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:where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n1fhamb6.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-scene nx-es-scene\" data-scene=\"text\" data-ground=\"none\" data-es-org=\"gra\" aria-labelledby=\"nx-scene-title\"><div class=\"nx-scene-intro nx-es-intro\"><p class=\"nx-eyebrow\"><abbr title=\"The Global Risks Alliance\">GRA<\/abbr> \u00b7 AI and Financial Model Risk<\/p><span class=\"nx-scene-rule\" aria-hidden=\"true\"><\/span><p class=\"nx-scene-accent nx-es-sig\"><strong>Spatial finance<\/strong><span>Where capital meets hazard, exposure and transition<\/span><\/p><h1 id=\"nx-scene-title\" class=\"nx-scene-title\">STEM foundation of AI and Financial Model Risk<\/h1><p class=\"nx-scene-lede\">The science, technology, engineering and mathematics AI and Financial <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 model-risk\" data-tk=\"Nexus risk vocabulary\" data-td=\"Risk of harm from decisions based on models that are wrong, misused or applied outside their validity domain.\" data-ts=\"NRS-C1\" data-tr=\"draft\">Model Risk<\/a> rests on. Each method has a canonical page in the STEM Commons, hosted by the Global Centre for Risk and Innovation (GCRI), and a page here on how it is applied in this field.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/ai-ml\/\">Open Artificial intelligence and machine learning for AI and financial model risk <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/\">Back to AI and Financial Model Risk<\/a><\/div><\/div><\/section><section id=\"nx-s-1-sec\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" aria-labelledby=\"nx-s-1\"><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\">Register<\/span><\/div><h2 id=\"nx-s-1\" class=\"nx-section-title\">Four pages under STEM foundation of AI and Financial Model Risk.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-es-fig\" data-es-layout=\"ledger\"><div class=\"nx-hero-panel\"><div class=\"nx-register\" data-variant=\"ledger\"><div class=\"nx-register-head\"><span class=\"nx-eyebrow\"><strong>AI and Financial Model Risk<\/strong><\/span><\/div><ol class=\"nx-register-rows\"><li><a href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/ai-ml\/\"><span class=\"nx-register-n\">01<\/span><span class=\"nx-register-k\">Method<\/span><span class=\"nx-register-v\">Artificial intelligence and machine learning for AI and financial model risk<\/span><\/a><\/li><li><a href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/ai-assurance\/\"><span class=\"nx-register-n\">02<\/span><span class=\"nx-register-k\">Method<\/span><span class=\"nx-register-v\">AI evaluation and assurance engineering for AI and financial model risk<\/span><\/a><\/li><li><a href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/uncertainty-quantification\/\"><span class=\"nx-register-n\">03<\/span><span class=\"nx-register-k\">Method<\/span><span class=\"nx-register-v\">Uncertainty quantification and model validation at AI and Financial Model Risk<\/span><\/a><\/li><li><a href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/probability-statistics\/\"><span class=\"nx-register-n\">04<\/span><span class=\"nx-register-k\">Method<\/span><span class=\"nx-register-v\">Probability and statistics for AI and financial model risk<\/span><\/a><\/li><\/ol><\/div><\/div><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-band=\"auto\" data-band-id=\"nx-band-1\" data-hue=\"finance\" aria-label=\"Methods, Methods, Why it matters\"><div class=\"nx-container\"><div class=\"nx-hm-band nx-band\" data-nx-tabs=\"true\" data-active=\"p1\"><div class=\"nx-tablist nx-hm-tabs\" role=\"tablist\" aria-label=\"Methods, Methods, Why it matters\"><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-1\" aria-controls=\"nx-sec-methods\" aria-selected=\"true\" data-key=\"p1\">Methods<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-2\" aria-controls=\"nx-sec-pg-nx-gra-a-p07-st\" aria-selected=\"false\" data-key=\"p2\">Methods<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-3\" aria-controls=\"nx-sec-why-it-matters\" aria-selected=\"false\" data-key=\"p3\">Why it matters<\/button><\/div><section id=\"nx-sec-methods\" class=\"nx-section nx-band-panel\" data-hue=\"finance\" aria-labelledby=\"nx-s-2\" role=\"tabpanel\" data-band-tab=\"nx-band-1-tab-1\"><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\">Methods<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">The methods behind the field.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-methods\"><ol class=\"nx-mledger\" aria-label=\"Methods\"><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/ai-ml\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">01<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Artificial intelligence and machine learning<\/span><span class=\"nx-mledger-role\">Gradient-boosted credit models \u00b7 Language models in operations \u00b7 Anomaly detection<\/span><span class=\"nx-mledger-meta\">Steward \u00b7 Artificial Intelligence and Autonomous Systems<\/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\"><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\/technology\/ai-ml\/\" aria-label=\"Canonical \u00b7 STEM Commons: Artificial intelligence and machine learning\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/ai-assurance\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">02<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">AI evaluation and assurance engineering<\/span><span class=\"nx-mledger-role\">Validation of machine learning models \u00b7 Red-teaming generative AI \u00b7 Fairness assessment<\/span><span class=\"nx-mledger-meta\">Steward \u00b7 Artificial Intelligence and Autonomous Systems<\/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\"><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\/ai-assurance\/\" aria-label=\"Canonical \u00b7 STEM Commons: AI evaluation and assurance engineering\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/uncertainty-quantification\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">03<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Uncertainty quantification and model validation<\/span><span class=\"nx-mledger-role\">Prediction intervals for loss models \u00b7 Model ensembles \u00b7 Model risk capital or buffers<\/span><span class=\"nx-mledger-meta\">Steward \u00b7 Systems Science and Modelling<\/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\"><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=\"Canonical \u00b7 STEM Commons: Uncertainty quantification and model validation\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/probability-statistics\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">04<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Probability and statistics<\/span><span class=\"nx-mledger-role\">Calibration testing \u00b7 Drift statistics \u00b7 Group outcome comparison<\/span><span class=\"nx-mledger-meta\">Steward \u00b7 Systems Science and Modelling<\/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\"><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\/probability-statistics\/\" aria-label=\"Canonical \u00b7 STEM Commons: Probability and statistics\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><\/ol><\/div><\/div><\/div><\/section><section id=\"nx-sec-pg-nx-gra-a-p07-st\" class=\"nx-section nx-band-panel\" data-hue=\"project\" aria-labelledby=\"nx-s-3\" role=\"tabpanel\" data-band-tab=\"nx-band-1-tab-2\"><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 STEM methods AI<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">The STEM methods AI and Financial Model Risk applies, and why.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><ul class=\"nx-dir\" data-cols=\"2\" aria-label=\"Method\"><li><a class=\"nx-dir-row\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/ai-ml\/\"><span class=\"nx-dir-name\">Machine learning in financial models<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role in AI and Financial Model Risk<\/span><span class=\"nx-dir-v\">Artificial intelligence and machine learning are methods that learn patterns from data to predict, classify or generate.<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/ai-assurance\/\"><span class=\"nx-dir-name\">AI assurance for financial models<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role in AI and Financial Model Risk<\/span><span class=\"nx-dir-v\">AI assurance is the set of practices that give justified confidence in an AI or model system: validation, testing, red-teaming, monitoring, documentation and independent review.<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/uncertainty-quantification\/\"><span class=\"nx-dir-name\">Uncertainty in financial models<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role in AI and Financial Model Risk<\/span><span class=\"nx-dir-v\">Uncertainty quantification estimates how far a model&#8217;s output could be wrong, from data, parameters, structure and use.<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/probability-statistics\/\"><span class=\"nx-dir-name\">Statistics for model performance testing<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role in AI and Financial Model Risk<\/span><span class=\"nx-dir-v\">Probability and statistics underpin financial models: estimating default and claim rates, testing calibration, measuring discrimination and detecting drift.<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><p class=\"nx-p\">Each AI and Financial <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 model-risk\" data-tk=\"Nexus risk vocabulary\" data-td=\"Risk of harm from decisions based on models that are wrong, misused or applied outside their validity domain.\" data-ts=\"NRS-C1\" data-tr=\"draft\">Model Risk<\/a> method is described once in the STEM Commons at GCRI and applied here to model and AI risk.<\/p><\/div><\/div><\/section><section id=\"nx-sec-why-it-matters\" class=\"nx-section nx-band-panel\" data-hue=\"finance\" data-variant=\"stack\" aria-labelledby=\"nx-s-4\" role=\"tabpanel\" data-band-tab=\"nx-band-1-tab-3\"><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\">Why it matters<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">Grounding makes claims checkable.<\/h2><p class=\"nx-lede\">When a finding names the methods it depends on, a reader can see its assumptions and limits, and an expert in that method can challenge it.<\/p><\/div><\/div><\/section><\/div><\/div><\/section><section class=\"nx-section\" data-band=\"auto\" data-band-id=\"nx-band-2\" data-tone=\"alt\" data-hue=\"project\" aria-label=\"Sources, Pages, Questions\"><div class=\"nx-container\"><div class=\"nx-hm-band nx-band\" data-nx-tabs=\"true\" data-active=\"p1\"><div class=\"nx-tablist nx-hm-tabs\" role=\"tablist\" aria-label=\"Sources, Pages, Questions\"><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-1\" aria-controls=\"nx-sec-pg-sources\" aria-selected=\"true\" data-key=\"p1\">Sources<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-2\" aria-controls=\"nx-s-6-sec\" aria-selected=\"false\" data-key=\"p2\">Pages<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-3\" aria-controls=\"nx-s-7-sec\" aria-selected=\"false\" data-key=\"p3\">Questions<\/button><\/div><section id=\"nx-sec-pg-sources\" class=\"nx-section nx-band-panel\" data-hue=\"project\" data-variant=\"stack\" aria-labelledby=\"nx-s-5\" role=\"tabpanel\" data-band-tab=\"nx-band-2-tab-1\"><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\">Sources<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">Where this page&#8217;s references lead.<\/h2><p class=\"nx-lede\">The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.<\/p><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\" data-nav=\"true\"><li><a class=\"nx-link\" href=\"https:\/\/www.federalreserve.gov\/supervisionreg\/srletters.htm\"><span>US interagency revised guidance on model risk management, SR 26-2 (April 2026), superseding SR 11-7<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/www.bankofengland.co.uk\/prudential-regulation\/publication\/2023\/may\/model-risk-management-principles-for-banks-ss\"><span>PRA SS1\/23 Model risk management principles for banks<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/eur-lex.europa.eu\/eli\/reg\/2024\/1689\/oj\"><span>EU AI Act (Regulation 2024\/1689) as amended by the AI Omnibus, Regulation 2026\/1744 (credit-scoring high-risk duties from 2 December 2027)<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-s-6-sec\" class=\"nx-section nx-band-panel\" data-hue=\"finance\" aria-labelledby=\"nx-s-6\" role=\"tabpanel\" data-band-tab=\"nx-band-2-tab-2\"><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\">Pages<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">Pages in STEM foundation of AI and Financial Model Risk.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-cards\" data-cols=\"3\"><a class=\"nx-card\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/ai-ml\/\"><span class=\"nx-eyebrow\">Method<\/span><h3 class=\"nx-h4 nx-mt-2\">Artificial intelligence and machine learning for AI and financial model risk<\/h3><\/a><a class=\"nx-card\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/ai-assurance\/\"><span class=\"nx-eyebrow\">Method<\/span><h3 class=\"nx-h4 nx-mt-2\">AI evaluation and assurance engineering for AI and financial model risk<\/h3><\/a><a class=\"nx-card\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/uncertainty-quantification\/\"><span class=\"nx-eyebrow\">Method<\/span><h3 class=\"nx-h4 nx-mt-2\">Uncertainty quantification and model validation at AI and Financial Model Risk<\/h3><\/a><a class=\"nx-card\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/stem\/probability-statistics\/\"><span class=\"nx-eyebrow\">Method<\/span><h3 class=\"nx-h4 nx-mt-2\">Probability and statistics for AI and financial model risk<\/h3><\/a><\/div><\/div><\/div><\/section><section id=\"nx-s-7-sec\" class=\"nx-section nx-band-panel\" data-hue=\"project\" aria-labelledby=\"nx-s-7\" role=\"tabpanel\" data-band-tab=\"nx-band-2-tab-3\"><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\">Questions<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>What is a steward platform?<\/summary><div class=\"nx-answer\">The platform that maintains the canonical description of a method and reviews how it is applied across the Consortium.<\/div><\/details><\/div><\/div><\/div><\/section><\/div><\/div><\/section><section id=\"nx-sec-nr-gateway\" class=\"nx-section\" data-hue=\"finance\" data-tone=\"alt\" aria-labelledby=\"nx-nr-gateway-h\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">Reports<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Contribute<\/span><\/div><h2 id=\"nx-nr-gateway-h\" class=\"nx-section-title\">Contribute evidence from this page.<\/h2><p class=\"nx-lede\"><a class=\"nx-link\" href=\"https:\/\/docs.therisk.global\/organization\/programme\/reports\">Reports<\/a> is the Consortium&#8217;s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.<\/p><div class=\"nx-chips\"><span class=\"nx-chip\">Global Risks Alliance<\/span><span class=\"nx-chip\">AI and Financial Model Risk<\/span><span class=\"nx-chip\">Methods and Technical<\/span><span class=\"nx-chip\">Exponential Technology<\/span><\/div><\/div><div class=\"nx-section-body\"><ul class=\"nx-dest\"><li><a class=\"nx-dest-card\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/write-to-us\/contact\/\"><span class=\"nx-dest-top\"><span class=\"nx-dest-rel\">Email<\/span><span class=\"nx-dest-host\">Gateway GW-GRA<\/span><\/span><span class=\"nx-dest-title\">Send it from this page<\/span><span class=\"nx-dest-why\">Evidence, a correction, a case, a method, a review, a translation or profile input. It arrives tagged with this page, so the editor who owns it receives it.<\/span><span class=\"nx-dest-go\" aria-hidden=\"true\"><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><\/li><li><a class=\"nx-dest-card\" href=\"https:\/\/globalriskalliance.com\/nexus-reports\/open-science\/#nx-sec-zenodo\"><span class=\"nx-dest-top\"><span class=\"nx-dest-rel\">Zenodo<\/span><span class=\"nx-dest-host\">Open deposit<\/span><\/span><span class=\"nx-dest-title\">Deposit it and submit to the community<\/span><span class=\"nx-dest-why\">Publish your own record on Zenodo with your ORCID iD, then submit it to the Reports community there. 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