Most models assume risks are Independent, Normally distributed, and Symmetric.
Reality is uglier: Bad events cluster, Channels fail together, and Downside risk is nonlinear.
This is why “Diversified” portfolios still collapse and forecasts look fine—until they don’t.
"Which channels fail together in bad scenarios?"
"How correlated are downside risks?"
"What does worst-case revenue loss actually look like?"
"Are we overexposed to a single hidden risk?"
"How fragile is our growth under stress?"
Copula Models separate the Individual behavior of variables from their Dependency structure.
Instead of assuming “If X is bad, Y is probably fine”, Copulas ask: “When X is bad, how likely is Y to also be bad?”
Think of it as: “Mapping failure patterns, not success stories.”
The Problem
Multiple channels drop simultaneously.
What It Reveals
Hidden dependency during downturns.
Decision Enabled
Reduce concentrated exposure.
The Problem
Worst-case planning is hand-wavy.
What It Reveals
Realistic downside joint outcomes.
Decision Enabled
Build buffers before crises.
The Problem
“Diversified” spend isn’t truly diversified.
What It Reveals
Which channels fail together.
Decision Enabled
Spread risk intelligently.
The Problem
Plans look fine under normal assumptions.
What It Reveals
What breaks under stress.
Decision Enabled
Choose resilient strategies.
The Problem
Fragility is subjective.
What It Reveals
Quantified tail dependence.
Decision Enabled
Rank risks instead of guessing.
SpendSignal uses Copula Models as a risk correlation layer.
Specifically:
This stops SpendSignal from saying “The average looks fine” when the real danger lives in the tails.
Instead of “Each channel has acceptable risk”, you see:
The decision insight: "This portfolio fails together."
Only if revenue collapse isn’t a concern.
No. It models how bad things get *if* crises occur.
Yes—SpendSignal surfaces dependency insights, not math.