Glossary

Credit decisioning, in plain terms

Concise definitions of the vocabulary a modern risk team uses. Written to be looked up and shared.

Product

BNPL (Buy Now, Pay Later): BNPL (Buy Now, Pay Later) is short-term instalment financing decided at the point of checkout. Its challenge is approving credit in milliseconds with minimal friction, which requires a fast decision engine, alternative data sources and policies that can be tuned per merchant.
Loan origination: Loan origination is the end-to-end process from a credit application being submitted to it being approved and disbursed: data capture, identity verification, data-source calls, scoring, policy execution and the final decision. Automating it cuts response times from days to seconds.

Decision traceability: Decision traceability is the ability to reconstruct, for any given case, which policy was applied, on what data, which version was live and what outcome it produced. It is the baseline requirement for auditing, explaining and defending a credit decision to customers and regulators.
Model risk: Model risk is the exposure to poor decisions caused by flaws in the design, data or use of a scoring model or credit policy. It is mitigated through governance: independent validation, versioning, performance monitoring and full traceability of every change.

Champion/Challenger testing: Champion/Challenger is a technique for improving credit policies by routing a share of traffic to an alternative policy (the challenger) and comparing its performance against the one in production (the champion). It lets teams validate changes on real data at controlled risk before adopting them.
Credit scoring: Credit scoring is the technique of assigning an applicant a score that estimates their likelihood of repayment, combining internal data with external sources such as credit bureaus, behavioural data and alternative data. That score feeds the lending decision alongside policy rules.

Decision engine: A decision engine is software that automates credit application assessment by applying business rules, scoring models and external data to return a decision — approve, decline or refer — in milliseconds. Unlike custom-built code, it lets the risk team configure and change policies without engineering involvement.
Decision tree: A decision tree is the visual representation of a credit policy as a sequence of conditions (if/then) leading to an outcome. In a no-code engine it is built by dragging blocks, which lets business and risk teams design and read the logic without writing code.
Policy versioning: Policy versioning is the practice of storing every change to a credit policy as an identifiable version — with author, date and reason — and being able to tell which one was live at any point in time. It makes policies comparable, revertible and auditable without ambiguity.