How I built an AI that reads bank contracts the way bankers do (not the way customers do)

How I built an AI that reads bank contracts the way bankers do (not the way customers do) The problem started in 2009. I was a banker. I watched loan officers use internal scoring grids that customers never saw. The information asymmetry wasn't illegal — it was just never shared. Fifteen years later, the asymmetry got worse. Banks now run LLMs on customer data before any human reviews it. The customer still signs without understanding what they're signing. So I built the reverse. The core insight: bankers read contracts differently than customers A customer reads a loan contract linearly — page by page, looking for the monthly payment. A banker reads it dimensionally — simultaneously scanning for: Covenant triggers (what makes the loan callable) Cross-default clauses (what other contracts could trigger this one) Margin ratchets (how the rate changes under specific conditions) Termination asymmetries (who can exit and under what conditions) These aren't hidden in fine print. They're jus