Property Lending Technology: Who’s Keeping Up, Who’s Falling Behind?

    Paul Huxter - Head of Intermediary Sales and Distribution

Legacy Systems vs. New Technology

Technology excels in the black-and-white areas of finance – where rules are clear and decisions binary. That’s why brokers are becoming more technologically reliant: some to deliver faster, more accurate service, others simply to meet clients’ expectations for instant answers and digital ease.

While brokers adapt quickly, many high street banks remain locked into legacy systems – outdated infrastructures never designed for today’s speed or complexity. Adding new tech to these systems only increases fragility and costs. Yet the costs and disruption that a full redevelopment will cause, makes change almost impossible. In contrast, lenders with adaptable platforms are better positioned to meet shifting borrower expectations in an increasingly tech-led market.

Automation: Benefits and Limitations

A recent study (although from the automotive lending sector) shows that for simple loans, humans and automated underwriting models perform similarly. As complexity increases, models tend to outperform, delivering higher profitability and lower default rates. Yet, direct comparative data in the mortgage sector remains limited, so the true impact of automation on lending is still uncertain.

Ironically, even though automation seems to reduce risk, tech-driven loans are often priced higher due to the perceived risks technology is thought to add. But fractional differences in rates can still mean thousands over the course of a loan term. Faster decisions may come at a cost to the borrower.

Beyond cost, trust and generational attitudes matter too. Digital natives (such as Gen Z and Millennials) are more comfortable with tech-driven processes, while older generations may prefer face-to-face advice. This shapes how borrowers engage with technology and their willingness to embrace it.

In terms of application, automated lending systems work best in straightforward scenarios like low-risk residential and buy-to-let mortgages. But in the “grey areas”, prevalent in specialist lending, technology struggles. Most models are trained on binary data and lack the nuance for subjective decisions. For instance, a human underwriter might approve a borrower who’s changed jobs within the same industry, while a model could flag this as a risk.

The Future: Balancing Technology and Expertise

AI continues to evolve, impacting the lending market, with regulatory and ethical concerns coming to the fore. Regulators such as the FCA are increasingly focused on ensuring automated decisions are fair and transparent. Over-reliance on automation risks missing exceptional cases or introducing unintended bias.

As specialist lending grows, the tension between automation and the need for case-by-case underwriting will intensify. Automation handles the “black-and-white,” but the “grey areas” will still require a blend of technology and human expertise. However, with enough training, data, and computing power, AI can grow to understand and analyse these “grey areas” much more efficiently – with brokers acting as the final check in complicated cases.

Thus, staying on top of the tech evolution has become a non-negotiable. I wouldn’t be surprised if this drives more brokers to join clubs and networks with advanced infrastructure – because those with the right tools will have a clear advantage.