Nine months into my role as CEO of FundingBy, I have become increasingly convinced that the most important competitive advantage in property lending right now is not rate, appetite, or even relationships; it is the quality of your decision-making infrastructure.
Technology is transforming the way property finance is underwritten across the UK. For small private credit providers and non-institutional lenders, this is not a distant trend to monitor. It is happening now, and the lenders who are moving quickly are pulling ahead in ways that will be difficult to close.
The Old Model is Too Slow
Traditionally, underwriting a property loan meant manual risk assessments, physical valuations, and credit committees that moved at the pace of calendars. This friction costs deals, not because borrowers lose patience, but because the best brokers stop bringing transactions to lenders who cannot give them speed and certainty.
The fundamental shift happening right now is a move from subjective, labour-intensive credit analysis to data-driven, system-supported decision-making. Let me walk through what that actually looks like in practice.
AI That Supports Human Judgment
AI and machine learning are genuinely changing risk analysis. By processing large volumes of structured and unstructured data, including financial statements, market trends, and property metrics, AI can identify risk patterns that traditional rule-based models miss. But the more important point, I think, is that it does not replace human judgment.
At FundingBy, we have built our approach around what we call AIWHO: AI with human oversight. The AI acts as a powerful analytical layer that gives our credit team better information, faster. It helps us predict default probabilities with greater accuracy, automates data extraction and creates consistent risk scoring across loan types. What it does not do is make final decisions. That remains a human responsibility, and I think it always should.
The result of building our underwriting platform around this principle is that we can move significantly faster than a traditional credit committee model, without sacrificing the quality of judgment that complex property transactions genuinely require.
The Broker Experience Matters More Than People Admit
One of the things I have noticed most clearly since joining FundingBy is how much the experience of working with a lender affects deal flow. Brokers do not just send transactions to the lender with the best rate; they send them to the lender who is easiest to work with, most predictable, and least likely to waste their time.
Digital origination platforms are changing this dynamic. When brokers can track the status of a deal in real time, and when borrowers can input transaction details through a simple interface and receive an Agreement in Principle automatically, it removes frustrations that erode relationships over time. We have built this capability directly into how we work with our lending partners, and the feedback has been consistent: it makes us easier to use, and in a competitive market, that matters enormously.
What This Means for Niche Lenders
For alternative lenders serving SME developers and specialist property investors, these advances compound in interesting ways. Faster decisions mean higher deal throughput and stronger broker relationships. Better data enables risk-adjusted pricing that genuinely reflects each borrower’s profile, rather than forcing everyone into broad buckets. And scalable technology means you can grow volume without a proportional increase in headcount.
The niche lender has always had advantages over the high street bank: flexibility, relationship quality, and willingness to engage with complexity. Technology is now adding speed and analytical depth to that list.
The Honest Reality of Implementation
I want to be direct about something, because this part of the conversation is usually glossed over: implementing these tools in a real lending business is hard. Not technically; the software exists and it works. The harder challenge is human.
Getting an experienced team to genuinely trust an AI output, takes time and deliberate effort. There is a real tension between moving fast enough to capture deals and maintaining the oversight that protects the business. We have had moments at FundingBy where the process moved faster than the team’s confidence in it, and we had to pause and rebuild that confidence properly before pushing forward.
What I have learned is that the Human-Tech Collaboration model is not a compromise position; it is the actual answer. The lenders who will win in this space are not the ones who automate the most, or the ones who resist automation. They are the ones who work out exactly where technology adds clarity and where human experience adds judgment, and build a process that reflects both honestly.
Where This is Heading
Data-driven underwriting will become the baseline expectation within the next few years, not a differentiator. The question for niche lenders is not whether to invest in these capabilities; it is how to do so in a way that preserves what makes them valuable: the expertise, the flexibility, and the relationships that institutional lenders cannot replicate.
I am still learning what that looks like at FundingBy. But I am more convinced than ever that getting the technology layer right is what will determine which niche lenders are still standing, and thriving, in five years’ time.