Knowledge Architecture:ConceptsObservationsEvidence

Computational Revenue at Risk (CRaR)

CRAR(

Revenue Exposed to Computational Transmission Attrition

Proposed hypothesis — not yet testedpublished

CRaR measures revenue exposed to computational transmission attrition.

July 12, 2026
Version 1.0
6 min read
By Marco Patrone
crarrevenue_risktransmission_attritionfinancial_bridge_metric

Definition

CRaR quantifies the revenue at risk from computational transmission attrition—the portion of revenue that may be lost if AI-mediated allocation channels degrade or fail.

CRaR quantifies in monetary terms the revenue at risk from AI-mediated allocation channel degradation or failure.

Conceptual Formula

CRaR = total_revenue × (1 - CDTR) × transmission_sensitivity_factor.

Methodology

Type

index construction

Data Sources

syntheticrevenue data

Confidence Level

low

Description

CRaR = total_revenue × (1 - CDTR) × transmission_sensitivity_factor.

Limitations

  • Revenue attribution is complex
  • Transmission sensitivity requires estimation

Key Takeaways

Key Points

  • CRaR is currency-denominated
  • Revenue risk exposure measure
  • Depends on CDTR

Target Audience

firmsinvestorsrisk managers

Relevance Tags

crarrevenue_risktransmission_attritionfinancial_bridge_metric

Source Paper

The Zero-Click Economy

HomeSelf Research (2026)

View on Zenodo
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Citation

For the Computational Revenue at Risk (CRaR), see HomeSelf Research (2026), The Zero-Click Economy.

DOI: 10.5281/zenodo.21321629

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