A financial journalist warns that rapid growth in a new bank can be a red flag. It often signifies aggressive lending to win market share, but the quality of those loans and associated risks may not become apparent for several years. This makes fast-growing banks, like the new tech-focused Erbador Bank, a source of cautious skepticism.
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Erebor, a new bank from Palmer Luckey and Joe Lonsdale, achieved the fastest approval in 25 years by flipping the traditional growth model. Instead of aggressive lending, they plan to lend only 50% of deposits (vs. the typical 90%), signaling to regulators that stability, not risk, is their priority.
Scott Goodwin highlights that while major banks report stable consumer credit, they overlook the explosive growth of online lenders like Upstart and SoFi. This hidden leverage, often ending up on insurance company balance sheets, means the US consumer is far more indebted than traditional metrics suggest.
The most imprudent lending decisions occur during economic booms. Widespread optimism, complacency, and fear of missing out cause investors to lower their standards and overlook risks, sowing the seeds for future failures that are only revealed in a downturn.
Unlike prior tech revolutions funded mainly by equity, the AI infrastructure build-out is increasingly reliant on debt. This blurs the line between speculative growth capital (equity) and financing for predictable cash flows (debt), magnifying potential losses and increasing systemic failure risk if the AI boom falters.
Contrary to being another SVB, Palmer Luckey's new bank Erebor is designed as its opposite. It targets tech and defense customers with a hyper-conservative model focused on high deposit-to-loan ratios, prioritizing capital safety over yield for its startup clients.
Widespread credit is the common accelerant in major financial crashes, from 1929's margin loans to 2008's subprime mortgages. This same leverage that fuels rapid growth is also the "match that lights the fire" for catastrophic downturns, with today's AI ecosystem showing similar signs.
Contrary to a popular trend among Indian FinTechs, simply adding a lending product is not a surefire way to make money. PhonePe's CTO warns that lending is an extremely difficult business to get right and is globally known for causing startups to fail.
Analyst Gil Luria argues that financing speculative AI infrastructure with debt, based on promises from cash-burning startups like OpenAI, is fundamentally unsound. This "unhealthy behavior" mirrors patterns from past financial bubbles by confusing equity-type risk with debt-based financing, creating significant instability.
In the current AI hype cycle, a common mistake is valuing startups as if they've already achieved massive growth, rather than basing valuation on actual, demonstrated traction. This "paying ahead of growth" leads to inflated valuations and high risk, a lesson from previous tech booms and busts.
A simple framework for assessing financial products involves checking for three warning signs. If it's too complex to explain to a 12-year-old, seems too good to be true, or lacks proper auditing, it's a major red flag. This heuristic helps investors cut through hype and avoid potential blow-ups like MicroStrategy's.
