The ZIP also includes full_hazard.parquet (conflict onset × draw, with severity shocks), full_net_losses.parquet (location × draw × policy layer, through the loss waterfall), and full_assets.parquet (asset × draw, with shocked values). These unaggregated files can be large; JSON responses contain summaries only.
conflict_summary.csv
Per-country hazard summary
One row per country (iso3 code). Columns include conflicts_simulated, conflicts_simulated_ratio (share of simulations with a conflict), conditional and unconditional means of deaths, damage, GDP / inflation / equity / bond shocks, and percentile columns (p01, p05, p50, p95, p99) for damage and each market shock.
inventory_summary.csv
Per-property loss summary
One row per property (inventory_id). Columns: property identifiers (property_name_or_address, policy_id, iso3, country, property_value), hit statistics (number_of_hits, hit_frequency, subthreshold_hit_percentage), ground-up fields (expected_ground_up_loss, ground_up_tvar_95, ground_up_tvar_99, ground_up_max_loss), and the insured, insurer, and reinsurer expected-loss and tail metrics. Ground-up loss is total property damage before any insurance. Each layer also includes an expected loss ratio.
assets_summary.csv
Per-asset investment impact
One row per asset (asset_id). Columns: asset_class, instrument_type, original_value, expected_loss, max_loss, tvar_95, tvar_99, expected_shocked_value, expected_loss_ratio. The expected_loss fields represent signed value impact: a negative loss means the investment is expected to grow. Per-asset VaR is deliberately not reported; portfolio-level VaR is in portfolio_summary.csv.
portfolio_summary.csv
Whole-book loss metrics
One row per view (layer column): each inventory layer alone (ground_up, insured, insurer, reinsurer), assets alone, and each layer combined with assets (ground_up_plus_assets, etc.). Layers that don't apply to your request are omitted. Columns: layer, expected_loss, var_95, var_99, tvar_95, tvar_99, max_loss, total_value (total USD book value of the view). Tail metrics are computed by summing losses within each simulated year first, so combined views are not simply the sum of their parts.
portfolio_waterfall.csv
Total-damage-to-net portfolio waterfall
One row per stage, in order: ground_up_loss, insurance_recovery, insured_net_loss, reinsurance_recovery, reinstatement_premiums, insurer_net_loss. Stages that do not apply are omitted. Columns: stage, expected_annual_loss, pct_of_ground_up, and description. Insurance applies coinsurance, deductible/attachment, occurrence limit, then participation; reinsurance follows the insurer’s gross share.
country_contributions.csv
Country tail-risk contributions
One row per country: expected_ground_up_loss, expected_insurer_net_loss, expected_asset_loss, expected_total_loss, tvar_95_contribution, tvar_99_contribution, and share_of_tvar_95. Co-TVaR is the country’s average loss in the portfolio’s worst 5% or 1% of simulated years. Contributions sum to portfolio TVaR; standalone country TVaRs do not.
top_locations.csv
Top property locations
The ten locations with the largest expected_ground_up_loss, including property value, hit frequency, subthreshold_hit_percentage, loss ratio, insured expected loss, and insurer expected loss.
policy_summary.csv
Per-policy loss trace
Only when policies are supplied. One row per layer: expected_ground_up_loss, expected_after_coinsurance, expected_layer_loss, expected_insurer_gross, expected_ri_recovery, expected_reinstatement_premium, expected_insurer_net_loss, insurer_net_tvar_95/99, insurer_net_max_loss, attachment_breaches, attachment_breach_frequency, n_properties, driving_country, and driving_country_share.
top_policies.csv
Top policy layers
When policies are supplied, the ten layers with the largest expected insurer net loss, including insurer, property count, driving country, attachment breach frequency, RI recovery, net loss, and TVaR 99.