Ghana's micro, small, and medium-sized enterprises (MSMEs) confront a substantial GHS 65 billion (equivalent to $4.8 billion) credit gap. This significant financing shortfall is primarily an information problem, not a lack of available capital, according to the Bank of Ghana.
The Deputy Governor, Matilda Asante-Asiedu, highlighted this during the National ICT Week's Distinguished Digital Finance Lecture. Lenders struggle to accurately assess the risk of small businesses. They often demand physical collateral, like land or buildings, instead of using readily available transaction data. This practice excludes many otherwise viable enterprises from accessing necessary funds.
This credit gap is among the most severe in Africa, despite Ghana possessing one of the continent's more capable financial systems. The country has successfully built robust digital payment infrastructure over the past fifteen years. This system reaches remote markets, farms, and lorry parks, enabling instant settlements and widespread interoperability. However, this success in payment rails has not translated into equally effective credit rails for businesses. The focus on account ownership and transaction volume, while important, does not measure the ability of businesses to grow and build with capital.
The Bank of Ghana's Deputy Governor stated that access to credit on fair terms should now be the benchmark for financial inclusion. She emphasized that open banking reforms must specifically target lending to businesses lacking conventional collateral. This regulatory shift means that failing to convert existing customer data into credit assessments is no longer just a commercial choice. It has become a supervisory concern for financial institutions.
The implications are far-reaching for Ghana's economic landscape. Collateral dependence currently constrains about 95% of MSMEs, even those with strong cash flows and contracts. Financial institutions must now re-evaluate their lending practices. They need to leverage internal transaction histories, such as cash flow, merchant activity, and income predictability, to build better credit risk models. This approach moves beyond traditional collateral-based lending, which often misinterprets legitimate seasonal cash flow variations as high risk.
Industry experts suggest several actions for financial institutions. They should immediately use their existing internal transaction data to build cash-flow early-warning capabilities. This can be done even before new open banking APIs are fully implemented. Furthermore, institutions should consider funding a 'learning tranche' of loans. This involves deliberately lending a controlled volume outside current policy, perhaps supported by development finance institutions (DFIs). This provides unbiased performance data on previously excluded segments. It should be viewed as an investment in market discovery, not a loss.
Finally, building robust monitoring systems before scaling loan volumes is crucial. Behavioural early warning systems, based on live transaction flows, can detect business deterioration much earlier. For example, a significant drop in receipts or shrinking counterparty counts signals trouble before a payment is missed. Addressing issues at this stage allows for restructuring, whereas detection at default only leaves collection options. This comprehensive approach is vital for closing Ghana's substantial MSME credit gap and fostering broader economic growth.