Loan Growth, Loan Deposit Ratio and Prediction of Bank Fragility in Kenya Using Generalised Linear Model

  • Albert C. Bwire Department of Accounting and Finance, School of Business and Economics Moi University, Eldoret, Kenya
  • Joel K. Tenai Department of Accounting and Finance, School of Business and Economics Moi University, Eldoret, Kenya
  • Robert M. Odunga Department of Accounting and Finance, School of Business and Economics Moi University, Eldoret, Kenya
Keywords: Loan Portfolio Growth. Loan Deposit Ratio & Generalised Linear Model


The purpose of this study was to investigate the predictive ability of growth of loan portfolio and loan deposit ratio on bank fragility in Kenya using Generalised Linear Model. Bank systemic crisis arises when the level of non-performing loans to total assets is between 5% -10%, while bank fragility is said to arise when the level of non-performing loans to totals assets is above 10%. Bank crises have a social welfare consequence on various stakeholders and therefore there is need to find ways to minimize the negative effects. The study targeted 42 Commercial banks in operation at the end of 2015. Secondary data was collected from Central Bank of Kenya for period 2005 – 2015 for purposes of descriptive statistics; this was mainly to test the stability of study variables for a longer period. The generalised linear regression analysis was for period 2010-2014 considered close to bank distress events of 2015 and 2016. The study data was found to be non-normal and heteroscedastic the reason GLM was utilised. The credit creation and agency cost theories were used to explain the causal relationships. These theories expound on credit creation, lender behaviour and bank fragility. It has been established that most research on bank fragility have focused on Non-Performing loans, Loan loss provisions and Capital, Assets, Management, Earnings, Liquidity and sensitivity (CAMELS) indicators to detect bank instability. This study is a departure from CAMELS and tests if there are a few variables with distinctive ability to predict bank fragility. The findings of the study show, lagged dependent variable with powerful predictive ability. Besides, loan growth shows a negative significant relationship with bank fragility. Loan Deposit ratio (LDR) shows a positive significant relationship with bank fragility. This study is significant because it proves need to re-examine CAMELS indicators and identify new ratios which can predict bank fragility, distress and bank failure. Consequently, there is need for further studies to establish LDR percentage beyond which regulatory authorities should intervene in the Commercial banks’ operations. The growth of loan portfolio showed a negative significant relationship, therefore there is need to find how this variable can be modelled to timely identify fragile institutions.


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How to Cite
Bwire, A., Tenai, J., & Odunga, R. (2021, May 8). Loan Growth, Loan Deposit Ratio and Prediction of Bank Fragility in Kenya Using Generalised Linear Model. African Journal of Education,Science and Technology, 6(3), Pg 103-113. Retrieved from