How a Lending Club user mined the company's data to uncover shady loans made to Lending Club insiders and repeat borrowers
very disappointing scandal http://www.bloomberg.com/... Can numbers from fintech upstarts be trusted? Max Chafkin / @chafkin : If you liked our story about a mayo company buying its own mayo, you'll love sequelhttp://www.bloomberg.com/news/ features/2016-08-18/how-lending-club-s- biggest-fanboy-uncovered-shady- loans ... Colin Weir / @radiocolin : “Silicon Valley tends to venerate mildly deceptive tactics when they're used in service of a scrappy upstart” http://www.bloomberg.com/... Mike Dudas / @mdudas : The “no big deal” response by the Foundation Capital VC to clear fraud at Lending Club is a stunner. http://www.bloomberg.com/... Anil Dash / @anildash : Looks like @LendingClub has been buying its own mayo, so to speak. http://www.bloomberg.com/...
Context & Ripple Effects
This story is the forensic sequel to Bloomberg/WSJ coverage of LendingClub's collapse: the final days of CEO Renaud Laplanche ended with his ouster over loan irregularities, and this piece shows how an outside user — not an auditor or regulator — mined the company's own published data to surface shady loans to insiders and repeat borrowers. The reaction quotes frame the deeper issue: Max Chafkin ties it to prior coverage of circular self-dealing, Colin Weir argues Silicon Valley excuses 'mildly deceptive tactics' by scrappy upstarts, and Mike Dudas calls out a Foundation Capital VC dismissing clear fraud as 'no big deal'.
Why it matters: if a retail user can find what institutional investors missed, the credibility of fintech-upstart loan data itself becomes the story.
First-order effects
- Lending Club faces immediate pressure on two fronts: its insider and repeat-borrower loans are now publicly documented from its own data, and its VC backers' 'no big deal' posture becomes a reputational liability rather than shelter.
- Investors in marketplace-lending paper must re-underwrite platforms whose headline origination numbers are shown to be minable for exactly the anomalies diligence should have caught.
Second-order effects
- Rival online lenders inherit a trust discount: buyers of their loans will demand the kind of granular, outsider-verifiable disclosure that just embarrassed Lending Club, raising funding costs across the category.
- The episode hands consumer-protection enforcers a template — the same playbook of documented misrepresentation later used to shut down LendUp under a CFPB order shows where regulator attention lands once the pattern is visible.
Third-order effects
- If the pattern holds — Lending Club's insider loans, LendUp's ordered shutdown, Eco's misrepresented 'rewards APY', Tala's sky-high Kenyan rates — fintech lending consolidates around players who can survive external audits of their own data, while startup-venerated growth metrics lose their default credibility.
- Accountability shifts structurally toward outsiders: users, journalists, and eventually regulators doing the forensic work that boards and VCs declined, making 'scrappy upstart' cover progressively less defensible.
The trend: Fintech lending keeps proving that self-reported platform data can't be taken at face value, with outsiders and regulators — not boards or VCs — becoming the sector's real audit function.