ANALYSIS OF CREDIT APPRAISAL TECHNIQUES IN CORPORATE BANKING

Authors

  • Hamilpur Deepthika1 , Bollu Laharika2 , Kashi Nagesh3 , Asadhi Nikitha Rani4 , Ms. R. Swapna5 Author

DOI:

https://doi.org/10.64751/s1wph911

Keywords:

Credit appraisal, corporate banking, DSCR, credit risk rating, collateral valuation, financial ratio analysis, NPA, Basel III, loan sanctioning, banking sector India.

Abstract

Credit appraisal in corporate banking constitutes the systematic evaluation of a borrowing entity's financial health, repayment capacity, management quality, and collateral adequacy before the extension of credit facilities. Unlike retail lending, corporate credit appraisal demands a multi-dimensional assessment encompassing quantitative financial analysis, qualitative risk evaluation, industry dynamics, and regulatory compliance. This study analyses the credit appraisal techniques employed in corporate banking, examining frameworks such as the 5-C model, financial ratio benchmarking, Debt Service Coverage Ratio (DSCR) analysis, credit risk rating, and post-sanction monitoring. Primary data was gathered through structured interactions with corporate banking professionals across leading Indian banks. Secondary data was sourced from RBI master circulars, Basel Committee guidelines, published annual reports, and academic literature spanning 2018–2024. Findings establish DSCR, Interest Coverage Ratio (ICR), and collateral quality as primary determinants of corporate credit decisions. Average loan appraisal turnaround time of 24.3 days and an overall approval rate of 76.7% across 60 sampled corporate loan cases were recorded. The study identifies key challenges including information asymmetry, valuation subjectivity, and regulatory compliance burden, and recommends adoption of AIdriven credit underwriting models, real-time financial monitoring, and standardized sector-specific appraisal templates.

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Published

2026-05-02

How to Cite

ANALYSIS OF CREDIT APPRAISAL TECHNIQUES IN CORPORATE BANKING. (2026). International Journal of AI Electronics and Nexus Energy, 2(2), 625-634. https://doi.org/10.64751/s1wph911

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