debt_leverage_profile
0.29x Total Debt / Equity (Conservative)
High
SEC-XBRL
interest_rate_sensitivity
High sensitivity; ~$1.4B floating-rate debt means 200bps rate rise adds ~$28M annual interest expense, compressing net income ~15-20%
Inferred
Agent_Inference
geopolitical_supply_exposure
High intensity; OPEC+ supply decisions and Russia-Ukraine conflict drive price volatility.
Medium
GICS-commodity-overlay-v1
supply_chain_dependency
Strait of Hormuz (crude oil flows) and Strait of Malacca (Asia-Pacific petroleum trade) are top two critical chokepoints
Inferred
Agent_Inference
international_expansion_readiness
Revenue denominated primarily in USD via spot/TC charter contracts; minimal direct FX devaluation exposure as global tanker rates are USD-settled
Inferred
Agent_Inference
geographic_footprint
Operates globally across Atlantic, Pacific, Middle East routes; USD-denominated contracts insulate from local currency devaluation in key markets like Asia and Europe
Inferred
Agent_Inference
commodity_exposure_profile
High intensity; commodities: Crude Oil, Natural Gas, Coal, Refined Petroleum Products, Uranium, Steel (equipment); geopolitical: OPEC+ supply decisions and Russia-Ukraine conflict drive price volatility.
Medium
GICS-commodity-overlay-v1
vendor_lock_dependency_score
No single vendor exceeds 30% of input costs; fuel (bunkers) is largest variable cost but sourced from multiple suppliers across global ports
Inferred
Agent_Inference
business_model_type_primary
Asset-heavy maritime shipping; negligible cloud infrastructure dependency; cloud account termination would affect back-office only, not core vessel operations
Inferred
Agent_Inference
business_model_type_secondary
Secondary digital exposure limited to vessel management software and ERP systems; no revenue-critical SaaS dependency on major cloud providers
Inferred
Agent_Inference
switching_cost_profile
Minimal API coupling risk; operations rely on maritime industry software (VMS, ERP) with multiple substitutable vendors and no proprietary API lock-in
Inferred
Agent_Inference
howey_test_risk_index
Low Howey risk; revenue derived from physical vessel charter services, not investment contracts or profit-sharing schemes with passive investors
Inferred
Agent_Inference
regulatory_burden_tier
High
Medium
GICS-regulatory-overlay-v1
data_sovereignty_risk
Low GDPR/CCPA exposure; primary data involves vessel operations and B2B charter contracts, not consumer personal data requiring strict compliance frameworks
Inferred
Agent_Inference
antitrust_exposure_flag
Low-moderate; tanker market is fragmented globally; INSW holds ~1-2% market share; no dominance trigger, though shipping cartel scrutiny exists historically
Inferred
Agent_Inference
regulatory_exposure_profile
High burden; regimes: EPA, FERC, DOE, CFTC, OSHA, SEC; Accelerating emissions mandates and methane rules threaten capex economics.
Medium
GICS-regulatory-overlay-v1
revenue_model_type
~60-70% transactional spot market revenue, ~30-40% recurring via time-charter contracts; highly cyclical with limited long-term contracted revenue base
Inferred
Agent_Inference
monetization_vector
Per-voyage and time-charter day-rate model; revenue tied directly to vessel utilization and prevailing tanker spot rates (Worldscale pricing benchmark)
Inferred
Agent_Inference
pricing_architecture
Price-taker in commodity freight market; rates set by global supply-demand dynamics; stress scenario of 30% rate decline cuts EBITDA by ~$150-200M annually
Inferred
Agent_Inference
pricing_power_rating
Low standalone pricing power; rates driven by Baltic Dirty/Clean Tanker Indices; INSW is a price-follower, not price-setter in fragmented tanker market
Inferred
Agent_Inference
target_gross_margin_bracket
Gross margin ~55-65% on TCE basis; net voyage revenues after port/bunker costs; EBITDA margins ~40-55% in strong rate environments, ~10-20% in troughs
Inferred
Agent_Inference
churn_vulnerability_index
No free-rider problem; physical shipping services require direct contracts; churn risk exists as charterers switch operators based on rate competitiveness
Inferred
Agent_Inference
headcount_cost_structure
Revenue growth is largely asset-linear not headcount-linear; adding vessels requires crew and ops staff but shore-based headcount grows sublinearly with fleet expansion
Inferred
Agent_Inference
marginal_cost_of_growth
Marginal growth cost dominated by vessel acquisition (~$60-120M per VLCC); operating leverage strong once fleet fixed costs covered; incremental crew costs modest
Inferred
Agent_Inference
franchise_compliance_risk
Not applicable; INSW is not a franchise business model
Inferred
Agent_Inference
customer_acquisition_metric
At 10x scale, CAC remains low as B2B charter relationships are broker-intermediated; unit economics improve with fleet scale via OpEx leverage and port cost negotiation
Inferred
Agent_Inference
network_effect_present
Weak network effects; larger fleet improves scheduling flexibility and charterer appeal but tanker shipping lacks true demand-side network effects
Inferred
Agent_Inference
asset_efficiency_ratio
11.6% Return on Assets (Excellent)
High
SEC-XBRL
recession_resistance_tier
Moderate resilience; crude tanker demand tied to global oil consumption which is relatively inelastic short-term, but rate collapse in recessions is severe (2020 example)
Inferred
Agent_Inference
customer_segment_primary
Major integrated oil companies and national oil companies (NOCs) such as Shell, BP, Aramco affiliates representing bulk of voyage charter demand
Inferred
Agent_Inference
customer_segment_secondary
Independent oil traders and commodity trading houses (Vitol, Trafigura, Glencore) representing significant spot market charter demand and concentration risk
Inferred
Agent_Inference
characteristic_occupations
["11-0000 Management Occupations", "13-0000 Business and Financial Operations Occupations", "15-0000 Computer and Mathematical Occupations", "17-0000 Architecture and Engineering Occupations", "19-0000 Life, Physical, and Social Science Occupations", "23-0000 Legal Occupations", "41-0000 Sales and Related Occupations", "43-0000 Office and Administrative Support Occupations", "47-0000 Construction and Extraction Occupations", "49-0000 Installation, Maintenance, and Repair Occupations", "53-0000 Transportation and Material Moving Occupations"]
High
SOC-2018/GICS-overlay
agent_automatable_labor_share
0.33 (HIL — ~33% of characteristic roles agent-automatable)
Medium
SOC-2018 + agentic-exposure-v1
capital_expenditure_profile
0.3% CapEx / Revenue (Low-CapEx Asset-Light)
High
SEC-XBRL
sec_cik
0001679049
High
SEC-EDGAR
ticker
INSW
High
SEC-EDGAR