Kifiya, Ethiopia’s fintech firm has facilitated $180 million in uncollateralised digital credit for 382,000 MSMEs, with a 12% month-to-month growth rate via AI-driven credit scoring.
Working in partnership with six banks, Kifiya has enabled 717,000 loans worth $44 million, proving that data-driven lending models can scale. Beyond MSMEs, 75,000 smallholder farmers have accessed $92 million in agricultural inputs and credit, strengthening food security and rural productivity. These successes highlight the potential for AI-powered financial inclusion across emerging economies.
Small businesses are the backbone of economies across emerging markets, from Africa to Asia to Latin America, yet many struggle to access financing. Traditional lending models, which rely on collateral and formal credit histories, exclude millions of entrepreneurs, particularly women, micro-enterprises, and informal businesses. AI-powered credit scoring is transforming financial access by using alternative data sources—such as mobile transactions, business performance, and digital footprints—to assess creditworthiness, eliminating barriers that have long hindered small business growth.
At a recent workshop in Dhaka, Bangladesh, titled “AI-Powered Credit Scoring and Micro-Loans for Women-Led Small Businesses,” financial leaders, development organisations, and technology experts explored how AI-driven credit scoring can revolutionise SME financing. Hosted by institutions like the SME Foundation, The Asia Foundation, and the SheProspers project, the event featured Bangladesh Bank Governor Dr. Ahsan H. Mansur and Munir Duri, CEO of Kifiya Financial Technology, as keynote speakers. Kifiya, a leader in AI-driven lending in Ethiopia, showcased how its data-driven financial inclusion model has successfully provided credit to MSMEs without collateral, a model that could be replicated across Bangladesh, Southeast Asia, and beyond.
Bangladesh offers a strong parallel to Africa. The SME Foundation has allocated Tk450 crore through 23 banks and financial institutions, with 30% of loans directed to women entrepreneurs, proving that AI-driven lending is already reshaping financial access. Similar challenges—high collateral requirements, complex loan processes, and economic data limitations—continue to exclude entrepreneurs across Ethiopia, Kenya, Nigeria, Ghana, Rwanda, Uganda, Tanzania, Senegal, and South Africa. AI-powered credit scoring addresses these challenges by evaluating creditworthiness through machine learning and alternative data, removing the need for collateral and expanding access to financing.
Governments, financial institutions, fintech innovators, and development organisations must collaborate to build a global framework for AI-driven financial inclusion to accelerate this transformation. Policymakers must support regulatory environments that ensure responsible AI-based lending while protecting consumers. Banks and fintech companies must scale AI models to make SME financing more efficient and accessible. NGOs and development agencies are critical in financial literacy and digital adoption, ensuring that underserved communities can fully benefit. With the right partnerships, shared knowledge, and bold action, AI-powered credit scoring can unlock prosperity for millions—transforming economies, strengthening communities, and creating a more inclusive global financial system
