De-Biasing Geopolitical and Regulatory Risk: The GCTI™ Framework and the Operationalization of Structured Analytic Techniques (SATs) in Global Corporate Governance
Authors/Creators
Description
This technical white paper introduces the Global Corporate Threat Intelligence (GCTI™) framework, a proprietary applied intelligence methodology developed by Jose Parejo & Associates (JPA). The framework addresses a persistent structural gap in corporate risk advisory: the disconnect between macro-level geopolitical forecasting and the operationally precise intelligence required for boardroom decision-making. Drawing on field experience across more than 100 countries and five continents, the paper argues that the primary failure mode in corporate geopolitical risk is not analytical depth, but the absence of structured methods for translating intelligence into actionable governance outputs. The GCTI™ framework resolves this through the systematic deployment of Structured Analytic Techniques (SATs) — including Analysis of Competing Hypotheses (ACH), Premortem Disruption Modeling, and High-Impact/Low-Probability Threat Assessments — originally developed within Western sovereign intelligence communities and codified in CIA and ODNI analytical standards. The paper situates the GCTI™ framework within the broader transatlantic risk advisory landscape alongside institutional counterparts including Eurasia Group, McLarty Associates, and the US Army War College Strategic Studies Institute, establishing a clear methodological position for boutique applied intelligence as a complementary and distinct capability. Outputs of the framework are designed to be legally defensible, auditable, and directly usable in international dispute resolution, asset protection, and multi-jurisdictional compliance. This document is registered for open-access indexing via SSRN and Zenodo and forms part of the permanent methodological corpus of Jose Parejo & Associates.
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v.2 JPA_GCTI_White_Paper_v2.pdf
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Additional details
Related works
- Is identical to
- Working paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6868198 (URL)
Dates
- Copyrighted
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2026-05-08