By Daniel Broadhurst, Commercial Director at Finova
Over the past year, the tone of conversations with lenders has started to change. Historically, complex borrowers were viewed as edge cases — scenarios that required workarounds rather than systemic solutions.
That perspective is becoming harder to justify.
Across bridging, commercial and specialist residential lending, borrower profiles are evolving. Contractors operating through limited companies, portfolio landlords with layered ownership structures, and business owners with non-linear income streams are no longer exceptions. They are increasingly representative of the market itself.
The real question is no longer how to accommodate complexity, but why the industry continues to treat it as unusual.
The real source of friction
It’s easy to assume that complexity creates operational strain because of the borrowers themselves. In reality, most of the friction sits elsewhere.
Underwriters are not the issue. They are highly skilled, experienced and well-equipped to assess nuanced cases. The challenge lies in how information is presented to them.
Data is often fragmented across systems. Key details arrive in unstructured formats, requiring manual interpretation. Two underwriters can review the same case and reach different conclusions simply because the underlying information has been assembled differently.
In fast-moving areas such as bridging, this becomes particularly problematic. Speed is often central to the product offering. Yet when underwriters must manually piece together financial positions — combining historic accounts, live cashflow and exit strategies from multiple sources — decision timelines inevitably stretch.
This isn’t a capability gap. It’s an infrastructure issue.
Rethinking the role of AI in specialist lending
Much of the current conversation around AI in lending focuses on incremental improvements: dashboards, reporting layers or document extraction tools. While valuable, these don’t fundamentally change how complex cases are assessed.
What’s more transformative is the emergence of more proactive, agent-driven capabilities.
Instead of simply surfacing information, these tools can organise and interpret it. They can pull in verified financial data, structure documents automatically and highlight patterns across multiple income streams — presenting a coherent, contextualised view of a borrower before an underwriter even begins their assessment.
This doesn’t replace human judgement. In specialist lending, that judgement is central to the proposition. What it does is shift the balance of effort — away from gathering and reconciling data, and towards making informed decisions.
Seen through that lens, this is less about automation and more about enabling underwriters to operate at their full potential.
The cost of standing still
Few lenders would argue that their current systems are perfectly suited to the demands of today’s borrowers. Yet many are still hesitant to act — waiting for the right moment, the right integration opportunity, or a fully formed solution.
That hesitation carries a cost.
It shows up in longer processing times, inconsistent decision-making and missed opportunities. Borrowers with complex needs are often the most commercially valuable, but they are also the quickest to look elsewhere if the experience falls short.
The lenders making the most progress aren’t necessarily the largest or the most technologically advanced. They are the ones focusing on the right problem.
Not “which tool should we implement?” but “where does complexity slow us down, and how do we remove that friction?”
Moving beyond workarounds
Complex borrowers don’t require exceptions or special handling. They require systems designed with their realities in mind.
As the market continues to evolve, the ability to handle complexity efficiently will become a defining competitive factor. Lenders that invest in better data foundations and more intelligent workflows will not only improve speed and consistency, but also unlock a broader, more valuable segment of the market.
The opportunity is clear. The question is how quickly the industry chooses to act on it.
