Industry experts who attended the AI Powered Credit Scoring and Micro Loans for Women-Led Small Businesses workshop in Dhaka, Bangladesh, believe that AI credit scoring can positively impact startup financing, especially for female-led startups.
The event, hosted by the SME Foundation, The Asian Foundation, and the SheProspers project, featured industry leaders from across Africa, Asia, and Latin America for an AI scoring analysis.
AI credit score, or artificial intelligence credit scoring, is a modern approach to assessing a borrower's creditworthiness. It provides a more sensitive and individualised credit score assessment based on an array of additional real-time factors.
Traditional credit scoring in Africa has long excluded a significant portion of the population, particularly the unbanked and those without formal employment. As of 2024, over 80 million adults in sub-Saharan Africa were still unbanked, and many individuals lacked the financial history needed for traditional credit evaluations.
This exclusion is driven by Africa’s informal, cash-based economy, limited banking infrastructure, and low financial literacy, making access to loans difficult, especially in countries like Rwanda, Uganda, South Africa, Ghana, and Nigeria.
While the conventional lending process relies on rigid criteria like mobile transaction histories, credit scores, business performance, and collateral, these processes often overlook the unique circumstances of female founders and other financially invisible groups, leading to unfair credit evaluations.
In Bangladesh, the AI scoring approach has allocated over 30% of its loans to women, helping to break gender biases in lending.
This new method removes the need for collateral and simplifies access to loan financing. It evaluates creditworthiness through its machine learning model and alternative data.
Several African countries are embracing AI-driven credit scoring to improve financial inclusion. In Ethiopia, Kifiya, an AI-powered lending service, claims the approach has facilitated over $150 million in digital credit for over 382,000 MSMEs, with a 12% month-on-month growth rate. All of which were processed without collateral.
Written by Omoruyi Edoigiawerie, a seasoned startup attorney with over a decade of experience. Learn more.
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“With over $330 billion in unmet credit demand across Africa, traditional lending models continue to exclude over 50 million MSMEs and 70% of smallholder farmers," says Munir Duri, CEO of Kifiya Financial Technology.
"AI-driven credit scoring is redefining how we assess risk, using real-time business activity instead of outdated collateral-based models. By embedding financial services into digital ecosystems, we can unlock financing at scale, enabling businesses to grow and economies to thrive.”
This Kifiya AI lending has also partnered with six banks, handled loans worth $44 million for 717,000 businesses, and provided 75,000 smallholder farmers with access to $92 million.
Industry leaders at the event also reiterated the need for partnership with banks, as most women do not have access to lands or houses to be used as collateral, which has hindered financial support for them.
While the Bangladesh Bank said it is working to make the loan processes easier with benefits to female entrepreneurs with over 30% ownership in an organisation, the issues with data security are first being addressed.
For a continent like Africa, where the startup space is mostly male-dominated, women-led startups receive only a small fraction of the funding, limiting their ability to scale and sustain their businesses.
In 2024, funding to African female startups hit a five-year low, garnering just $48 million compared to male startups, which brought in $2 billion.
“Africa’s greatest economic opportunity lies in unlocking the full potential of women entrepreneurs, yet they continue to receive less than 10% of available financing, despite running nearly 60% of informal businesses," Hayat Abdulmalik, Deputy CEO of Kifiya stated. "This isn’t just a funding gap — it’s a systemic flaw in how financial institutions assess risk and opportunity."
While government and financial institutions have been working hand in hand to create a budding startup ecosystem, this innovation establishes a support framework for financial inclusion across different countries in Africa.
Risks such as ethics, data privacy, and regulatory compliance are still left to be tackled before proper adoption; however, industry experts are certain AI lending will provide a good covering for many investment-starved startups.
