The promise of financial inclusion has been around for decades. What is different now is the scale and speed at which AI can either close or widen the gap. Joining me is Shamina Singh, Founder and President of the Mastercard Center for Inclusive Growth and EVP Sustainability at Mastercard. Shamina, welcome to the show.
Thank you so much for having me.
You have spent your career at the intersection of finance and inclusion. What has AI actually changed about that work?
AI has changed the scope of what is possible. When we think about financial inclusion — getting people access to credit, to savings, to payments — the traditional barriers have always been the same. No credit history. No formal employment record. No collateral. AI, when trained on the right data, can look at alternative signals of creditworthiness and financial behaviour that traditional systems simply cannot process at scale. That changes the math on who can be served profitably. And when you can serve someone profitably, you serve them sustainably — not as a charity project but as a business.
But AI trained on the wrong data can also automate exclusion at scale.
Absolutely. And that is the risk we have to take seriously. If the data AI is trained on reflects decades of lending decisions that systematically excluded certain communities, the model will learn that those communities are higher risk — not because they are, but because they were never given the chance to prove otherwise. That is why the design choices made now matter so much. Who is in the room when these systems are built? What data are they trained on? Who audits the outcomes? These are not technical questions. They are governance questions.
Where are you seeing genuine, measurable progress on financial inclusion right now?
Digital payments infrastructure has been transformative. In markets across Africa, South Asia, and Southeast Asia, mobile money and digital payment systems have brought hundreds of millions of people into the formal financial system for the first time. That is the foundation. What AI can do now is build on that foundation — using transaction data to extend credit, to detect fraud, to provide personalised financial guidance. The Mastercard Center for Inclusive Growth has been funding research and programmes in this space for years, and the evidence is real. The question now is how to scale what works and how to govern it responsibly.
Mastercard sits at the intersection of financial infrastructure and sustainability. How do those two things actually connect?
Financial inclusion and sustainability are not separate agendas. They are the same agenda. If you do not include people in the formal economy — if you leave hundreds of millions of people outside the financial system — you cannot build a sustainable global economy. Climate resilience, economic stability, social cohesion — all of these require that people have access to the financial tools to manage risk, build assets, and participate in economic life. Mastercard's sustainability strategy is built around that conviction. Financial inclusion is not a side programme. It is central to what sustainable business actually means.
What is your message to financial institutions that are still treating inclusion as a CSR exercise rather than a core business opportunity?
The data does not support that framing anymore. The populations that have historically been excluded are also the fastest-growing consumer segments in the world. The middle class is expanding in Africa, in South Asia, in Southeast Asia. The question is not whether those markets will matter — they already do. The question is whether you are building the products and infrastructure to serve them now, or whether you will be playing catch-up in ten years. AI makes it possible to serve these markets profitably at scale. The institutions that figure that out first will have a significant competitive advantage.
Thank you so much for joining us today.
Thank you. It is a conversation I am always glad to have.
