OmniScore

Better lending decisions, explained

Traditional scorecards struggle with customers who have little credit history and react slowly to change. OmniScore uses machine learning on a wider set of signals — repayment behaviour, account transactions, cash-flow patterns and approved alternative data — to produce a more accurate view of risk.

Explainability first

Every score comes with the factors that drove it, so credit officers understand each decision, customers can be given clear reasons, and risk teams can satisfy auditors and regulators.

From score to decision

• Decision engine — configurable policy rules turn scores into approve, refer or decline outcomes with limits and pricing.
• Portfolio view — track approval rates, risk distribution and early-warning signals across the loan book.
• Model governance — monitoring for drift and bias, with documented model versions and validation reports.