2023-06-03-ADB-Sustainable_Financing_Strategies_for_SMEs_Two_Alternative_Models_21页_514kb

Summary of "Sustainable Financing Strategies for SMEs: Two Alternative Models"

Core Content

This working paper by Monzur Hossain, Naoyuki Yoshino, and Kenmei Tsubota proposes two alternative sustainable financing strategies for Small and Medium Enterprises (SMEs) in developing countries, with a focus on Bangladesh. The paper aims to address the common challenges SMEs face in accessing formal finance, including high interest rates, stringent collateral requirements, and information asymmetry between banks and SMEs. It evaluates the effectiveness of the "Credit Wholesale Program" (CW program) initiated by the SME Foundation (SMEF) in Bangladesh and suggests a blended model incorporating digital finance and agency-based information.

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Main Viewpoints

1. Problem Statement

• Access to formal finance is a major bottleneck for SME development in developing countries.
• High interest rates and collateral requirements increase the cost of borrowing for SMEs.
• Banks are hesitant to lend to SMEs due to high default risks and information asymmetry.
• Informal financing sources are costly and often insufficient to meet SMEs' needs.

2. Proposed Models

• Model 1: Institutional Mechanism with Subsidized Funding

  • A government agency (like SMEF) provides subsidized loanable funds and training to SMEs.
  • This reduces banks' fund constraints and default risks by improving the creditworthiness of SMEs.
  • Banks can then offer lower-interest, collateral-free loans to SMEs.
  • However, this model may suffer from moral hazard and selection bias, as the government's limited funds may not cover all SMEs, and there could be political interference in the selection process.

• Model 2: Blended Digital Finance with Agency Information

  • A government agency provides credit information and credit scores to banks through big data analytics.
  • Banks use this information to disburse loans via digital platforms, reducing transaction costs and default risks.
  • This model is expected to have better coverage and lower transaction costs, thus improving the sustainability of SME financing.

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Key Information

Empirical Evaluation of the CW Program

• The CW program was initiated in 2009 by the SME Foundation in Bangladesh.
• It provides subsidized loanable funds to partner financial institutions (PFIs) at a 4–5% interest rate.
• The program restricts itself to 177 SME clusters and selects beneficiaries based on training and group-based lending.
• The repayment rate of the CW program is over 95%, indicating its success compared to regular SME credit programs.
• However, the coverage is limited due to the fund constraints of SMEF.
• The program has disbursed Tk2,271.5 million to 5,000 SMEs, mostly female entrepreneurs, over the years.

Empirical Findings

• The CW program meets only 51% of SMEs' financing needs and contributes 26% to the total loan portfolio and 36% to other loans in 2016.
• Banks offer lower interest rates (9%) to CW beneficiaries compared to other sources (e.g., commercial banks at 10.81% and NGOs at 15.25%).
• CW beneficiaries receive more credit from banks than non-beneficiaries.
• The financing gap is reduced for firms accessing the CW program compared to those relying on commercial banks or personal sources.

Theoretical Insights

• The paper develops a theoretical model that integrates the government, banks, and SMEs.
• The government's objective function includes loan supply and nonperforming loan ratios.
• The loan demand function is influenced by the interest rate, expected output, and borrower information.
• Digital finance is expected to reduce transaction costs and default risks, thereby increasing loan supply and SME performance.

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Conclusion

• The CW program has shown positive spillover effects on SME performance and access to finance.
• However, its limited coverage and potential for moral hazard suggest the need for a more sustainable model.
• The blended model of digital finance with agency information is proposed as a more scalable and sustainable alternative.
• The model aims to improve loan performance and reduce default risks by leveraging big data analytics and digital platforms.
• The paper argues that this blended model can produce better results than the traditional subsidized fund model due to its wider coverage and lower transaction costs.

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Keywords and Classification

• Keywords: SME financing models, credit wholesale program, default risk, digital finance, Bangladesh
• JEL Classification: O16, L25