AI applied to financial products: credit, receivables, document analysis automation, anticipation, transaction screening. The intersection of credit products and artificial intelligence.
AI in credit does not replace the credit decision — it enhances the surrounding steps: document analysis automation, receivables screening, contract reading, inconsistency flagging. The real gain is in freeing analysts for higher-value decisions, not in automating the final decision without risk criteria.
Everything. Credit pricing was never about the cost of processing a transaction. It was always about the value of unlocking working capital, anticipating a receivable, providing cash flow predictability. AI changes the delivery cost of this solution, but does not change the value benchmark. The framework is the same.
Automating without risk criteria quickly becomes a headache. The work is in designing governance: deciding where humans step in and where the machine decides on its own, classifying the impact of each automation, reviewing in layers. Lovable applied exactly this pattern for coding agents — the logic applies to credit.