The Evolution of Online Lending
P2P lending is no longer a niche asset class that’s only considered favourable terrain by early adopters and yield chasers. It’s big business nowadays. The UK market alone has originated £9bn in loans.
A lot of commentators have focused on the fact that the marketplace lending model is yet to be stress tested by tighter credit conditions, but I’d prefer to focus on something far more interesting – the emerging crossover between lending and big data, and how this poses a serious threat to incumbents in the P2P lending sector.
P2P lending has technology in its DNA, and leading platforms like Zopa, RateSetter and Lending Club are the original fintech pin-ups, matching lenders with individuals and businesses hungry for credit. But now P2P is being played at its own game by aggressive companies entering the lending space.
The reason for this is simple – by connecting to users’ bank accounts, accounting software and even social profiles, fintechs can leverage large volumes of data in order to better calculate risk and optimise the lending process. Think of it as “insider information” on borrower behavior and credit worthiness. All this has been made possible by APIs, which enable technology companies to safely and efficiently access user data across platforms on a permissioned basis.
Perhaps the most interesting thing about this is the extension of credit to people and businesses who would previously have found it difficult to borrow due to gaps in their credit history, dodgy financials and other red flags. This had been made possible by technology and data analytics, transforming the underwriting process from a static risk assessment made at origination into a dynamic, real-time process whereby underwriters monitor borrowers on an ongoing basis.
An entirely new market is forming, and fintechs are moving in for their slice of the action and the potential profits. The FT reported this week that OnDeck has $1.1bn in loans on its balance sheet. Kabbage has lent out a total of $6bn in the past 10 years. And PayPal extended $1bn in credit to businesses in Q3 2018 alone.
There’s a price for everything, provided you can calculate risk. A progressive, tech-enabled approach to underwriting opens lending up to small businesses, where liquidity can have a huge impact. Using large volumes of data to do this at scale lowers costs for intermediaries and underwriters, bringing smaller loan transactions in to play and enabling lenders to target the long tail of businesses. Advances in AI and machine learning will undoubtedly further improve this process in the years to come.
It’s often said that data is now the world’s most valuable commodity. But does it actually qualify as a commodity? After all, not all data sets were born equal. In fact, the data held by payments companies and accounting software providers is far superior to that held by say, a fitness app. Payment companies like PayPal and Square enjoy the privilege of owning and accessing the world’s most powerful data, and they’re now discovering how to monetise that information efficiently by going into the credit business.
Where does this leave P2P platforms? They will no doubt battle on, but it will be hard for them to compete with large payment companies with global reach and superior data. This is part of a wider trend towards technology companies seeking to bundle products and services in order to monetize their data and diversify their operations. Of course, the potential for tie-ups with banks is huge, and we are already seeing some interesting partnerships emerge. By working with new age lending platforms, banks can grow their balance sheets quickly and cheaply, with greater visibility on underlying risk.
I promised I’d try not to talk about the credit cycle, but I can’t resist! Playing devil’s advocate, could it be that the new breed of lenders are actually better placed to weather a tightening of liquidity conditions than traditional lenders, since their risks are more accurately priced? Could this time really be different, thanks to the awesome power of technology and big data? I don’t have the answers, but we will get them eventually.