SMEs are the backbone of the economy, yet for too many, the experience of securing finance remains slow and fragmented. At the same time, we are navigating growing SME portfolios, tighter regulatory expectations, and the relentless pressure to improve time to funding.
That’s why we brought a panel of lending and technology experts together to tackle these challenges head-on. Featuring Adam Archibald, Regional Director UKI at Mambu, Gareth Plummer, Head of Product at Recognise Bank (a shared client of nCino and Mambu), and Sebastien Vidal, Regional Vice President at nCino, the session covered everything from legacy infrastructure to AI adoption, and the path forward for lenders serious about transforming their SME offering.
Here are the four key takeaways and reasons to watch the full session on demand.
1. The real barriers to acquiring and onboarding SME customers
Lenders know that acquiring and onboarding SME customers is rarely straightforward, but the panel are clear about exactly why. Legacy infrastructure sits at the heart of the problem. When core systems weren't built or connected to support end-to-end lending and credit risk management, every step in the process becomes harder.
Adding to the challenge is data fragmentation. SME data isn’t always clean, consistent or easy to access. Lenders need the right data in the right place at the right time to make accurate decisions.
The result? Slow, disjointed processes that create friction for everyone involved. Brokers experience delays and poor communication. Borrowers face lengthy waits with little transparency. And internally, teams are spending time navigating system limitations rather than serving customers.
To reinvent the lending experience, end-to-end lending processes need to be slick, seamless, and designed around people and technology working in unison. Anything less is a competitive disadvantage.
2. Reducing time-to-yes without compromising on risk and compliance
Time-to-yes is critical for the SME segment. Managing risk and compliance while accelerating decisions requires the right technology, the right data, and a deliberate approach.
The key, the panel argues, is getting the right data in front of the right people at the right time. That means pulling verified data from the right sources early in the process to support an initial assessment, and empowering lending teams to move decisively to a conclusion, whether that is a yes or an equally important no.
“It’s about time to certainty, not just time to yes. The key is to give certainty and clarity to the broker and the borrower”, Gareth Plummer, Head of Product at Recognise Bank
This is especially critical in SME lending, where niche requirements are common. The panel highlights that most friction in the process sits in compliance; lenders need certainty that they’re lending to the right customers. This requires automating wherever possible. Spreading financials, running credit checks, and embedding credit policy checks directly into the workflow are all things that can be handled by technology, freeing human judgment for where it truly matters.
The reinvention outcome? Faster approvals, clearer escalation paths for complex cases, and significantly improved time to funding for SME customers.
3. Leveraging automation to drive operational efficiency
There’s still a significant amount of legacy in lending infrastructure across the industry, and batch-based processes remain commonplace. For lenders serious about operational efficiency, the priority should be automating the journey between application and disbursement.
The panel is clear about where to focus. Repetitive, low-value tasks such as data capture, manual data entry, and chasing information should be taken out of human hands. Technology should be used to pull data from the right third-party sources and surface it in a way that makes human judgment easier and faster.
When it comes to reinventing the lending experience, the goal of automation isn’t to remove people from lending; it’s to make sure the people in the process are focused on what matters and the cases that genuinely need a human judgment.
“You cannot just automate the whole lending decision process; instead, it’s about focusing attention on the bits that need human judgement…enabling the human decision maker to make better, faster, and more informed decisions”, Gareth Plummer, Head of Product at Recognise Bank
4. Building the connected banking ecosystem. AI-powered lending and modern core working together
AI must be a partner to the lending team, not a replacement for it. In a heavily regulated sector like lending, the human-in-the-loop concept isn’t optional. It’s essential.
The most compelling use case the panel explores is AI augmenting lenders in ways that genuinely transform productivity. Take credit committee reports, for example, traditionally one of the most time-consuming parts of the lending process, drawing on data from multiple people and systems. AI can now generate those narratives, verify the data, and ensure everything is correct and trusted before it goes anywhere near a decision maker.
But AI adoption in lending is not without its challenges. The panel identifies 3 things every institution needs to get right:
Use it in the right way, start small, and take an iterative approach
Partner with the right vendors
Focus on the right use cases and solving real, defined challenges,
A significant barrier to AI adoption remains access to near-real-time, accurate, and clean data. Without this foundation, AI cannot function effectively in a lending workflow. The panel is unequivocal that there’s a growing divide between lenders still running on legacy systems and those operating on modern platforms built to deliver the kind of outward-facing, AI-ready data foundation that makes genuine AI adoption possible.
“One of the biggest barriers is access to near real-time clean, accurate data…there’s going to be a big void between the legacy platforms and the modern players built and designed for outward-facing data access”, Adam Archibald, Regional Director UKI at Mambu
Regulatory and compliance risk is also front of mind. The most-cited hesitance from lenders comes down to how to adopt AI without exposing the organisation to new risks. The panel's advice is to embed AI within lending culture gradually, ensure proper governance is in place, and use the iterative approach to build confidence over time.
On customer experience, the panel is equally clear. The benefit of cloud-native, modern platforms is the ability to offer a genuinely joined-up experience for both brokers and borrowers. Customer data no longer needs to be scattered across disparate, siloed systems. With the right data flows, the right governance, and the right integrations between core banking systems, lenders can move faster and adapt more readily to what their SME customers actually need.
The panel's top tips for lenders embarking on this journey:
Be clear on what you are trying to achieve
Be precise about the use case you want to solve
Use as few systems as possible to do as much as possible
Find the right partners; and manage the change process internally to drive real adoption.
“The ability to integrate seamlessly between nCino, Mambu, and other core [EM1] platforms is really the key when it comes to the ability to move quickly and offer a joined-up experience”, Gareth Plummer, Head of Product at Recognise Bank.
The final word from the panel was a timely one. In today's uncertain world economic volatility, geopolitical instability, rapid regulatory change, the ability for lenders to pivot at pace will be a defining competitive differentiator. The institutions that build the right foundations now will be the ones best placed to respond.
Watch the full free on-demand session here for the complete discussion.
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