SciRisk 100 · Automotive · Rank 32 of 100
Tesla
TSLA · USA · Automotive SC3 Moderate
What does this ESCRC number mean?
An ESCRC of $93.2m is the estimated economic supply-chain risk capital requirement generated by the SciRisk ESCRC model for Tesla under the stated assumptions: a 365-day horizon, 100,000 simulated years, and the 95% tail of the resulting loss distribution. Beyond that threshold the average loss — the Expected Shortfall — is $123.0m; in an ordinary year the expected loss is $23.9m.
Value-at-Risk: the portfolio loss not exceeded with the chosen confidence level. Read as the ESCRC risk capital — the loss the firm should be prepared to absorb in a bad year. Model-implied and intended for screening and ranking, not a calibrated capital figure.
Supply Chain Risk Capital Profile
Where the risk capital comes from. Every column is a production-engine output for this network — nothing is inferred.
By tier
Share of summed standalone VaR. Deeper tiers are attenuated by the engine's echelon buffer factors and capped by flow conservation.
By supplier geography
Major-event risk is correlated within a geography group (rho = 0.35), so concentration here compounds.
By supplier industry
Buckets are the calibrated-priors industry classes that set each supplier's minor-event rate.
| Supplier | Tier | Country | ExposureUSD m | Standalone VaRUSD m | Expected lossUSD m | Tail intensityrevenue-days | RoESCRCx |
|---|---|---|---|---|---|---|---|
| Panasonic EnergyEV batteries | T1 | Japan | 7110 | 78.4 | 8.1 | 3.3 | 20.0 |
| CATLEV batteries | T1 | China | 7900 | 49.1 | 5.1 | 1.8 | 35.5 |
| LG Energy SolutionEV batteries | T1 | South Korea | 4740 | 29.4 | 3.1 | 1.8 | 35.5 |
| NidecDrive motors | T1 | Japan | 2370 | 15.6 | 1.8 | 2.0 | 33.4 |
| VersigentWiring harnesses | T1 | Ireland | 2370 | 14.7 | 1.1 | 1.8 | 35.5 |
| Samsung ElectronicsFSD compute chips | T1 | South Korea | 1975 | 14.6 | 1.4 | 2.2 | 29.7 |
| ZF FriedrichshafenElectric drivetrain components and safety/chassis systems | T1 | Germany | 790 | 12.4 | 0.9 | 4.7 | 14.0 |
| AlbemarleLithium hydroxide | T2 | USA | 2765 | 8.5 | 0.6 | 1.5 | 42.9 |
| MichelinTyres | T1 | France | 1185 | 7.4 | 0.5 | 1.8 | 35.5 |
| NucorSheet steel/castings | T2 | USA | 1975 | 5.3 | 0.4 | 1.3 | 49.6 |
| Aptiv PLCHigh-voltage connectors, busbars and wiring/interconnect systems | T1 | Ireland | 790 | 4.3 | 0.4 | 1.6 | 40.8 |
| Robert Bosch GmbHiBooster electromechanical brake booster | T1 | Germany | 790 | 3.4 | 0.3 | 1.3 | 51.6 |
| GlencoreCobalt/nickel | T3 | Switzerland | 1185 | 1.8 | 0.1 | 1.5 | 42.9 |
| Continental AGOriginal-equipment tires for Model 3/Model Y | T2 | Germany | 474 | 1.8 | 0.1 | 1.8 | 35.5 |
| Ganfeng Lithium Co.Battery-grade lithium hydroxide | T3 | China | 316 | 0.6 | 0.1 | 1.8 | 35.5 |
Scenario Analysis — coming in Phase 2
Recovery-time, supplier-diversification, inventory and geographic-diversification scenarios for Tesla are not part of this release. The ESCRC Calculator already supports what-if analysis on a network you build yourself.
Sector peers
Nearest-ranked companies in Automotive. Tesla is highlighted.
| Rank | Company | Ticker | Country | Sector | RevenueUSD bn | ESCRCUSD m | ESCRC / Revenue% | Risk Grade | Change |
|---|---|---|---|---|---|---|---|---|---|
| 18 | Mercedes-Benz Group | MBG.DE | Germany | Automotive | 160.0 | 136.9 | 0.086 | SC3 Moderate | ▲ +36.3% |
| 21 | BMW Group | BMW.DE | Germany | Automotive | 155.0 | 123.8 | 0.080 | SC3 Moderate | ▲ +28.9% |
| 24 | General Motors | GM | USA | Automotive | 187.0 | 118.2 | 0.063 | SC3 Moderate | ▲ +19.0% |
| 27 | Stellantis | STLA | Netherlands | Automotive | 200.0 | 110.0 | 0.055 | SC2 Low | 0.0% |
| 29 | Ford Motor | F | USA | Automotive | 176.0 | 101.5 | 0.058 | SC2 Low | ▲ +18.1% |
| 32 | Tesla | TSLA | USA | Automotive | 97.0 | 93.2 | 0.096 | SC3 Moderate | ▲ +0.2% |
See this for your own supply chain
You are looking at Tesla's supply-chain risk capital: $93.2m against $97.0bn of revenue, driven mostly by Panasonic Energy and Japan. The calculator runs the same engine on a network you build yourself.
Company data as of 2026-06-30 · ESCRC calculated 2026-09-21 · dataset 2026.09-23 Beta
- Simulation
- 100,000 Monte Carlo paths · 95% confidence · 365-day horizon
- Seed
- 20260821 · regional correlation ρ = 0.35
- Input basis
- Curated network, calibrated-prior parameters
- Input fingerprint
- b85ad0e5f313
- Financials
- Curated from the company's most recent reported full financial year, as filed.
- Network
- Curated from company supplier disclosure; purchase volumes declared as a share of reported COGS.
- Parameters
- lambda1/lambda2 = calibrated ESCRC priors 2026.09-5 bucket defaults; r1/r2 = median of the shipped production preset networks within the same industry x geography cell when that cell has enough independent data, else the same industry-only bucket median, or (for industries with no preset supplier coverage) a directly-cited external recovery-event duration where one was found; ic = the same preset-network median (no external benchmark exists for this parameter for any industry). All three clamped into externally-cited recovery-time/BI-loss bounds per field.
Beta / preliminary dataset. Company inputs are analyst-curated from public annual reports and public supply-chain disclosure. ESCRC itself is computed by the production ESCRC engine — only the INPUTS on this page are preliminary.