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Developing A Predictive Model for Small Business Loan Default

Author

Listed:
  • Benedict, Refiloe Gladys
  • O Stumke
  • Carstens, Veruschka Pelser

Abstract

Purpose: Governments assume responsibility for supporting SBs, including financial assistance. In South Africa, legislative measures and strategic initiatives have been established to bolster SBs, including the creation of funding agencies. These agencies intervene to enhance SB growth, job creation, poverty reduction, increased tax revenue and overall economic participation. This inherent risk results in ongoing losses and suboptimal returns on government investments, potentially wasting taxpayer funds. This paper proposes a model aimed at proactively increasing loan repayment probabilities. The study investigates SB characteristics that can pre-emptively mitigate loan repayment failures to government agencies.Design/Methodology/Approach: Employing a quantitative approach, a purposive sample of 114 SBs was analyzed using Stata, a versatile statistical software package.Findings: The findings highlight factors that may predict SBs' failure to repay loans from government agencies. These factors include risk taking, innovativeness, pro-activeness, customer relations, interpersonal relations, business planning, record keeping, financial management, market orientation, education and training, business experience and age and gender.Implications/Originality/Value: The study recommends that loan agreements should incorporate covenants that stipulate a required level of owner involvement in the business, as this serves as a demonstration of the owner's commitment.

Suggested Citation

  • Benedict, Refiloe Gladys & O Stumke & Carstens, Veruschka Pelser, 2024. "Developing A Predictive Model for Small Business Loan Default," Journal of Accounting and Finance in Emerging Economies, CSRC Publishing, Center for Sustainability Research and Consultancy Pakistan, vol. 10(4), pages 573-588, December.
  • Handle: RePEc:src:jafeec:v:10:y:2024:i:4:p:573-588
    DOI: http://doi.org/10.26710/jafee.v10i4.3351
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