-Diana & Strat Vasile Alecsandru & Dima Alina Mihaela, 2024. "Mapping the Landscape: A Bibliometric Analysis of Rating Agencies in the Era of Artificial Intelligence and Machine Learning," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 18(1), pages 67-85.

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