Reinventing Mortgages with AI

Frustrated by outdated processes, Stuart Cheetham, CEO of MQube built MPowered to prove that AI-driven mortgage lending can be faster, fairer, and more efficient – changing the game for brokers and borrowers alike.

By Patricia Cullen | Dec 10, 2025
MQube
Stuart Cheetham , CEO, MQube

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When Stuart Cheetham first encountered the sluggish, paper-heavy mortgage process, he saw an opportunity: technology could transform a system bogged down by legacy systems and manual checks. As founder and CEO of MQube, Cheetham didn’t just develop a platform – he built a full-service, AI-powered lender, MPowered, to demonstrate that mortgages could be processed faster, more accurately, and with a better experience for everyone involved. His journey underscores a key lesson: in complex industries like financial services, technology alone isn’t enough – solutions must work seamlessly with the people who use them. Entrepreneur UK finds out more…

What inspired you to tackle a specific problem in the tech industry?
I was frustrated by how slow and outdated the mortgage process was, not just for borrowers, but for brokers and lenders too. Decisions that should take minutes were taking weeks because of legacy systems and manual checks. I saw an opportunity to use data and AI to rebuild the mortgage process from the ground up, to create something faster, fairer, and far more efficient.

What unexpected challenges did you face while addressing this problem?
The biggest challenge wasn’t the technology, it was the ecosystem around it. Mortgages are highly regulated and involve multiple stakeholders who are used to doing things a certain way. Convincing them that automation and AI could be both compliant and beneficial took time. Integrating with legacy systems was also more complex than we ever anticipated.

How did those challenges shape the way you approached your solution?
Those challenges were exactly why we built MPowered. We realised that to truly fix the problems in mortgage lending, we couldn’t just build tools, we had to build a lender from the ground up, powered by our own technology. MPowered became the proof point for what our platform could do: show that an end-to-end, AI-driven process could deliver mortgages faster, with fewer errors, and a better experience for brokers and borrowers alike. It shaped everything, from how we designed our tech stack to how we worked with brokers day-to-day. MPowered is now the fastest growing mortgage lender in the UK.

What’s the most important lesson you’ve learned about solving tough tech problems?
Technology alone doesn’t solve problems, people do. You can have the most advanced AI models in the world, but if they don’t fit into real workflows or if people don’t trust them, they’ll never get used. The key is building technology that works with people, not around them.

What advice would you give other tech entrepreneurs facing similar challenges?
Start by deeply understanding the industry you’re trying to change: its pain points, its regulations, and its people. Then, design technology that complements rather than conflicts with that reality. And finally, be patient. Real transformation takes persistence, especially in industries as complex as financial services.

When Stuart Cheetham first encountered the sluggish, paper-heavy mortgage process, he saw an opportunity: technology could transform a system bogged down by legacy systems and manual checks. As founder and CEO of MQube, Cheetham didn’t just develop a platform – he built a full-service, AI-powered lender, MPowered, to demonstrate that mortgages could be processed faster, more accurately, and with a better experience for everyone involved. His journey underscores a key lesson: in complex industries like financial services, technology alone isn’t enough – solutions must work seamlessly with the people who use them. Entrepreneur UK finds out more…

What inspired you to tackle a specific problem in the tech industry?
I was frustrated by how slow and outdated the mortgage process was, not just for borrowers, but for brokers and lenders too. Decisions that should take minutes were taking weeks because of legacy systems and manual checks. I saw an opportunity to use data and AI to rebuild the mortgage process from the ground up, to create something faster, fairer, and far more efficient.

What unexpected challenges did you face while addressing this problem?
The biggest challenge wasn’t the technology, it was the ecosystem around it. Mortgages are highly regulated and involve multiple stakeholders who are used to doing things a certain way. Convincing them that automation and AI could be both compliant and beneficial took time. Integrating with legacy systems was also more complex than we ever anticipated.

Patricia Cullen

Entrepreneur Staff

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