All autopsies

// STARTUP COMPARISON

Geopagos (2022 crisis) vs LendingClub (2016 crisis)

Geopagos (2022 crisis) failed in 2022 due to Unit Economics. LendingClub (2016 crisis) failed in 2016 due to Founder Chaos. Different causes, different sectors, different eras — but the same simulation outcome.

METRIC🔥 Geopagos (2022 crisis)🔥 LendingClub (2016 crisis)
SectorFintechFintech
CountryArgentinaUSA
Founded20132006
Died20222016
Raised$35M$1.3B
Peak$35M raised$9B valuation
Primary CauseUnit EconomicsFounder Chaos

// WHY EACH FAILED

🔥 Geopagos (2022 crisis)
Unit Economics
Geopagos provided white-label payment acceptance infrastructure to banks and fintechs across Latin America. After raising $35M and processing billions in payments, the 2022 fintech funding crunch hit infrastructure plays hard. Geopagos's bank clients slowed implementation timelines and reduced scope of projects. Unable to maintain its burn rate without a new funding round, the company underwent restructuring and significant layoffs.
// LESSON
Infrastructure plays selling to banks have elongated revenue recognition cycles. You need 18-24 months of runway beyond the point you expect the first enterprise contract to close. If you don't have it, you run out before you get paid.
🔥 LendingClub (2016 crisis)
Founder Chaos
LendingClub CEO Renaud Laplanche resigned in May 2016 after an internal review found that $22M in loans had been sold to an investor with falsified application dates, and that Laplanche had failed to disclose a personal conflict of interest. The stock fell 50% in a single day. LendingClub survived but spent years rebuilding institutional trust.
// LESSON
For marketplace lenders, loan data integrity is the product. Falsifying origination dates is not a compliance technicality — it invalidates every institutional investor's credit risk model and destroys the trust that marketplace lending is built on.

// IN THE SIMULATION

Geopagos triggers B2B_SALES_CYCLE_RISK — bank client implementations have 12-18 month sales cycles. In a funding crunch, runway runs out before the enterprise revenue materializes. The simulation flags infrastructure companies with >80% bank-client revenue as having elongated revenue recognition risk.

LendingClub triggers FINTECH_FOUNDER_DATA_MANIPULATION — the simulation models loan data integrity as a hard constraint for marketplace lenders. When origination data is falsified, every institutional investor's credit model becomes invalid simultaneously.

// EXPLORE FURTHER