RCMECredit materiality pre-analysisIncludes illustrative values
Analytical aid.Not a rating or rating recommendation. Public data only.
Boston Scientific
CIK
0000885725
SIC
3841
Event
8-K Item 1.05 · cyber incident
Identified
2026-08-25
Filed
2026-09-08
Overall
Moderate to Elevated
Boston ScientificAmgenV.F. Corp
Audit trail

RCME pre-analysis · Analytical aid, not a rating or rating recommendation

Boston Scientific: Form 8-K Item 1.05 cybersecurity incident

Report 194 · 2026-10-20 03:07 UTC · Disclosure pass · claude-opus-5-5 · Derived

1. Incident summary

The issuer disclosed a cybersecurity incident under Item 1.05 of Form 8-K [8-K 0000885725-26-000059 Item 1.05]. The fields below are derived from the filing by the engine and are labeled "derived" in the inputs.

The tiers in this memo (low, moderate, elevated, high) are the engine's materiality tiers under internal calibration. They are not ratings and should not be read as such [scoring.yaml combination].

2. Business Risk

  • The disclosed disruption reaches manufacturing, the distribution network, and order processing and shipping [8-K 0000885725-26-000059 Item 1.05]. For a device manufacturer, these functions sit on the revenue path. The engine therefore treats the event as an operational disruption shock rather than a data-only event [scoring.yaml cyber].
  • Low scenario (7 outage days): the Business Risk tier is moderate. The engine's stated reasons are "partial disruption" and "rule for moderate met" [scoring.yaml business_tier_rule_cyber].
  • Base scenario (21 outage days): the Business Risk tier is elevated. The engine's stated reasons are "outage 21 >= 14 days" and "rule for elevated met" [scoring.yaml business_tier_rule_cyber].
  • High scenario (42 outage days): the Business Risk tier is elevated. The engine's stated reasons are "outage 42 >= 14 days" and "rule for elevated met" [scoring.yaml business_tier_rule_cyber].
  • The outage-day values are scenario assumptions under internal calibration. They are not facts from the filing [scoring.yaml cyber].
  • The affected unit share of 1.0 is an upper bound because the affected segment is not identified. The scenario results may therefore overstate the disruption if only one of the 2 reportable segments is affected [scoring.yaml cyber].
  • Because the data types compromised are unknown, the engine cannot assess data-related exposure through its data-type calibration [scoring.yaml cyber].

3. Financial Risk

Inputs

  • The metrics are drawn from SEC XBRL companyfacts (as-reported, USD).
    • Verified figures: CFO of $4,534M, cash interest of $319M, and operating lease liabilities of $536M.
    • Derived figures: FFO of $4,101M, debt of $11,436M, EBITDA of $4,981M, and FOCF of $3,658M.
  • EBITDA, FFO and FOCF are non-GAAP style measures. They are treated as unverified.
  • DCF is null because dividends paid and share repurchases are missing.
  • The ratios are as-reported proxies. S&P adjustments are not applied [corporate_methodology p.33].

Table selection

  • The engine applies the standard table (Corporate Methodology Table 17) by default [corporate_methodology p.33].
  • Under the criteria, the table is selected from industry and country risk, which the engine does not compute. The table choice is therefore an internal calibration default, not a criteria determination [corporate_methodology p.33].
  • The criteria use five-year time-weighted ratios [corporate_methodology p.32]. The inputs here reflect fiscal year 2025 only.

Pre-event ratios

  • FFO/debt: 35.86%, band index 2 (30% to 45%). The relative distance to the 30% boundary is 0.1953, so the ratio is not within 10% of the boundary [corporate_methodology p.33].
  • Debt/EBITDA: 2.30x, band index 2 (2x to 3x). The relative distance to the 3x boundary is 0.2347, so the ratio is not within 10% of the boundary [corporate_methodology p.33].
  • Neither ratio is borderline under the 10% relative-distance test [corporate_methodology p.32].

Post-event scenarios

ScenarioLost EBITDAFFO/debt (band 2, 30% to 45%)Distance to 30%Debt/EBITDA (band 2, 2x to 3x)Distance to 3x
Low (7 days)$48M35.44%0.18142.32x0.2273
Base (21 days)$143M34.61%0.15362.36x0.2120
High (42 days)$287M33.35%0.11182.44x0.1880

Sources for the table: [corporate_methodology p.33] [scoring.yaml cyber].

  • In all three scenarios, both ratios stay in band index 2, which is 0 bands from the pre-event position. Each relative distance remains at or above 0.1 [corporate_methodology p.32].
  • The Financial Risk tier is low in the low, base and high scenarios. The engine reports "rule for low met" in each case [scoring.yaml financial_tier_rule].
  • In the high scenario, the FFO/debt distance of 0.1118 is the closest any ratio comes to the 10% borderline threshold [corporate_methodology p.32].

4. Liquidity

5. Governance

  • No governance flags were raised in the inputs [scoring.yaml overlay_rule].
  • The governance overlay is downside only. It never lowers a tier and moves a tier by one step at most [scoring.yaml overlay_rule].
  • With no flags, the overlay did not change the scenario results [scoring.yaml overlay_rule].
  • Overall tier: the overall tier is the worst of Financial, Business and Liquidity, with no weighted average. Dimensions without a tier are skipped rather than treated as low [scoring.yaml combination].
    • The resulting overall tier is moderate in the low scenario and elevated in the base and high scenarios.
    • The overall range is moderate to elevated, with 0 unscored cases [scoring.yaml combination].
  • Because Liquidity is skipped, the overall tier does not reflect any liquidity effect [scoring.yaml combination].

6. Key watch factors

  • Containment and outage duration. Containment is ongoing. The Business Risk tier moves from moderate to elevated once the outage reaches 14 days or more [scoring.yaml business_tier_rule_cyber].
  • Segment identification. Disclosure of the affected segment would replace the 1.0 upper-bound affected unit share and could narrow the scenario results [scoring.yaml cyber].
  • Data types. Disclosure of compromised data types would allow the engine's data-type calibration to be applied [scoring.yaml cyber].
  • FFO/debt distance to the 30% boundary. In the high scenario this distance is 0.1118, close to the 10% borderline threshold. A longer outage than the high scenario would warrant reassessment [corporate_methodology p.32].
  • Liquidity inputs. Information on contracted asset sales, the 12-month working capital change and expected shareholder distributions would allow the liquidity reference levels to be tested [liquidity_descriptors p.13] [liquidity_descriptors p.8] [liquidity_descriptors p.9].
  • Table selection. An industry and country risk assessment could point to a table other than the standard default [corporate_methodology p.33].
  • Recovery measures. Further disclosures about system restoration, patch or update activity, and any governance findings could trigger the downside-only overlay [scoring.yaml overlay_rule].

7. Sources

Filing

Criteria excerpts

Internal calibration (docs/scoring/scoring.yaml)

Financial data: SEC XBRL companyfacts (as-reported, USD).

8. Disclaimers

  • This memo is an analytical aid. It is not a credit rating or a rating recommendation and does not represent the view of any rating committee.
  • Based only on public information. Figures are as-reported in SEC filings unless labeled derived or estimate.
  • Non-GAAP figures (including EBITDA, FFO and FOCF) are treated as unverified. Ratios are as-reported proxies without S&P adjustments.
  • Materiality tiers, outage-day scenarios, sector mapping and table selection are internal calibration. They are not criteria determinations.
This pre-analysis is an analytical aid for credit analysts. It is not a credit rating, a rating recommendation or a rating opinion, and it is not an input to any rating committee. Financial figures are as-reported proxies from SEC XBRL data; S&P adjustments are not applied. Internal calibration values are labeled where used.

Sources cited

  • [corporate_methodology p.32]Corporate Methodology, para 118, p.32: a ratio less than 10% from a range boundary in relative terms is borderline (ratio_bands.borderline_relative)
  • [corporate_methodology p.33]Corporate Methodology, para 123, p.33: the ratio table is chosen from industry and country risk, which the engine does not compute (ratio_bands.table_selection)
  • [liquidity_descriptors p.13]Methodology And Assumptions: Liquidity Descriptors For Global Corporate Issuers, para 37, p.13: sources over uses of at least 1.2x, and sources minus uses staying positive after a 15% EBITDA decline (liquidity.reference_levels)
  • [liquidity_descriptors p.16]Methodology And Assumptions: Liquidity Descriptors For Global Corporate Issuers, para 40, p.16: sources over uses below 1.2x as a reference level (liquidity.reference_levels)
  • [liquidity_descriptors p.8]Methodology And Assumptions: Liquidity Descriptors For Global Corporate Issuers, para 23, p.8: sources of liquidity counted in A (liquidity.sources_of_liquidity)
  • [liquidity_descriptors p.9]Methodology And Assumptions: Liquidity Descriptors For Global Corporate Issuers, para 30, p.9: uses of liquidity counted in B (liquidity.uses_of_liquidity)
  • [scoring.yaml business_tier_rule_cyber]docs/scoring/scoring.yaml, business_tier_rule_cyber: Business Risk tier rule for cyber events, internal calibration
  • [scoring.yaml combination]docs/scoring/scoring.yaml, combination: overall tier is the worst dimension, no weighted average, internal calibration
  • [scoring.yaml cyber.sector_map]docs/scoring/scoring.yaml, cyber.sector_map: SIC to sector map, internal calibration
  • [scoring.yaml cyber]docs/scoring/scoring.yaml, cyber: cyber shock: disruption fractions, outage-day scenarios, data types and sectors, internal calibration
  • [scoring.yaml financial_tier_rule]docs/scoring/scoring.yaml, financial_tier_rule: Financial Risk tier rule, internal calibration
  • [scoring.yaml liquidity.gate_rule]docs/scoring/scoring.yaml, liquidity.gate_rule: liquidity gate states, internal calibration applying verified reference levels
  • [scoring.yaml liquidity.xbrl_proxies]docs/scoring/scoring.yaml, liquidity.xbrl_proxies: XBRL proxies for liquidity inputs (prior-year capex, 12-month maturities)
  • [scoring.yaml overlay_rule]docs/scoring/scoring.yaml, overlay_rule: governance overlay, downside only, internal calibration

Time to memo

57.3 seconds Derived

Engine processing time from filing ingest to memo, one measured run, excludes analyst review.

V.F. Corp, ledger rows 129 (ingest) to 133 (report). Derived (difference of two ledger timestamps).