Abstract
Financial institutions want to draw upon a pool of borrowers having a high capacity of making repayments to ensure a smooth lending process. Before lending, financial institutions can assess their prospective customers using various tools such as customer interviews, visits, ratings from external credit rating agencies, financial analysis, and internal ratings along with risk mitigation through securities and collateral, as guided by the regulators and Basel committee. Basel accord suggests an internal rating-based approach where banks are allowed to estimate the borrower’s probability of default, internally. Multivariate statistical approaches such as logistic models is widely used for finding the probability of default models by banks. The current study covers the development of probability of default model after using financial ratios as predictors. Results reveal that financial ratios have a significant impact on the firm’s probability of default, except cash flow ratios. Fitted probability of default model can be utilized in any corporate lending firm for the assessment of its strength and its ability to pay back the loan. Probability of default model meets the State Bank of Pakistan (SBP) and Basel requirements for the implementation of internal rating based approaches in the case of conventional Pakistani banks. Credit risk rating and expected credit losses can be calculated using fitted probability of default model. This study was executed only based on financial ratios because of the availability of financial data only. Conventional banks use managerial, business and economic factors along with financial ratios to construct better predictive models. The current study was conducted on limited data adopted from financial statements analysis published by SBP. The developed model in this study is suitable for all non-financial corporates. Future researchers may develop different models for different industries, for instance, manufacturing and trading.Keywords: financial ratios, default, Basel, internal rating
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