AI in mortgage financing accelerates but human advisers remain indispensable
AI in mortgage financing speeds approvals and cuts costs, but advisers remain essential as rising rates, regulation and liability limit full automation.
The recent Iran conflict rattled mortgage markets and intensified a rush to lock in loan conditions, while banks race to deploy AI in mortgage financing to speed approvals and reduce costs, industry executives say. Tomas Peeters, CEO of the Bilthouse Group and Baufi24, described a market shock that pushed rates up about 0.2 percentage points and prompted customers to secure cheaper terms before funding conditions tightened. At the same time, lenders such as ING are piloting automated decision tools that aim to shorten processing times and set new standards for speed and cost efficiency.
Iran conflict drives a short-term rate scramble
The geopolitical escalation led to an unexpected near-term rise in lending rates, provoking immediate reactions from borrowers and lenders alike. Many customers reacted by accelerating purchase decisions or fixing rates quickly to avoid higher costs once the market adjusted to the shock.
Industry leaders warned that while the initial surge in demand locks favorable terms for some, subsequent financing conditions will be tougher as lenders recalibrate pricing and underwriting in response to elevated uncertainty. The short-term rush reduces available capacity and may complicate approvals for buyers who cannot move as fast.
Markets optimistic about peace, ECB faces trade-offs
Equity markets have already priced in hopes of a de-escalation, but officials and analysts remain cautious about structural changes to inflation expectations. Peeters argued that the European Central Bank may delay rate tightening to avoid choking off growth, yet monetary policy cannot remain passive if inflation expectations drift higher.
That tension could translate into lower growth and upward pressure on long-term yields, a dynamic that would raise borrowing costs beyond the immediate shock. Lenders and borrowers must therefore weigh both near-term opportunities and medium-term interest-rate trajectories when arranging mortgages.
ING’s InstantBaufi raises the speed and cost bar
ING’s rollout of its “InstantBaufi” tool has already prompted competitors to test similar automation to capture quick-decision business. Peeters said Bilthouse is trialing comparable AI systems and welcomed the technology’s ability to establish a market benchmark for speed and reliability.
Faster decisions do not necessarily expand market share for the first mover, he noted, but they reduce costs and set expectations for service levels industry-wide. If other banks follow, customers could benefit from shorter lead times and lower operational fees even as pricing competition remains focused on rates and underwriting quality.
Advisers remain central to complex, one-off home purchases
Despite automation gains, customer behavior still favors human interaction in the majority of home-buying cases, industry executives say. Peeters estimated that between 95% and 98% of buyers will continue to seek personal advice for their first significant property purchase, especially where grants, energy-efficiency incentives or construction issues are involved.
Complex situations—such as allocating debt across multiple properties or coordinating specialist services like energy consultants and installers—reinforce the need for adviser judgment. Whether the adviser sits in a bank branch or acts as an independent broker is secondary to the buyer’s desire for local knowledge and empathetic guidance.
Bilthouse deploys AI for document reading and adviser support
Recent advances in machine learning have enabled firms to extract structured data from unstructured documents that were previously too complex for automation. Peeters described progress in parsing long, nuanced documents such as 100-page subdivision declarations and automatically identifying document types with high accuracy.
Bilthouse is already using AI to draft communications and pre-fill analyses, allowing advisers to focus more on client interactions and less on administrative tasks. The company sees productivity gains and a potential to engage younger, chat-preferred customers, while flagging operational risks if automated systems fail or produce errors.
Regulatory, liability and practical limits constrain automation
Executives cautioned that AI currently handles standard cases well but stumbles on large, high-risk or legally intricate files. Scenarios involving novel collateral structures or partial debt transfers between family members require creative solutions and human judgment that current models cannot reliably reproduce.
Regulatory and liability questions remain unresolved, particularly around who bears responsibility when an algorithm’s recommendation leads to a poor outcome. Banks hold the long-term performance data needed to build robust scoring models, but those datasets are not freely available to brokers, limiting independent providers’ ability to develop fully autonomous decision systems.
Looking ahead, industry leaders expect a hybrid operating model: AI will prepare and streamline analyses while human specialists retain final oversight for complex or sensitive decisions. That combination aims to preserve consumer confidence, satisfy regulators, and capture efficiencies without relinquishing accountability.
The transition will reshape roles and processes in mortgage financing, but it will not eliminate the adviser’s function overnight; instead, technology will change how advisers spend their time and whom they can serve.
