If recent press is anything to go by, you’d be forgiven for thinking that 2019 is the beginning of the end for the debt advisory sector as we know it.
At the very least, you might expect significant disruption to what has traditionally been a ‘people-based’ business. In 2018, a number of digital real estate finance platforms were launched, claiming to use bespoke algorithms to match borrowers with lenders.
Proptech has revolutionised several property subsectors. But I’m not convinced algorithms will put debt advisers out of a job yet. As the co-founder of a debt adviser, you’d expect me to say that, but let me explain why I feel securing real estate finance will always require the human touch.
Algorithms can outperform humans at repetitive tasks or crunching large, well-organised data; however, intrinsically diverse property projects are nuanced and require the qualitative judgements computers can’t yet deliver reliably.
Securing the best finance package for clients involves the detailed analysis and due diligence of projects, borrowers and teams. We often secure bespoke development or acquisition finance for clients thanks to the details we communicate to lenders – details I don’t believe even the most advanced AI-backed algorithm could analyse.
These are generally less quantifiable factors, such as: the borrower’s in-depth track record; the subtleties of the business plan; the quality of market intelligence and advice from third parties; as well as the back-up plan underpinning the security and so on.
Complex projects, particularly developments, are often affected by planning, political, environmental and social policies. Lenders accept that there will be unknowns at a project’s outset, which is why you can’t underestimate the quality of borrowers, their advisers and the delivery team. The numbers might look great on the appraisal but if the goalposts move, can the borrower ensure that the project reaches a satisfactory completion?
Not a homogenous asset
Lenders usually communicate their appetite to borrowers and advisers by ring-fencing criteria by geography, asset sector or size of ticket; rules that can be programmed into an algorithmic analysis. But as property is not a homogeneous asset, these boundaries are rarely absolute.
Banks and debt funds often lend outside published guidelines for ‘the right’ project or borrower. Understanding where they have done so – information that is rarely public knowledge – gives a good adviser a big competitive advantage.
The benefits of personal relationships hold true across other deal metrics. Often a lender only puts their best foot forward if they have a good chance of closing a deal – and that is best handled through personal relationships.
Similarly, how can an algorithm get an application to the front of the queue or ensure it reaches this week’s credit committee?
A combination of people and technology will achieve the best results for our clients. Last year, we developed a capital database to track lenders and loans in an interactive, searchable way. Debt markets are evolving rapidly thanks to a swathe of new entrants competing to attract market share, differentiating themselves by leverage, pricing, sector and geographic niches and creative structuring. This means more options for clients and more market data for us to collect.
In an increasingly crowded market, algorithms can help track and shortlist potential lenders. But the devil is in the detail – and it is the human touch that delivers approvals and closes deals.
Joanne Barnett is co-founder of London-based real estate debt adviser BBS Capital
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