How we turn raw signals into trade-grade intelligence
Authoritative public data, academically validated frameworks, transparent scoring. Every number on TradeCompaz is traceable to a named source and a documented model.
Data sources
| Source | Cadence | What we use it for |
|---|---|---|
| GDELT Project | every 15 min | Global political event monitoring |
| World Bank Open Data | quarterly/annual | GDP, inflation, trade balance, governance |
| UN Comtrade | monthly | Bilateral trade flows by HS code |
| World Bank WITS | annual | Live tariff rates and NTMs |
| OECD Stats | quarterly | FDI flows, productivity metrics |
| ECB Frankfurter | daily | Live FX data |
| FRED | daily | Treasury spreads, CPI, fed funds, oil |
| WTO | as published | Active disputes, escalation scoring |
| OEC | annual | Product complexity, top exporters |
| GTA | as published | Tariffs, subsidies, export restrictions |
Academic & industry frameworks
ISO 31000:2018
Risk score = Likelihood × Impact (1–25 scale)
ISO 22301 / 22317
Business Impact Analysis (financial, operational, regulatory, reputational)
SCOR Model 12.0 (ASCM)
Reliability, responsiveness, agility, cost, asset efficiency
Porter’s Five Forces
Trade-corridor competitive dynamics
World Bank LPI
Logistics performance scoring
WTO Trade Facilitation Agreement
Transparency and risk management baselines
EY Geostrategy Framework
Scan → Focus → Manage → Strategize → Govern
PESTLE Analysis
Political, Economic, Social, Tech, Legal, Environmental factors
Backtesting
Every score is backtested against historical events. For policy cascades, first-order effects average ~87% accuracy; second-order ~74%; third-order ~61%. We disclose confidence levels on every forecast — the further out, the more uncertainty.