Two Prime built one of the largest bitcoin-backed lending operations in the US by doing what collapsed lenders didn't: lending exclusively to institutions with provable bitcoin reserves. CEO Alexander Blume and CIO Nathan Cox explain their credit framework that's processed $3.5 billion in loans with zero liquidations across 40 margin calls, how they structured products using derivatives to eliminate margin call requirements entirely, and why their systematic trading strategies generating 8-10% bitcoin-denominated yields became the second pillar of their $2.5 billion business. Their approach reveals what institutional-grade infrastructure actually requires when managing other people's bitcoin. Topics Discussed: Credit infrastructure scaling $100M to $1.5B in loan origination within nine months using over-collateralization and institutional-only underwriting Structured loan products engineered with derivatives overlays to eliminate margin call requirements while maintaining LTV discipline Institutional borrower selection criteria: public companies with transparent bitcoin holdings versus retail credit risk vectors Systematic strategy architecture combining CTA-style trend following, mean reversion, and volatility positioning for bitcoin yield generation Custom OMS/EMS/PMS build requirements for simultaneous execution across 30-40 separately managed accounts with randomized order routing Why separately managed account structure became product-market fit for public companies avoiding pooled investment vehicle tax events Digital Asset Treasury categorization framework separating legitimate businesses from desperate pivots based on operational track record Bitcoin-only collateral thesis rejecting ethereum and altcoins despite demand based on institutional volatility profile analysis Institutional DeFi barriers that higher yields cannot overcome: custody gaps, AML/KYC requirements, and SOC compliance failures Deribit liquidity concentration at 87% options flow and why competitive threats haven't materialized despite predictions Listen to more episodes:  YouTube