Guide
April 24, 2026
by Shweta Kulkarni
Annotated step-by-step guide to validating custom risk metrics in India
Abstract
Validation is more than math. It’s the discipline of tracing every decision, documenting every test, and inviting challenge. This annotated guide highlights where to look and what to ask at each step.
1.Data Review
Begin with data review. Assess the quality, source, and completeness of all inputs before running any model. In our experience, early transparency about data weaknesses shapes better metric design and faster error correction.
Always question the initial data. Even the most trusted source can hide unexpected gaps or biases.
2.Peer Review
The next stage is peer review. Assemble a team with diverse backgrounds to review every step. In India, we’ve found combining academic and practitioner insights surfaces issues that pure technical reviews miss. Document all findings.
No formula survives first contact with reality—be prepared to adapt after peer challenge.
3.Documentation
Validation is incomplete without clear documentation. Keep a running log of every decision, test, and outcome. This living record is vital for ongoing reliability, especially as teams or regulations change.
Document changes as you go. Transparent records prevent confusion later and ease future audits.