This report focuses on examining small and medium-sized enterprises (SMEs) finance indicators collected by development finance institutions (DFIs). Specifically, the report assesses the scope of data, identifies opportunities and recommendations for improved coordination and data sharing, and highlights relevant gender-disaggregated data to address the SME finance gap.

Macro-level results and analysis

The report identifies significant disparities in the breadth and scope of collected data as well as in the methods of collection and framework definitions of SMEs. The analysis reveals that only half of the twelve databases sampled are collecting the core indicators assessed in this exercise. Additionally, the report demonstrates that SME finance data in emerging markets is limited and that gender-disaggregated data is often absent. While there are resource commitments to attain data quality, still, macro-level performance data is not consistently available from the less developed and fragile markets.

Micro-level results and analysis

At the micro-level, the report shows that there are 17 institutions collecting SME finance data, and the agencies primarily focus on their own portfolios and directly collect data from client or partner FIs. The micro-level data sets are better at capturing MSME finance indicators, especially loan data, with some efforts at data disaggregation. However, the report underlines huge disparities in breadth and scope of indicators, methods of collection and modularities of definitions of SMEs. Only two gender-specific indicators are being collected, and six unite the potential for extrapolation.

Recommendations

The report provides the following recommendations to improve SME finance data collection and coordination:

• The development of a harmonised framework over the long term to help sustain the collection and use of quality data about the SME loan portfolios of partner financial institutions.
• The introduction of a pilot program for data coordination to jumpstart standardisation efforts.
• The harmonisation of data collection across agencies to ensure greater accuracy and efficiency.
• A total commitment to data disaggregation by IFIs and DFIs to enable better aggregation and more comprehensive reporting.
• A focus on developing reliable gender-disaggregated data to aid in identifying inclusion gaps and allow for monitoring and measuring alternative options to closing these gaps.

Conclusion

The report highlights the key role of SMEs in driving economic growth and underlines that access to finance remains a significant barrier to their survival, growth and productivity. The report identifies significant limitations of existing SME finance data collection and recording regimes and puts forward several recommendations to address the coordination and quality of SME finance data quality to close SME finance gap. Ultimately, harmonising data collection is crucial to identify gaps, designing necessary interventions to close them and monitoring progress.