The balance sheet versus the profit-and-loss statement is one of the great rivalries in corporate America. Lending Club now aspires to bridge the great divide. The fintech has purchased a conventional financial institution, Radius, and rebranded itself as a “digital marketplace bank”. It is a counter-intuitively shrewd move.
In the wake of the financial crisis, fintechs threatened to eat the lunch of stodgy, paralysed banking titans. Algorithms would give them an edge and their lack of branches would make them agile. Lending Club was one of the first, offering unsecured personal loans typically used to pay off consumer debt.
A decade later, banking looks less boring. The Radius deal has doubled Lending Club’s shares. Tough regulation and steep capital requirements are evidently prices worth paying for cheap funding from deposits.
The legacy Lending Club depended on fees from matching lending banks with consumer borrowers. Loans were originated by the company but funded externally then sold off to third-party investors. Marketing expenses remained stubbornly high as the company grew. In 2019, for example, Lending Club had just $2m of adjusted net income on $760m of revenue after originating $12bn in loans.
Financing lines were expensive at more than 3 per cent. As a bank with deposits costing 35 basis points, charges are much lighter. The rub is that Lending Club will now retain loans originated from this funding source. According to its maths, interest income — even netted against accounting losses — will generate $12m of revenue over two years. This compares against $4m of immediate fee revenue in its historical role as an intermediary.
The missing part of the equation is the capital Lending Club will need to hold on its balance sheet against loans. This will curtail the return on equity. Still, Lending Club loans charge an interest rate around 15 per cent. With good underwriting and lower marketing costs, banking should still be a good business. Lending Club will retain its agency business as the bulk of its operation. So it should be able to find the sweet spot between the two models.
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