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AI is fundamentally reshaping digital lending. Models that used to follow fixed rules and slow update cycles are now being replaced by adaptive systems that learn from borrower behaviour in real time. This shift promises better accuracy, broader inclusion, and powerful new portfolio insights — but it also introduces a far more important question:

Can lenders govern AI models with confidence?

In an era of dynamic machine-learning systems, governance becomes the differentiator. Below is a practical view of how lenders should think about credit model governance in the age of AI.

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When news broke that MUFG, Japan’s largest bank, is building a new digital-lending subsidiary powered by OpenAI, the focus naturally fell on automation, chatbots, and customer experience.

But the real transformation isn’t in how AI talks to customers — it’s in how it thinks about credit.

If MUFG truly re-engineers lending operations around AI, it won’t just streamline processes. It will change who gets approved for credit — and how financial systems define risk.

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Across emerging markets, the conversation about SME finance has evolved.. We’ve moved beyond “access” and into “design”: how can lenders deliver credit that flexes with business growth — without losing control of risk?

Many pilots now prove that alternative data, digital scoring, and revenue-linked lending can work. But for most institutions, these remain isolated experiments. The next frontier is institutional — embedding innovation into governance, credit policy, and culture so that experimentation becomes part of how lenders operate, not an exception.

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India is often cited as a pioneer for digital-financial infrastructure: real-time payments, biometric e-KYC, open-data APIs and more. These rails have enabled not just improved access to finance, but entirely new business models in credit. As regulators and lenders elsewhere explore how to bring innovation into MSME finance and SME lending, the Paytm case offers lessons for how digital rails can power lending products—and how fintechs and digital banks convert infrastructure into scale.

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Not every market enjoys India’s digital infrastructure. Across Asia, Africa, and parts of Latin America, lenders face thin credit bureaus, fragmented data, and weak secured-transaction laws. Yet progress is still possible.

The key is adaptation—finding pragmatic, risk-controlled workarounds while laying the foundation for long-term reform.

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Digital lending is reshaping access to finance for micro, small, and medium enterprises (MSMEs). But technology alone doesn’t create transformation—infrastructure does. India’s experience shows how a coordinated framework of digital identity, data standards, and secured-transaction systems can unlock credit at scale.

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Scaling digital lending is never just about customer demand or smart credit models. At some point, the question becomes: where does the money come from to fund the loan book?

For GCash, which serves over 90 million users in the Philippines, answering that question was critical to turning lending from an experiment into a sustainable, revenue-generating product line. Much like Akulaku in Indonesia, GCash has had to innovate on the back-end funding structures that make large-scale lending possible.

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When GCash first introduced GScore, it marked a turning point in the Philippines’ digital finance ecosystem. For the first time, mobile money transaction data could be transformed into a credit score — providing a foundation for responsible lending. But data alone doesn’t build a lending business. To turn credit insights into real products, GCash needed partners with balance sheet strength and regulatory expertise: the banks.

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In the Philippines, GCash has become synonymous with digital finance. What began as a payments and wallet service is now one of Southeast Asia’s most influential fintechs. A key driver of this growth is its move into lending — powered by GScore, a proprietary credit scoring system built from user data.

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Akulaku stands out not only for its scale but for its ingenuity in funding innovation. What truly differentiates Akulaku is how it funds its loan book — blending traditional debt, risk-sharing, and revenue-linked financing to fuel growth without excessive dilution or risk exposure.

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Akulaku began in 2016 as an e-commerce platform offering customers the ability to purchase goods on installments. In a market where fewer than 3% of Indonesians had access to credit cards, this innovation quickly resonated. Akulaku wasn’t just helping people shop — it was pioneering digital lending in one of the world’s largest underbanked markets.

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Fuliza is Safaricom’s overdraft / short-term credit service that allows users to complete M-PESA transactions even if their account lacks sufficient funds. Find out how they did it…

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Nearly 11 years ago, two giants in their fields—Safaricom, the telco behind M-PESA, and the Commercial Bank of Africa (CBA)—joined forces to launch M-Shwari…