Effect of operating leverage on the relationship between liquidity management, credit risk and loan repayment among microfinance Banks, Kenya

Abstract

Globally, reports indicate that of the loans disbursed in the United States of America, 45% of borrowers default on repayment, 60% of whom eventually end up as non-performing. In India, loan repayment rates experienced rise in default by over 50% between 2017 and 2020. In Ghana, adverse loan repayment was recorded at USD 0.97B in 2015 which grew to USD1.84B by 2018. Uganda recorded about USD.1.215 billion worth of non-performing loans in its MFI sector in 2018, from USD 324 million in 2017. The Kenyan scene recorded steep rise in default from about Kshs.100M in 2015 to over Kshs. 2.7B in 2022. Leverage remains an alternative source of funding available to microfinance banks (MFBs) to plug financial deficiency brought by default-triggered liquidity shortfalls for their operational sustainability. MFBs serve low-end borrowers, prone to fall in default of honouring their loan repayment obligations. The reported adverse loan repayment trend among MFBs reflects a trajectory calling for urgent invention measures. Previous studies on loan repayment have focused on conventional banking institutions, whose operational lending dynamics are significantly distinct from those of MFB. Existing literature is focused towards investigating study parameters associated to profitability, yet its analysis is preceded by loan repayment. Operating leverage (MLG) was a plausible robust moderator since literature demonstrates it influencing the transactional environment of study parameters. Main study objective was to establish effect of operating leverage on the relationship between liquidity management, credit risk and loan repayment among MFBs in Kenya. Specifically, it sought to; analyze relationship between liquidity management (MLDM) and loan repayment (LRP); assess relationship between credit risk management (MCRK) and LRP; determine relationship between MLG and LRP; assess moderating effect of MLG on relationship between MLDM and LRP; and, investigate moderating effect of MLG on relationship between MCRK and LRP among MFBs in Kenya. The anticipated income, credit risk, liquidity preference and moral hazard theories underpinned study objectives. Secondary balanced panel data sourced from audited annual reports of 12 regulated MFBs in Kenya was used. The study covered an eight-year period from 2015 to 2022, yielding 96 data points. Moderated multiple regression was applied to realize the study objectives. Regression results showed; a unit change in liquidity management results in 2.01% significant change in loan repayment (β=0.020110, p=0.0085) with adjusted R2=79.7024%; credit risk management yields a negative and significant change in loan repayment (β=-0.009874, p=0.0260); operating leverage to loan repayment is positive and insignificant (β=-0.004192, p=0.9100) with adjusted R2 of 78.5133%; product term of MLDM and MLG yields an inverse significant relationship (β=-0.099417, p=0.0109) with adjusted R2 of 79.8886%% posting an overall computed effect size change in R2 of 1.36%, calculated to 3.481%. Results indicate MLG fully moderates the relationship between liquidity management and LRP. In conclusion, the interaction term of MLDM and MLG alters the direction of primary relationship between MLDM and LRP. The study recommends MFBs to cautiously use debt capital in their financing options. The regulations for MFBs should streamline their proclamation on acceptable liquidity controls to foster sustainability. Further studies should investigate why credit risk management posts conflicting results when implemented to overcome default.