LATAM context
Every LATAM lender runs its own scoring model. Typical inputs: credit bureau history, verified income, expenses, job tenure, account behavior. finO$ supplies the inputs derived from bank statements.
Concrete example
A scoring model might use "average net monthly income, last 6 months" (extracted from bank statements with finO$) as one of 30+ features that predict default probability.
How it shows up on your bank statement
A score doesn't appear on the statement, but many of the variables that feed it get calculated from it: income volume and stability, the ratio of fixed expenses to income, average balance, and how often the account overdraws. That's why the quality of statement extraction directly shapes the quality of the score.
How does finO$ handle this?
finO$ doesn't generate the score itself (that's your IP), but it delivers the structured inputs your model needs: recurring income, filtered internal transfers, exposure to other lenders.