A Critique of the Influence of the Loan Model on Asset Quality in Zimbabwe Commercial Banks (International Journal of Business Ecosystem and Strategy (2687-2293))

Summary

• The quantitative study surveyed 406 loan department staff across 14 Zimbabwean commercial banks, achieving an 81.2% response rate from 500 distributed questionnaires.p.5
• Qualitative semi-structured interviews were conducted with 24 risk officers from both operating and defunct commercial banks in Zimbabwe.p.5
• Non-performing loan (NPL) ratios in Zimbabwe peaked at 20% in 2015, far exceeding the 5% benchmark established by Basel II.p.2
• Bank failures and closures between 2009 and 2014 led to over 1,000 bank employees losing their jobs in Zimbabwe.p.2
• Factor analysis extracted two principal components that explain a cumulative variance of 51.068 percent in loan portfolio management model effectiveness.p.7
• Extreme hyperinflation in Zimbabwe peaked at 489 billion% in 2008 following money printing to fund government operations.p.10

Key insights

1. 1. Regression analysis indicates a statistically significant positive relationship between loan model effectiveness and loan performance (β = 0.736, p = 0.000).p.11
2. 2. Comparing performing loans to the total loan book was rated as the highest indicator of model effectiveness with a mean score of 4.13.p.6
3. 3. Survey respondents identified poor markets as the single largest contributor to non-performing loans, with a mean rating of 4.12.p.8
4. 4. Effective credit risk management requires a combination of proactive screening factors and reactive post-disbursement measures.p.8
5. 5. Macroeconomic volatility, inflation, and currency dislocations severely impair the predictive capability of automated loan models.p.9
6. 6. Under the Altman Z-score model for private manufacturing firms, a score of 2.90 or above indicates creditworthiness, whereas 1.23 or lower denotes high risk.p.3