Scenario modeling techniques: a checklist for climate transition risk in India
April 3, 2026
Rajeev Das
You’ve heard all about scenario modeling. But what does it look like in practice, especially in the Indian context? Our checklist, method by method:
Map drivers: start with the right variables
Scenario drivers must be context-specific. We map the policy signals, macroeconomic variables, and sector-specific factors that actually move outcomes. No averaging away unique risks. Our process checks for overlooked local dynamics and feedback loops that alter risk profiles.
Test baselines: shift assumptions, check reactions
Standard models use baseline assumptions that rarely fit every portfolio. We test these by changing policy timelines, altering energy transition rates, and varying compliance costs. The real test: does your model react the way actual Indian firms would? Our checklist reveals the answer.
Layer uncertainty: add plausible unknowns
Adding uncertainty isn’t a box to tick—it’s the point. We introduce plausible event ranges, stress major unknowns, and keep uncertainty layers explicit. Each additional uncertainty tests portfolio resilience, exposing risks hiding behind the consensus view.
Data sources: interrogate before using
Data sources define your model’s credibility. We interrogate the provenance, consistency, and context-fit of every input. Local agency reports, sector studies, and on-the-ground interviews all get a place on the list. If you’re not questioning your data, you’re copying errors.
Transparency: document every modeling step
Model transparency is everything. We document every choice, parameter, and outcome, so the path from input to result is visible. No black boxes here—just an open checklist for scrutiny.
Checklist complete—now compare your process to what you see here. We invite you to question every method on your current list.