Report on Microbusiness Financing and its Impact on Sustainable Development Goals

Introduction: The Role of Microenterprises in Sustainable Development

Microbusinesses, defined as firms with fewer than ten employees, are essential for achieving several Sustainable Development Goals (SDGs). Their growth is intrinsically linked to local economic vitality, innovation, and community resilience. However, a significant barrier to their scaling is the lack of access to financial services, a challenge that directly impedes progress on global development targets.

• SDG 8 (Decent Work and Economic Growth): Microbusinesses are critical engines for job creation and local economic activity.
• SDG 9 (Industry, Innovation, and Infrastructure): These enterprises are hubs of innovation, but require robust financial infrastructure to thrive.
• SDG 10 (Reduced Inequalities): Ensuring equitable access to finance for the smallest firms is crucial for reducing economic disparities.

The Core Challenge: Data Deficiencies Hindering SDG 8

A report by PYMNTS Intelligence and Markaaz, “Keeping Score: Why Data Quality Determines Lending Decisions for the Smallest Firms,” identifies a systemic crisis in data quality as the primary reason microbusinesses are denied credit. This is not an issue of credit risk but of data verifiability, which stifles economic growth and job creation.

1. Nearly 30% of microbusiness loan applications in the U.S. and U.K. are rejected due to unverifiable legitimacy.
2. This rejection rate is five times higher than that for larger businesses.
3. This financial exclusion directly undermines the objectives of SDG 8 by stunting the growth of enterprises that provide decent work and fuel local economies.

Systemic Barriers and their Impact on SDG 9 and SDG 10

The inability of financial institutions to assess microbusinesses effectively creates a significant inequality, sidelining the smallest economic players and hampering innovation.

Key Findings on Systemic Gaps:

• Institutional Aspiration vs. Capability: While 60% of U.S. banks desire real-time business data to approve more loans, only 30% possess comprehensive assessment capabilities for microbusinesses. This disconnect represents a failure in financial infrastructure, impacting SDG 9.
• The “Unknowable” Applicant: Microbusinesses are often rejected for being “unknowable” rather than “risky.” They typically lack audited financials and have fragmented credit histories, making them invisible to traditional underwriting models. This creates an unequal playing field, contrary to the principles of SDG 10.
• Perception of Profitability: Only 22% of large U.S. banks and 25% of credit unions view lending to microbusinesses as profitable. This contrasts sharply with the 84% of banks that find lending to data-rich small businesses highly profitable, highlighting a clear financial penalty for informational opacity.

The Critical Role of Verifiable Data

Lender confidence is directly proportional to the quality and verifiability of data. This disparity in data access and trust perpetuates the exclusion of microenterprises.

• Confidence in underwriting soars to 96% with data from a credit bureau and 94% with audited financials.
• Confidence drops to 82% when reviewing self-reported bank statements.
• The U.K.’s centralized Companies House registry provides a standardized data framework, leading to nearly half of U.K. banks prioritizing audited financials. In the fragmented U.S. system, only one-third of banks do so.

Pathways Forward: Aligning Solutions with SDG 9 and SDG 17

Addressing the microbusiness lending gap requires an innovative data strategy that supports sustainable and inclusive economic development. This aligns with SDG 9’s call for resilient infrastructure and SDG 17’s emphasis on partnerships for the goals.

Recommendations for a New Data Infrastructure:

1. Develop Scalable Verification Tools: Financial institutions need low-cost, scalable methods to verify business fundamentals like ownership, revenue, and payment history.
2. Leverage Technology and Partnerships: Platforms that aggregate and refresh global business records in real-time, such as Markaaz, offer a promising solution. Such public-private and technology-driven partnerships are essential for achieving the SDGs.
3. Build a U.S. Data Framework: The absence of a U.S. equivalent to the U.K.’s Companies House must be addressed to create a more equitable and efficient lending environment, fostering the innovation and growth central to the 2030 Agenda for Sustainable Development.

SDGs Addressed in the Article

• SDG 8: Decent Work and Economic Growth
• SDG 9: Industry, Innovation, and Infrastructure
• SDG 10: Reduced Inequalities

Specific SDG Targets Identified

1. SDG 8: Decent Work and Economic Growth

   • Target 8.3: Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity and innovation, and encourage the formalization and growth of micro-, small- and medium-sized enterprises, including through access to financial services.
   • Explanation: The article directly addresses this target by focusing on how microbusinesses (firms with fewer than 10 employees) are denied “access to the financial fuel they need to scale.” This lack of access to financial services (loans) stifles their growth, ability to create jobs, and innovate, which are core components of Target 8.3. The article states this problem is “stunting job creation and starving the early-stage firms that drive America’s entrepreneurial engine.”

2. SDG 9: Industry, Innovation, and Infrastructure

   • Target 9.3: Increase the access of small-scale industrial and other enterprises… to financial services, including affordable credit, and their integration into value chains and markets.
   • Explanation: The central theme of the article is the struggle of small enterprises to access credit. It highlights that “nearly 3 in 10 microbusiness loan applications… are rejected.” The article also discusses the need for a better “data infrastructure” to solve this problem, mentioning the lack of a U.S. equivalent to the U.K.’s Companies House, which centralizes business filings and improves data quality for lenders.

3. SDG 10: Reduced Inequalities

   • Target 10.2: By 2030, empower and promote the social, economic and political inclusion of all… irrespective of… economic or other status.
   • Explanation: The article highlights a significant economic inequality between microbusinesses and larger businesses in accessing financial services. It explicitly states that the loan rejection rate for microbusinesses is “five times the rejection rate of larger businesses.” This disparity demonstrates an economic exclusion of the smallest firms from the financial system, which Target 10.2 aims to eliminate.

Implied Indicators for Measuring Progress

1. For SDG Target 8.3

   • Indicator: Percentage of microbusiness loan applications rejected due to data issues.
   • Evidence from the article: The article provides a direct metric: “nearly 3 in 10 microbusiness loan applications in the U.S. and the United Kingdom are rejected not due to credit risk, but due to unverifiable legitimacy.” A decrease in this percentage would indicate progress.
   • Indicator: Percentage of financial institutions that find lending to microbusinesses profitable.
   • Evidence from the article: The text states that only “22% of large U.S. banks and 25% of credit unions consider lending to microbusinesses profitable.” An increase in this figure would show improved financial inclusion and viability for this sector.

2. For SDG Target 9.3

   • Indicator: Percentage of financial institutions with comprehensive data assessment capabilities for microbusinesses.
   • Evidence from the article: The article mentions that “only 30% of institutions reported having truly comprehensive assessment capabilities for microbusinesses.” This indicator measures the technological and infrastructural gap that prevents access to credit.
   • Indicator: Lender confidence levels based on the quality of financial data.
   • Evidence from the article: The article quantifies this by stating confidence “soared to 96% when debt repayment histories came from a credit bureau… That confidence dropped to 82% when reviewing self-reported bank account statements.” This demonstrates how data infrastructure directly impacts lending decisions.

3. For SDG Target 10.2

   • Indicator: Ratio of loan application rejection rates between microbusinesses and larger businesses.
   • Evidence from the article: The article provides a clear indicator of inequality by stating the rejection rate for microbusinesses is “five times the rejection rate of larger businesses.” Reducing this ratio would signify a reduction in inequality.

Summary of SDGs, Targets, and Indicators

Source: pymnts.com