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\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<\/script><script type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-mount\" 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auto;padding:0 16px;font-family:ui-sans-serif,system-ui,-apple-system,\"Segoe UI\",sans-serif;line-height:1.55;overflow-wrap:break-word}#nxe-nx6nx7c0.nxe :where(*,*::before,*::after){box-sizing:inherit}#nxe-nx6nx7c0.nxe :where(section,header,footer,nav,aside){display:block;margin:0 0 32px}#nxe-nx6nx7c0.nxe :where(h1,h2,h3,h4){line-height:1.2;margin:24px 0 12px;font-weight:600}#nxe-nx6nx7c0.nxe :where(p,ul,ol,dl,table,figure,details){margin:0 0 16px}#nxe-nx6nx7c0.nxe :where(ul,ol){padding-left:20px}#nxe-nx6nx7c0.nxe a{color:inherit;text-decoration:underline;text-underline-offset:2px}#nxe-nx6nx7c0.nxe table{border-collapse:collapse;width:100%;display:block;overflow-x:auto}#nxe-nx6nx7c0.nxe :where(th,td){padding:6px 8px;text-align:left;vertical-align:top;border-bottom:1px solid;border-color:inherit}#nxe-nx6nx7c0.nxe svg{display:none}#nxe-nx6nx7c0.nxe svg.nx-i{display:inline-block;width:18px;height:18px;vertical-align:-3px}#nxe-nx6nx7c0.nxe :where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-nx6nx7c0.nxe img{max-width:100%;height:auto}<\/style><svg class=\"nx-defs\" aria-hidden=\"true\" focusable=\"false\" width=\"0\" height=\"0\"><defs><linearGradient id=\"nx-gi\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-giu\" gradientUnits=\"userSpaceOnUse\" x1=\"0\" y1=\"0\" x2=\"800\" y2=\"0\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-gp\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gp-a\"\/><stop offset=\"1\" class=\"nx-gp-b\"\/><\/linearGradient><\/defs><\/svg><section class=\"nx-hero\" data-layout=\"console\" aria-labelledby=\"nx-title-1\"><div class=\"nx-container\"><div class=\"nx-theme-toggle\" role=\"group\" aria-label=\"Appearance of this page\" hidden><button type=\"button\" data-mode=\"light\" aria-pressed=\"false\">Light<\/button><button type=\"button\" data-mode=\"dark\" aria-pressed=\"false\">Dark<\/button><button type=\"button\" data-mode=\"auto\" aria-pressed=\"true\">Auto<\/button><\/div><div class=\"nx-folio\" aria-label=\"Document reference\"><strong>A-P02 \u00b7 TOPIC \u00b7 model-validation<\/strong>GRA dossier \u00b7 service level R0<\/div><div class=\"nx-hero-grid\"><div class=\"nx-hero-text\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">GRA<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">Reinsurance and Catastrophe<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">In development<\/span><\/div><div class=\"nx-accent-row\"><span class=\"nx-accent-rule\" aria-hidden=\"true\"><\/span><span>Topic dossier \u00b7 Reinsurance and Catastrophe<\/span><\/div><h1 id=\"nx-title-1\" class=\"nx-hero-title\">Model validation<\/h1><p class=\"nx-tagline\">Catastrophe models inform capital, price and rating decisions, so they must be shown fit for purpose. Validation tests each module against observations, compares models, challenges assumptions and documents limits. Supervisors, rating agencies and professional standards set expectations. This page sets out how catastrophe model validation works and where it falls short, the evidence it uses, and who decides.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/contact\/\">Make an enquiry <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/topics\/\">Back to Topics<\/a><\/div><\/div><div class=\"nx-hero-panel\"><div class=\"nx-register\"><div class=\"nx-register-head\"><span class=\"nx-eyebrow\"><strong>Dossier<\/strong><\/span><span class=\"nx-eyebrow\">A-P02 \u00b7 topic<\/span><\/div><ol class=\"nx-register-rows\"><li><a href=\"#nx-sec-brief-answer\"><span class=\"nx-register-n\">01<\/span><span class=\"nx-register-k\">In brief<\/span><span class=\"nx-register-v\">Definition and scope<\/span><\/a><\/li><li><a href=\"#nx-sec-question\"><span class=\"nx-register-n\">02<\/span><span class=\"nx-register-k\">The question<\/span><span class=\"nx-register-v\">4 mechanisms<\/span><\/a><\/li><li><a href=\"#nx-sec-terms\"><span class=\"nx-register-n\">03<\/span><span class=\"nx-register-k\">Key terms<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">3<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-field\"><span class=\"nx-register-n\">04<\/span><span class=\"nx-register-k\">Field<\/span><span class=\"nx-register-v\">H3 field plate<\/span><\/a><\/li><li><a href=\"#nx-sec-indicators\"><span class=\"nx-register-n\">05<\/span><span class=\"nx-register-k\">Indicators<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">6<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-pipeline\"><span class=\"nx-register-n\">06<\/span><span class=\"nx-register-k\">Pipeline<\/span><span class=\"nx-register-v\">Run graph<\/span><\/a><\/li><li><a href=\"#nx-sec-sources\"><span class=\"nx-register-n\">07<\/span><span class=\"nx-register-k\">Sources<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">5<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-decisions\"><span class=\"nx-register-n\">08<\/span><span class=\"nx-register-k\">Decision holders<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">4<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-methods\"><span class=\"nx-register-n\">09<\/span><span class=\"nx-register-k\">Methods<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">4<\/span><\/span><\/a><\/li><\/ol><p class=\"nx-register-foot\">GRA \u00b7 In development \u00b7 service level R0<\/p><\/div><\/div><\/div><\/div><\/section> <nav class=\"nx-index-strip\" data-nx-spy=\"true\" aria-label=\"On this page\"><div class=\"nx-container\"><a href=\"#nx-sec-brief-answer\"><span>01<\/span>The short answer<\/a><a href=\"#nx-sec-field\"><span>02<\/span>Exposure, hazard and the exceedance\u2026<\/a><a href=\"#nx-sec-question\"><span>03<\/span>Model validation: how the risk\u2026<\/a><a href=\"#nx-sec-terms\"><span>04<\/span>Terms used on this page<\/a><a href=\"#nx-sec-indicators\"><span>05<\/span>What is measured, and how well<\/a><a href=\"#nx-sec-pipeline\"><span>06<\/span>From sources to decisions<\/a><a href=\"#nx-sec-sources\"><span>07<\/span>Where the evidence comes from<\/a><a href=\"#nx-sec-decisions\"><span>08<\/span>Who decides, and what the evidence\u2026<\/a><\/div><\/nav> <section id=\"nx-sec-brief-answer\" class=\"nx-section\" data-hue=\"finance\" aria-labelledby=\"nx-s-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">01<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">In brief<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">The short answer.<\/h2><p class=\"nx-lede\">Catastrophe model validation is the process of showing that a model is fit for its intended use by testing modules against observations, comparing models, challenging assumptions and documenting limits. Validation functions, boards, supervisors and public commissions decide whether a model may inform capital and rates.<\/p><\/div><\/div><\/section><section id=\"nx-sec-field\" class=\"nx-section\" data-hue=\"climate\" data-tone=\"alt\" aria-labelledby=\"nx-s-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Spatial finance<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">Exposure, hazard and the exceedance curve.<\/h2><p class=\"nx-lede\">Which places drive loss in a severe year, and how far it reaches into reinsurance. Illustrative design values.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><figure class=\"nx-fk nx-sf\" data-fk=\"cat-ep\" data-gl=\"sf:cat-ep\" data-sf=\"cat-ep\" data-sx-credit=\"Natural Earth (public domain) | design event set, not a model output\" data-sx-src=\"Natural Earth ~ public domain ~ https:\/\/www.naturalearthdata.com\/ | Design scenario values by the Global Risks Alliance ~ illustrative, not data\" data-sf-learn-views=\"ep\" aria-label=\"Interactive map: coastal exposure under cyclone basins and earthquake belts, linked to a loss exceedance curve. Choosing a return period on the curve marks the places that lose at it.\" 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\"><figcaption class=\"nx-fk-cap\"><span>Coastal exposure under cyclone and earthquake zones, beside the loss curve it produces.<\/span><span data-honesty=\"true\">Illustrative design values, not a model output or a price.<\/span><\/figcaption><\/figure><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"map\" data-nxf-kind=\"map\" data-nxf-resource=\"nexus:\/\/gra\/A-P02\/topics\/model-validation\/#map\" data-nxf-title=\"Reinsurance and Catastrophe live map\" data-nxf-height=\"560\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-question\" class=\"nx-section\" data-hue=\"systemic\" data-variant=\"split\" aria-labelledby=\"nx-s-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">The question<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">Model validation: how the risk develops.<\/h2><p class=\"nx-lede\">Uncertainty, sensitivity and benchmarks. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-cells\" data-cols=\"2\"><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3.85 8.62a4 4 0 0 1 4.78-4.77 4 4 0 0 1 6.74 0 4 4 0 0 1 4.78 4.78 4 4 0 0 1 0 6.74 4 4 0 0 1-4.77 4.78 4 4 0 0 1-6.75 0 4 4 0 0 1-4.78-4.77 4 4 0 0 1 0-6.76Z\"\/><path d=\"m9 12 2 2 4-4\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Module-by-module testing<\/h3><p class=\"nx-p nx-mt-1\">Hazard is compared with observed event statistics, vulnerability with claims, and the full model with historical losses. Each test covers part of the model, not all of it.<\/p><\/div><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"m12.83 2.18a2 2 0 0 0-1.66 0L2.6 6.08a1 1 0 0 0 0 1.83l8.58 3.91a2 2 0 0 0 1.66 0l8.58-3.9a1 1 0 0 0 0-1.83Z\"\/><path d=\"m22 17.65-9.17 4.16a2 2 0 0 1-1.66 0L2 17.65\"\/><path d=\"m22 12.65-9.17 4.16a2 2 0 0 1-1.66 0L2 12.65\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Short records limit tests<\/h3><p class=\"nx-p nx-mt-1\">Rare events cannot be validated against long loss histories. Validation relies on scientific plausibility and expert judgement for the tail.<\/p><\/div><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M2 12s3-7 10-7 10 7 10 7-3 7-10 7-10-7-10-7Z\"\/><circle cx=\"12\" cy=\"12\" r=\"3\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Independence matters<\/h3><p class=\"nx-p nx-mt-1\">Validation by the team that adopted the model is weaker than independent challenge. Governance separates development, adoption and validation.<\/p><\/div><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"3\"\/><circle cx=\"19\" cy=\"5\" r=\"2\"\/><circle cx=\"5\" cy=\"19\" r=\"2\"\/><path d=\"M10.4 21.9a10 10 0 0 0 9.941-15.416\"\/><path d=\"M13.5 2.1a10 10 0 0 0-9.841 15.416\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Model change shocks results<\/h3><p class=\"nx-p nx-mt-1\">Vendor updates can shift results sharply. Change management assesses why results moved and whether the new view is adopted.<\/p><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-terms\" class=\"nx-section\" data-hue=\"finance\" data-tone=\"alt\" data-variant=\"stack\" aria-labelledby=\"nx-s-5\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">04<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Key terms<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">Terms used on this page.<\/h2><p class=\"nx-lede\">Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Term<\/th><th scope=\"col\">Definition<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Term\">Model validation<\/td><td data-label=\"Definition\">Independent testing that a model performs as intended and is fit for a stated use.<\/td><\/tr><tr><td data-label=\"Term\">Change analysis<\/td><td data-label=\"Definition\">Explaining how and why a new model version changes results.<\/td><\/tr><tr><td data-label=\"Term\">Independent challenge<\/td><td data-label=\"Definition\">Review of a model by people not involved in developing or adopting it.<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-indicators\" class=\"nx-section\" data-hue=\"climate\" aria-labelledby=\"nx-s-6\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Indicators<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">What is measured, and how well.<\/h2><p class=\"nx-lede\">Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.<\/p><\/div><div class=\"nx-section-body\" data-lv=\"register\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Indicator<\/th><th scope=\"col\">Unit<\/th><th scope=\"col\">Cadence<\/th><th scope=\"col\">Source type<\/th><th scope=\"col\">Label<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Indicator\">Modelled versus historical loss for past events<\/td><td data-label=\"Unit\">ratio<\/td><td data-label=\"Cadence\">per validation<\/td><td data-label=\"Source type\">Validation reports<\/td><td data-label=\"Label\"><span class=\"nx-chip\">MODELLED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Change in results from model version updates<\/td><td data-label=\"Unit\">percent change in key metrics<\/td><td data-label=\"Cadence\">per update<\/td><td data-label=\"Source type\">Change analysis<\/td><td data-label=\"Label\"><span class=\"nx-chip\">MODELLED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Independent validation completed<\/td><td data-label=\"Unit\">yes or no, by model<\/td><td data-label=\"Cadence\">annual<\/td><td data-label=\"Source type\">Governance records<\/td><td data-label=\"Label\"><span class=\"nx-chip\">DECLARED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Internal models approved by supervisors<\/td><td data-label=\"Unit\">count<\/td><td data-label=\"Cadence\">annual<\/td><td data-label=\"Source type\">Supervisor records<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OFFICIAL<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Validation findings outstanding<\/td><td data-label=\"Unit\">count by severity<\/td><td data-label=\"Cadence\">periodic<\/td><td data-label=\"Source type\">Validation records<\/td><td data-label=\"Label\"><span class=\"nx-chip\">DECLARED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Public model reviews completed<\/td><td data-label=\"Unit\">count<\/td><td data-label=\"Cadence\">annual<\/td><td data-label=\"Source type\">Public commissions<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OFFICIAL<\/span><\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"indicators\" data-nxf-kind=\"indicator\" data-nxf-resource=\"nexus:\/\/gra\/A-P02\/topics\/model-validation\/#indicators\" data-nxf-title=\"Indicators\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-pipeline\" class=\"nx-section\" data-hue=\"systemic\" data-tone=\"alt\" aria-labelledby=\"nx-s-7\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Canvas<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">From sources to decisions.<\/h2><p class=\"nx-lede\">The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-plate\" data-wide=\"true\"><div class=\"nx-plate-label\"><span class=\"nx-eyebrow\"><strong>Pipeline canvas<\/strong> \u00b7 Model validation as a run graph<\/span><span class=\"nx-eyebrow\">Design, not a record<\/span><\/div><div class=\"nx-figure-frame\" data-scene=\"true\"><svg class=\"nx-figure nx-ui nx-dag\" viewBox=\"0 0 1200 564\" data-nx-dag=\"true\" data-w=\"1200\" data-h=\"564\" role=\"img\" aria-labelledby=\"nx-dag-a-p02-topics-model-validation-catmodel-t nx-dag-a-p02-topics-model-validation-catmodel-d\" data-nx-z=\"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\"><title id=\"nx-dag-a-p02-topics-model-validation-catmodel-t\">Model validation: catastrophe model pipeline<\/title><desc id=\"nx-dag-a-p02-topics-model-validation-catmodel-d\">A stochastic event catalogue drives the hazard module; exposure and vulnerability turn intensity into damage; the financial module applies policy terms; event and year loss tables give exceedance curves, PML and TVaR. Design of the process, not a record of a run.<\/desc><\/svg><\/div><\/div><p class=\"nx-caption\"><strong>Fig. 02<\/strong><span>Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.<\/span><\/p><\/div><\/div><\/section><section id=\"nx-sec-sources\" class=\"nx-section\" data-hue=\"finance\" data-variant=\"stack\" aria-labelledby=\"nx-s-8\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Sources<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">Where the evidence comes from.<\/h2><p class=\"nx-lede\">Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.<\/p><\/div><div class=\"nx-section-body\" data-lv=\"register\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Source<\/th><th scope=\"col\">What it gives<\/th><th scope=\"col\">Licence class<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Source\">Florida Commission on Hurricane Loss Projection Methodology standards and reports<\/td><td data-label=\"What it gives\">Public standards and acceptance reviews for hurricane and flood models<\/td><td data-label=\"Licence class\">Public records<\/td><\/tr><tr><td data-label=\"Source\">EIOPA and PRA guidance on internal model use and validation<\/td><td data-label=\"What it gives\">Supervisory expectations for model validation<\/td><td data-label=\"Licence class\">Free, EU and Bank of England terms<\/td><\/tr><tr><td data-label=\"Source\">Lloyd's catastrophe modelling guidance and minimum standards<\/td><td data-label=\"What it gives\">Validation and governance expectations for managing agents<\/td><td data-label=\"Licence class\">Free to read, Lloyd's terms<\/td><\/tr><tr><td data-label=\"Source\">Actuarial Standards Board ASOP on catastrophe modeling<\/td><td data-label=\"What it gives\">Professional standards for using models<\/td><td data-label=\"Licence class\">Free, ASB terms<\/td><\/tr><tr><td data-label=\"Source\">Oasis LMF model documentation<\/td><td data-label=\"What it gives\">Open model documentation enabling comparison<\/td><td data-label=\"Licence class\">Open source, terms per model<\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gra\/A-P02\/topics\/model-validation\/#evidence\" data-nxf-title=\"Sources\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-decisions\" class=\"nx-section\" data-hue=\"climate\" data-tone=\"alt\" aria-labelledby=\"nx-s-9\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Decisions<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Who decides, and what the evidence serves.<\/h2><p class=\"nx-lede\">Reinsurance and Catastrophe prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Who decides<\/th><th scope=\"col\">The question<\/th><th scope=\"col\">Evidence this page serves<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Who decides\">Model validation functions<\/td><td data-label=\"The question\">Whether a model is fit for each intended use<\/td><td data-label=\"Evidence this page serves\">Test results, comparisons and documented limits<\/td><\/tr><tr><td data-label=\"Who decides\">Boards and risk committees<\/td><td data-label=\"The question\">Whether to adopt a model or version as the company view<\/td><td data-label=\"Evidence this page serves\">Validation findings and change analysis<\/td><\/tr><tr><td data-label=\"Who decides\">Supervisors<\/td><td data-label=\"The question\">Whether to approve internal models for capital<\/td><td data-label=\"Evidence this page serves\">Validation and governance evidence<\/td><\/tr><tr><td data-label=\"Who decides\">Public model commissions<\/td><td data-label=\"The question\">Whether models meet standards for rate filings<\/td><td data-label=\"Evidence this page serves\">Model submissions and review findings<\/td><\/tr><\/tbody><\/table><\/div><h3 class=\"nx-h4 nx-mt-4\">Outputs this topic produces<\/h3><ul class=\"nx-list\"><li>Guide to validating each catastrophe model module<\/li><li>Method note on model change analysis<\/li><li>Brief on independent challenge and governance<\/li><li>Questions for boards approving a model view<\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-core-questions\" class=\"nx-section\" data-hue=\"systemic\" data-variant=\"split\" aria-labelledby=\"nx-s-10\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Core questions<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">What experts ask about validation.<\/h2><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\"><li>Do the hazard, vulnerability and financial modules reflect current scientific understanding?<\/li><li>How do modelled losses compare with observed losses from past events?<\/li><li>Which assumptions drive the results most strongly?<\/li><li>How do results compare across different models for the same portfolio?<\/li><li>How should model uncertainty be communicated to decision-makers?<\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-mechanisms-and-drivers\" class=\"nx-section\" data-hue=\"finance\" data-tone=\"alt\" data-variant=\"stack\" aria-labelledby=\"nx-s-11\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">10<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Mechanisms and drivers<\/span><\/div><h2 id=\"nx-s-11\" class=\"nx-section-title\">Why validation is difficult.<\/h2><\/div><div class=\"nx-section-body\"><p class=\"nx-p\">The events that matter most are the rarest, so there are few observations against which to test tail estimates. A model may match recent losses well but misestimate the tail. Validation must therefore test components separately, against hazard records, engineering studies and claims, as well as the model as a whole.<\/p><p class=\"nx-p\">Sensitivity analysis shows which assumptions matter. Small changes in vulnerability functions, event frequencies or exposure data can change loss estimates significantly. Understanding these sensitivities is essential for using models responsibly.<\/p><p class=\"nx-p\">Comparing models helps reveal structural uncertainty: if independently built models disagree, the disagreement indicates how uncertain the estimate is.<\/p><\/div><\/div><\/section><section id=\"nx-sec-methods-and-data\" class=\"nx-section\" data-hue=\"climate\" aria-labelledby=\"nx-s-12\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">11<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods and data<\/span><\/div><h2 id=\"nx-s-12\" class=\"nx-section-title\">Methods and their limits.<\/h2><\/div><div class=\"nx-section-body\"><ol class=\"nx-rows\"><li><span class=\"nx-eyebrow nx-index\">01<\/span><div><h3 class=\"nx-h4\">Component validation<\/h3><p class=\"nx-p nx-mt-1\">Testing modules against independent evidence, using <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/uncertainty-quantification\/\">uncertainty quantification and model validation<\/a>.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">02<\/span><div><h3 class=\"nx-h4\">Historical loss comparison<\/h3><p class=\"nx-p nx-mt-1\">Comparing modelled and observed losses for past events. Exposure changes complicate comparison.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">03<\/span><div><h3 class=\"nx-h4\">Sensitivity analysis<\/h3><p class=\"nx-p nx-mt-1\">Varying key assumptions systematically. Interactions between assumptions can be complex.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">04<\/span><div><h3 class=\"nx-h4\">Model intercomparison<\/h3><p class=\"nx-p nx-mt-1\">Comparing outputs of different models on common portfolios. Requires shared, consistent inputs.<\/p><\/div><\/li><\/ol><p class=\"nx-note nx-mt-3\">Validation reduces but cannot remove model uncertainty. It is an ongoing process, repeated as models and science change.<\/p><\/div><\/div><\/section><section id=\"nx-sec-methods\" class=\"nx-section\" data-hue=\"systemic\" data-tone=\"alt\" aria-labelledby=\"nx-s-13\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">12<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods<\/span><\/div><h2 id=\"nx-s-13\" class=\"nx-section-title\">How it is studied, and what the methods cannot say.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-methods\" data-limits=\"true\"><ol class=\"nx-mledger\" aria-label=\"Methods\"><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/stem\/uncertainty-quantification\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">01<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Uncertainty quantification and model validation<\/span><span class=\"nx-mledger-role\">Primary and secondary uncertainty \u00b7 Sensitivity ranking \u00b7 Multi-model ensembles<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/uncertainty-quantification\/\" aria-label=\"Uncertainty quantification and model validation: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/stem\/extreme-value\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">02<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Extreme value theory and tail risk<\/span><span class=\"nx-mledger-role\">Pricing high excess layers \u00b7 Hazard return levels \u00b7 Tail dependence between perils<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/extreme-value\/\" aria-label=\"Extreme value theory and tail risk: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/stem\/structural-engineering\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">03<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Structural and earthquake engineering<\/span><span class=\"nx-mledger-role\">Vulnerability by construction class \u00b7 Building code effectiveness \u00b7 Post-event damage surveys<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/engineering\/structural-engineering\/\" aria-label=\"Structural and earthquake engineering: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/stem\/geoscience\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">04<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Earth and geophysical science<\/span><span class=\"nx-mledger-role\">Seismic source models \u00b7 Ground motion and site effects \u00b7 Secondary hazards<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/science\/geoscience\/\" aria-label=\"Earth and geophysical science: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><\/ol><aside class=\"nx-limits\" aria-label=\"What the methods cannot say\"><span class=\"nx-eyebrow\">What the methods cannot say<\/span><p class=\"nx-limits-text\">Tail behaviour cannot be validated against observed losses, so judgement remains central. Model documentation from vendors is partly confidential. Validation standards differ by regulator and by intended use, so a model accepted for one purpose may not be fit for another. Reinsurance and Catastrophe explains validation methods; it does not validate or endorse any model.<\/p><\/aside><\/div><\/div><\/div><\/section><section id=\"nx-s-14-sec\" class=\"nx-section\" data-hue=\"finance\" aria-labelledby=\"nx-s-14\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">13<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Questions<\/span><\/div><h2 id=\"nx-s-14\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>Can a catastrophe model be validated against history?<\/summary><div class=\"nx-answer\">Partly. Hazard and vulnerability can be tested against observed events and claims, but rare tail losses have too few observations, so plausibility and expert challenge fill the gap.<\/div><\/details><details><summary>Why do model updates move results?<\/summary><div class=\"nx-answer\">New science, data and methods change hazard or vulnerability. Change analysis explains which component moved results and why.<\/div><\/details><details><summary>Who reviews catastrophe models publicly?<\/summary><div class=\"nx-answer\">Some bodies, such as the Florida Commission on Hurricane Loss Projection Methodology, review models against published standards before they may support rate filings.<\/div><\/details><details><summary>Does the platform validate models?<\/summary><div class=\"nx-answer\">No. It studies validation methods. Validation of specific models is carried out by their users and reviewed by supervisors.<\/div><\/details><details><summary>Why compare models?<\/summary><div class=\"nx-answer\">Because disagreement between independent models reveals structural uncertainty that a single model cannot show.<\/div><\/details><details><summary>Can a model be fully validated?<\/summary><div class=\"nx-answer\">No. Validation builds confidence for a purpose, but rare-event estimates always carry uncertainty.<\/div><\/details><details><summary>Does the Nexus Universe exercise compare models?<\/summary><div class=\"nx-answer\">A model comparison exercise for a hazard season is designed, described on the platform's <a class=\"nx-link\" href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/universe\/\">Universe page<\/a>.<\/div><\/details><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-tone=\"alt\" aria-labelledby=\"nx-rel-15\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Related<\/span><h2 id=\"nx-rel-15\" class=\"nx-h3 nx-mt-2\">Around Reinsurance and Catastrophe.<\/h2><nav class=\"nx-related nx-mt-3\" aria-label=\"Related\"><a href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/topics\/reinsurance-structures\/\">Reinsurance structures <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/topics\/catastrophe-models\/\">Catastrophe models <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/topics\/aggregate-accumulation\/\">Aggregate accumulation <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/topics\/protection-gaps\/\">Protection gaps <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/topics\/climate-and-natcat\/\">Climate and natcat <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/topics\/retrocession-and-capital\/\">Retrocession and capital <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/\">Reinsurance and Catastrophe home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/counterparts\/\">Counterparts across the Consortium <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/\">The Global Risks Alliance home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/trust\/\">GRA governance and trust <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/nav><\/div><\/section><section class=\"nx-closing\" aria-labelledby=\"nx-close-16\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Reinsurance and Catastrophe<\/span><h2 id=\"nx-close-16\" class=\"nx-section-title\">Bring your expertise to this field.<\/h2><p class=\"nx-lede\">The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"mailto:contact@globalriskalliance.com?subject=Reinsurance%20and%20Catastrophe%3A%20Model%20validation\">Write to the team <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/contact\/\">See all contact routes<\/a><\/div><\/div><\/section><\/div><\/div><script class=\"_iub_cs_skip\">window.__nxMount ? window.__nxMount(document.currentScript) : null;<\/script>\n\n\n<script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"FAQPage\",\"@id\":\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/topics\/model-validation\/#faq\",\"isPartOf\":{\"@id\":\"https:\/\/globalriskalliance.com\/reinsurance-catastrophe\/topics\/model-validation\/#webpage\"},\"inLanguage\":\"en\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"Can a catastrophe model be validated against history?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Partly. 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