SciRisk 100 · Automotive · Rank 21 of 100
BMW Group
BMW.DE · Germany · Automotive SC3 Moderate
What does this ESCRC number mean?
An ESCRC of $123.8m is the estimated economic supply-chain risk capital requirement generated by the SciRisk ESCRC model for BMW Group 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 $172.3m; in an ordinary year the expected loss is $32.2m.
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 |
|---|---|---|---|---|---|---|---|
| ZF FriedrichshafenDrivetrain parts | T1 | Germany | 7040 | 109.3 | 7.7 | 4.7 | 13.2 |
| BoschFuel injection/electronics | T1 | Germany | 11520 | 70.6 | 5.0 | 1.8 | 33.5 |
| Samsung SDIEV batteries | T1 | South Korea | 6400 | 39.2 | 4.2 | 1.8 | 33.5 |
| AUMOVIO SEBraking/HVAC systems | T1 | Germany | 5760 | 35.3 | 2.5 | 1.8 | 33.5 |
| CATLEV batteries | T1 | China | 5120 | 31.4 | 3.3 | 1.8 | 33.5 |
| Schaeffler AGBearings, clutches and driveline/powertrain components | T1 | Germany | 1920 | 27.5 | 2.5 | 4.3 | 14.3 |
| Magna InternationalBody stampings | T1 | Canada | 4480 | 27.4 | 2.1 | 1.8 | 33.5 |
| InfineonPower semiconductors | T2 | Germany | 3584 | 15.7 | 1.0 | 2.2 | 28.1 |
| MichelinTyres | T1 | France | 2560 | 15.7 | 1.1 | 1.8 | 33.5 |
| ThyssenKruppSheet steel | T2 | Germany | 3840 | 10.1 | 0.7 | 1.3 | 46.8 |
| Continental AGOriginal-equipment tires (Tires business, distinct from AUMOVIO SE) | T1 | Germany | 1280 | 7.8 | 0.6 | 1.8 | 33.5 |
| Envision AESCCylindrical EV battery cells | T2 | Japan/UK (US plant) | 1920 | 7.1 | 0.6 | 1.8 | 33.5 |
| EVE EnergyLarge cylindrical EV battery cells | T2 | China | 1280 | 4.7 | 0.5 | 1.8 | 33.5 |
| BremboBrake discs, calipers and pads (original equipment) | T1 | Italy | 768 | 3.2 | 0.3 | 1.3 | 48.7 |
| GlencoreCobalt/nickel | T3 | Switzerland | 1536 | 2.3 | 0.2 | 1.5 | 40.5 |
Scenario Analysis — coming in Phase 2
Recovery-time, supplier-diversification, inventory and geographic-diversification scenarios for BMW Group 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. BMW Group is highlighted.
| Rank | Company | Ticker | Country | Sector | RevenueUSD bn | ESCRCUSD m | ESCRC / Revenue% | Risk Grade | Change |
|---|---|---|---|---|---|---|---|---|---|
| 14 | Honda Motor | 7267.T | Japan | Automotive | 137.0 | 190.0 | 0.139 | SC4 High | ▲ +20.4% |
| 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% |
See this for your own supply chain
You are looking at BMW Group's supply-chain risk capital: $123.8m against $155.0bn of revenue, driven mostly by ZF Friedrichshafen and Germany. 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
- 14bcc93a48a6
- 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.