Scenario Testing explained: this guide covers what it means, who it applies to, the step-by-step process, documents required, fees, due dates and penalties in India — so you can stay compliant with confidence and avoid costly mistakes.
Some things do not vary by a percentage. A regulatory approval is granted or refused; a resolution succeeds or it does not. Those uncertainties need a different tool.
Why sensitivity analysis is not enough
Sensitivity analysis evaluates the impact of changes in individual assumptions. But certain valuation uncertainties arise from discrete events or outcomes that cannot be adequately assessed by varying a single assumption. In such cases, scenario testing may provide a more meaningful assessment of uncertainty.
Where it applies
| Scenario | The uncertainty |
|---|---|
| Going concern vs. liquidation | Where the viability of the business or the success of the resolution process is uncertain |
| Recovery of disputed assets or receivables | Where recoverability may range from nil recovery to full recovery |
| Litigation outcomes | Where value depends on the outcome of significant legal proceedings |
| Regulatory approvals | Where asset utilisation or business operations depend on pending approvals |
| Resolution success vs. delayed resolution | Where timing materially affects business continuity or asset recoverability |
An illustrative framework sets each scenario against its key assumption and its valuation impact — liquidation, going concern, and nil, partial (say 50%) and full recovery of a disputed asset.
In CIRP assignments, the comparison between going-concern value and liquidation value is often the most significant scenario analysis, because it directly illustrates the economic implications of the alternative outcomes available to stakeholders.
That comparison is not optional analysis — Regulation 35 requires both figures. What is optional, and often omitted, is presenting them as a scenario comparison: stating what each assumes, why the gap is the size it is, and what the CoC is therefore choosing between.
Two numbers in separate sections of a report leave that work to the reader. The same two numbers presented as alternative outcomes with their assumptions disclosed do the work the section 30(2) and section 53 comparison actually requires.
The nil / partial / full structure
For disputed assets the framework is deliberately three-point rather than a range, because recovery is not continuous. A receivable in litigation is not 60% recoverable — it will be recovered, partly recovered on settlement, or not recovered.
This is also the honest answer to a nil value assignment on a disputed asset. Rather than asserting nil and inviting a challenge that the asset was written off, the report can present the nil conclusion as the adopted scenario and quantify what full recovery would add.
The discipline
- Scenario testing should be used selectively, and only where the conclusion is materially dependent on a specific uncertain event.
- The assumptions underlying each scenario should be clearly disclosed and supported.
- Scenarios should represent realistic possibilities rather than extreme outcomes designed to influence the valuation conclusion.
The third point is a warning about the tool's own risk. A scenario set that runs from a plausible base case to an implausibly favourable upside is advocacy, and it is visible as such to any informed reader.
It supplements, it does not replace
Scenario testing supplements, but does not replace, sensitivity analysis. The primary focus should remain on testing key valuation assumptions, with scenarios reserved for circumstances where uncertainty arises from discrete events or fundamentally different valuation outcomes.
The objective throughout is not to predict the future, but to demonstrate how the valuation may change under alternative, reasonably possible circumstances.
Common mistakes
- Running scenarios for every uncertainty instead of the discrete ones.
- Presenting fair value and liquidation value without framing them as alternative outcomes.
- Building scenarios whose assumptions are never disclosed.
- Substituting scenario testing for sensitivity analysis on the key assumptions.