Key takeaways
- H2O Driverless AI builds repayment, prepayment and default models from your own loan, payment and customer data.
- Propensity models predict whether a customer will apply for a mortgage or refinance within a given time window, so your offer arrives first.
- Every score comes with reason codes and sensitivity analysis, so credit risk and model risk teams can see how each input moves the result.
- A borrower likely to refinance gets a retention offer; a borrower likely to fall behind gets an early conversation about payment options.
Repayment behavior moves with every rate change
When rates fall, your best borrowers refinance elsewhere and the future interest you planned on disappears. When budgets tighten, other customers fall behind, and a late payment becomes a default before anyone calls.
Portfolio averages hide both. A prepayment curve for the whole book cannot tell you which borrower is about to leave, and a collections queue sorted by days past due cannot tell you who would repay with a small change to their plan. Every model you use for credit decisions also has to pass review: your risk team and your regulator will ask what drives each prediction and how it behaves when conditions change.