An Innovative Framework for Building Agency-Free Credit Rating Systems

Chang, C. H.; Liou, Wei-Chen; Hsu, William W. Y.; Shih, Jen-Ying; Wu, Chung-Su; Ho, Jan-Ming

doi:10.1109/soca.2017.32

Cited by 1 publication

(2 citation statements)

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“…To raise the confidence of these users, CRAs must focus on development of an effective mechanism for identifying potential factors responsible for arising conflicts of interest (Rebryk et al, 2017). (Chang et al, 2017) challenged the contribution of CRAs by developing a credit-rating model that can rate firm without involving CRAs. The said model used generic indices, area under curve (AUC) of receiver operating characteristics (ROC) and log loss.…”

Section: Common Factors Considered By Crasmentioning

confidence: 99%

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

Ubarhande

Chandani

2021

Cogent Business & Management

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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 ABOUT THE AUTHOR Prashant Ubarhande, MBA (Finance) is a research scholar in faculty of Management at

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Section: Common Factors Considered By Crasmentioning

confidence: 99%

“…Weighted Averages (Shi et al, 2019), (Shi et al, 2016) Loss Given Default (Tounsi et al, 2018), (Chang et al, 2017) Area Under the Curve…”

Section: Key Authorsmentioning

confidence: 99%