Making automated lending decisions understandable
LendWise uses a machine-learning risk model to give instant loan decisions, and explains every one of them clearly.
Our story
LendWise began as a data-science project exploring loan default prediction on a dataset of 252,000 applicant profiles. We engineered features, compared several models and selected a tuned Random Forest that balances catching risky profiles with approving good ones.
We then wrapped that model in a complete digital lending experience — application, instant decision, decision letter, status tracking and an officer dashboard — to show what a responsible, end-to-end ML product looks like.
Every decision screen is honest about what the model does and doesn’t consider. Loan amount, for instance, is recorded but is not a model input.
What we stand for
- Transparency
- We show what the model uses, how it performs and where it falls short.
- Speed with care
- Instant decisions, delivered respectfully — especially when the answer is no.
- Human oversight
- Automation assists; loan officers can always review and override.
- Responsible by design
- LendWise shows how machine learning can be used responsibly in lending. It does not issue credit.
Decisions on LendWise are generated by a machine-learning risk model and are not an actual credit offer.