Access to credit has evolved significantly over the last decade.

East Africa has been at the forefront of this evolution, setting the standard globally of how digital credit should work, especially with the goal of bringing traditionally excluded and underbanked populations.

Taking the example of Kenya, the home of mobile money and digital credit, an estimated 80 per cent of Kenyans have interacted with digital credit to date, making this one of the most advanced fintech markets globally. Looking beyond Kenya, according to the World Bank, about 1.2 billion adults remain unbanked and financially underserved.

Digital credit presents an opportunity to bridge this financial gap by leveraging smartphone and internet penetration as well as the adoption of mobile money to expand access to individuals excluded from traditional banking systems.

The power of digital credit

Digital credit has emerged as a game-changer, leveraging technology to address the shortcomings of traditional lending. It encompasses various forms, including digital lending, mobile banking, and microfinance solutions. By utilising digital platforms, individuals can now access credit in a streamlined and efficient manner, bypassing the extensive paperwork, lengthy approval processes, and collateral requirements that often hinder their access to credit.

Digital credit has the potential to empower individuals and small businesses in emerging economies.

This is by providing easy and affordable access to credit, especially to MSMEs and entrepreneurs resulting in job creation, economic growth, and poverty reduction, fostering more inclusive and prosperous societies.

In the next decade, technological advancements will continue to reshape the digital credit landscape, further democratising credit access.

Here are the key ones driving innovation in the sector today, as well as in the future decade:

Alternative credit scoring: Traditional credit scoring models rely on historical financial data, often leaving out individuals without a formal credit history. However, advancements in machine learning and data analytics can enable alternative credit scoring.

By considering non-traditional data sources such as mobile phone usage, utility bill payments, cash flows and social activity, lenders can assess creditworthiness, extending credit to those who were previously excluded.

Blockchain and smart contracts: Blockchain technology can enhance the security, transparency, and efficiency of digital credit transactions. Smart contracts, powered by blockchain, have the potential to automate loan agreements, reduce the need for intermediaries, and lower transaction costs – attracting more participants and democratising credit.

AI and machine learning: In the digital credit space, AI algorithms can analyse vast amounts of data to assess creditworthiness in real time, enabling quicker loan approvals and disbursements. Machine learning can help lenders understand borrower behaviour and potential risks.

Responsible lending practices and regulations need to be in place to prevent over-indebtedness and protect borrowers from predatory practices.

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