Inspiration
Global trade policy shifts, especially tariffs as of recent, often move faster than the tools people have to understand them. In recent years, sudden tariff announcements have created unintended economic shockwaves, disproportionately affecting specific industries and regions before policymakers, businesses, or investors can react. We aim to fix that.
What it does
TradeRisk is an explainable simulation engine that helps users understand how global tariff changes impact Canadian industries.
Specifically, TradeRisk allows users to:
- Visualize tariff exposure across Canadian sectors
- Simulate “what-if” tariff scenarios by adjusting:
- tariff magnitude
- target trading partners
- affected sectors
- tariff magnitude
- Rank sectors by risk using transparent, interpretable metrics
- Understand why risk changes, not just that it does
Instead of producing a single prediction, TradeRisk emphasizes risk awareness and insight. Users can see how exposure shifts under different policy decisions and which factors—such as export dependency or concentration—are driving vulnerability.
This makes TradeRisk useful for:
- policymakers evaluating trade decisions,
- analysts assessing sector risk,
- and anyone seeking clarity around complex trade dynamics.
How we built it
The backend uses real Canadian trade data and a deterministic risk engine to quantify exposure under different tariff scenarios, exposed through a Flask API. We built our risk engine using processed datasets that capture sector-level export values across Canadian industries, bilateral trade shares between Canada and more than 200 trading partners, partner concentration metrics to measure dependency risk, and tariff reference tables used to calibrate scenario-based shocks. Together, these datasets allow the model to quantify how exposed different sectors are under varying tariff conditions in a transparent and interpretable way, ensuring that all results are based on observed trade relationships rather than synthetic or speculative inputs.
Challenges we ran into
The main challenge was avoiding oversimplification. Tariff risk is complex, and we had to be careful not to present results as predictions. Aligning large, messy trade datasets across partners and sectors while keeping the UI clear and defensible was also non-trivial.
Accomplishments that we're proud of
- An end-to-end system connecting real data to interactive simulations
- Clear baseline vs scenario comparisons instead of raw scores
- An explainable risk model with transparent drivers
- A professional, data-first dashboard design
What we learned
Small UI and wording decisions can dramatically change how trustworthy an analytical tool feels.
What's next for TradeRisk
Next, we plan to support multi-partner scenarios and deeper sector granularity.
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