{"id":90,"date":"2026-10-17T10:48:49","date_gmt":"2026-10-17T10:48:49","guid":{"rendered":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/?page_id=90"},"modified":"2026-10-18T18:35:23","modified_gmt":"2026-10-18T18:35:23","slug":"methods","status":"publish","type":"page","link":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/","title":{"rendered":"Analysis and uncertainty"},"content":{"rendered":"\n<!-- Nexus network page \u00b7 https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/ \u00b7 source template \u00b7 generated by integrations\/wordpress\/network\/build.mjs, never edit this file --><script type=\"application\/json\" class=\"_iub_cs_skip\" id=\"nxe-water-data\" data-nx-pack=\"deflate\">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<\/script><script type=\"application\/json\" class=\"_iub_cs_skip\" id=\"nxe-water-gibs\" data-nx-pack=\"deflate\">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<\/script><script type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-water-engine\" data-nx-run=\"water\">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<\/script><script type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-maplibre-sources\" data-nx-run=\"mlsources\">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<\/script><script type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-maplibre-engine\" data-nx-run=\"maplibre\">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<\/script><script type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-mount\" data-nx-run=\"mount\">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<\/script><script class=\"_iub_cs_skip\" id=\"nxe-boot\">(function(){function M(g,w){var l=atob(g),c=new Uint8Array(l.length),r;for(r=0;r< l.length;r++){c[r]=l.charCodeAt(r)}var o=0,e=0,b=0,f=new Uint8Array(Math.max(1024,c.length*6)),n=0;var V=[3,4,5,6,7,8,9,10,11,13,15,17,19,23,27,31,35,43,51,59,67,83,99,115,131,163,195,227,258];var W=[0,0,0,0,0,0,0,0,1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,0];var Y=[1,2,3,4,5,7,9,13,17,25,33,49,65,97,129,193,257,385,513,769,1025,1537,2049,3073,4097,6145,8193,12289,16385,24577];var Z=[0,0,0,0,1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13];var z=[16,17,18,0,8,7,9,6,10,5,11,4,12,3,13,2,14,1,15];function u(a){while(b< a){if(o>=c.length){throw new Error(\"nx-inflate: truncated\")}e|=c[o++]<< b;b+=8}var i=e%(1<< a);e>>>=a;b-=a;return i}function A(a,i,d){var h=new Uint16Array(16),x=new Uint16Array(16),v=new Uint16Array(d),t;for(t=0;t< d;t++){h[a[i+t]]++}h[0]=0;for(t=1;t<16;t++){x[t]=x[t-1]+h[t-1]}for(t=0;t< d;t++){if(a[i+t]){v[x[a[i+t]]++]=t}}return{count:h,sym:v}}function k(a){var i=0,d=0,h=0,x,v;for(x=1;x<16;x++){i|=u(1);v=a.count[x];if(i-v< d){return a.sym[h+(i-d)]}h+=v;d+=v;d<<=1;i<<=1}throw new Error(\"nx-inflate: bad code\")}function I(a){if(n+a<=f.length){return}var i=new Uint8Array(Math.max(f.length*2,n+a));i.set(f.subarray(0,n));f=i}var L=null,R=null,T=0;while(!T){T=u(1);var O=u(2),S,$;if(O===0){e=0;b=0;var E=c[o]|c[o+1]<<8;o+=4;I(E);f.set(c.subarray(o,o+E),n);n+=E;o+=E;continue}if(O===1){if(!L){var X=new Uint8Array(288),J=new Uint8Array(30);for(r=0;r<288;r++){X[r]=r<144?8:r<256?9:r<280?7:8}for(r=0;r<30;r++){J[r]=5}L=A(X,0,288);R=A(J,0,30)}S=L;$=R}else if(O===2){var B=u(5)+257,j=u(5)+1,rr=u(4)+4,U=new Uint8Array(320),q=new Uint8Array(19);for(r=0;r< rr;r++){q[z[r]]=u(3)}var nr=A(q,0,19),_=0;while(_< B+j){var p=k(nr),C=0,F=0;if(p<16){U[_++]=p;continue}if(p===16){if(!_){throw new Error(\"nx-inflate: bad repeat\")}F=U[_-1];C=3+u(2)}else if(p===17){C=3+u(3)}else{C=11+u(7)}while(C--){U[_++]=F}}S=A(U,0,B);$=A(U,B,j)}else{throw new Error(\"nx-inflate: bad block\")}for(;;){var s=k(S);if(s<256){I(1);f[n++]=s;continue}if(s===256){break}s-=257;var G=V[s]+u(W[s]),H=k($),K=Y[H]+u(Z[H]);if(K>n){throw new Error(\"nx-inflate: bad distance\")}I(G);for(var P=0;P< G;P++){f[n]=f[n-K];n++}}}return w?f.subarray(0,n):new TextDecoder(\"utf-8\").decode(f.subarray(0,n))}if(typeof window.__nxInflate!==\"function\"){window.__nxInflate=M}function Q(g){var w=M(g,true),l=w[0]|w[1]<<8|w[2]<<16|w[3]<<24;var c=w.subarray(4+l);function r(o,e){var b=\"\",f=c.subarray(o,o+e);for(var n=0;e>n;n+=8192){b+=String.fromCharCode.apply(null,f.subarray(n,n+8192))}return btoa(b)}return JSON.parse(new TextDecoder(\"utf-8\").decode(w.subarray(4,4+l)),function(o,e){return e?e.$b?r(e.$b[0],e.$b[1]):e:e})}if(typeof window.__nxUnpack!==\"function\"){window.__nxUnpack=Q}var N=document.querySelectorAll(\"script[data-nx-run]\");for(var D=0;D< N.length;D++){var y=N[D];if(y.hasAttribute(\"data-nx-ran\")){continue}y.setAttribute(\"data-nx-ran\",\"true\");try{var m=document.createElement(\"script\");m.className=\"_iub_cs_skip\";m.setAttribute(\"data-nx-runtime\",y.getAttribute(\"data-nx-run\"));m.textContent=window.__nxInflate(y.textContent);(document.head||document.documentElement).appendChild(m)}catch(g){y.setAttribute(\"data-nx-ran\",\"failed\")}}})();<\/script><div class=\"nxe-host\" data-nxe-embed=\"n-a-p07-research-methods\"><div class=\"nxe\" id=\"nxe-ny2ez3k2\" data-inst=\"gra\" data-theme=\"light\" data-grammar=\"atlas\" data-domain=\"project\" data-arche=\"evidence\" lang=\"en\" data-nx-css=\"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\"><style>#nxe-ny2ez3k2.nxe{display:block;box-sizing:border-box;max-width:1180px;margin:0 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-ny2ez3k2.nxe :where(*,*::before,*::after){box-sizing:inherit}#nxe-ny2ez3k2.nxe :where(section,header,footer,nav,aside){display:block;margin:0 0 32px}#nxe-ny2ez3k2.nxe :where(h1,h2,h3,h4){line-height:1.2;margin:24px 0 12px;font-weight:600}#nxe-ny2ez3k2.nxe :where(p,ul,ol,dl,table,figure,details){margin:0 0 16px}#nxe-ny2ez3k2.nxe :where(ul,ol){padding-left:20px}#nxe-ny2ez3k2.nxe a{color:inherit;text-decoration:underline;text-underline-offset:2px}#nxe-ny2ez3k2.nxe table{border-collapse:collapse;width:100%;display:block;overflow-x:auto}#nxe-ny2ez3k2.nxe :where(th,td){padding:6px 8px;text-align:left;vertical-align:top;border-bottom:1px solid;border-color:inherit}#nxe-ny2ez3k2.nxe svg{display:none}#nxe-ny2ez3k2.nxe svg.nx-i{display:inline-block;width:18px;height:18px;vertical-align:-3px}#nxe-ny2ez3k2.nxe :where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-ny2ez3k2.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=\"dag\" 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-P07 \u00b7 EVIDENCE \u00b7 methods<\/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\">AI and Financial Model Risk<\/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>Methods and uncertainty<\/span><\/div><h1 id=\"nx-title-1\" class=\"nx-hero-title\">Analysis and uncertainty<\/h1><p class=\"nx-tagline\">The methods AI and Financial Model Risk relies on, the assumptions they carry and the limits of what they can show.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/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\/ai-financial-model-risk\/research\/\">Back to Professional research<\/a><\/div><dl class=\"nx-facts\"><div><dt class=\"nx-eyebrow\">Publisher<\/dt><dd>The Global Risks Alliance<\/dd><\/div><div><dt class=\"nx-eyebrow\">Field<\/dt><dd>Artificial intelligence, Financial stability<\/dd><\/div><\/dl><\/div><div class=\"nx-hero-canvas\" data-lv-fill=\"dag\" data-lv-id=\"model-validation\"><div class=\"nx-plate\" data-wide=\"true\"><div class=\"nx-plate-label\"><span class=\"nx-eyebrow\"><strong>Canvas<\/strong> \u00b7 draft to published version<\/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-p07-research-methods-source-passport-t nx-dag-a-p07-research-methods-source-passport-d\" data-nx-z=\"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\"><title id=\"nx-dag-a-p07-research-methods-source-passport-t\">Analysis and uncertainty: from a source to a labelled evidence record<\/title><desc id=\"nx-dag-a-p07-research-methods-source-passport-d\">A source is registered with its licence and steward, checked for quality and coverage, labelled by evidence class, versioned and published with a passport; corrections create a new version. Design of the process, not a record of a run.<\/desc><\/svg><\/div><\/div><p class=\"nx-caption\"><strong>Fig.<\/strong><span>How a finding is reviewed before it is published. Design, not a record.<\/span><\/p><\/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>Connected activity in California<\/a><a href=\"#nx-sec-methods\"><span>03<\/span>The methods in use<\/a><a href=\"#nx-sec-pg-nx-gra-ap07-me-xai\"><span>04<\/span>Explainability and fairness methods,\u2026<\/a><a href=\"#nx-sec-pg-nx-gra-ap07-me-uq\"><span>05<\/span>Quantifying what the model does not\u2026<\/a><a href=\"#nx-sec-uncertainty\"><span>06<\/span>How uncertainty is reported<\/a><a href=\"#nx-sec-terms\"><span>07<\/span>Terms used on this page<\/a><a href=\"#nx-sec-pg-sources\"><span>08<\/span>Where this page's references lead<\/a><\/div><\/nav> <section id=\"nx-sec-brief-answer\" class=\"nx-section\" data-hue=\"project\" 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\">The AI and Financial Model Risk methods page sets out the methods the platform relies on, among them artificial intelligence and machine learning, AI evaluation and assurance engineering, and uncertainty quantification and model validation, with their assumptions, validation and limits. Each analysis lists its assumptions and data, reports ranges and confidence beside central estimates, is checked against observations or other models, and states what it cannot show.<\/p><\/div><\/div><\/section><div class=\"nx-live-slot\" data-nxf-slot=\"search\" data-nxf-kind=\"search\" data-nxf-resource=\"nexus:\/\/gra\/A-P07\/research\/methods\/#search\" data-nxf-title=\"Search publications\" data-nxf-height=\"520\" hidden><\/div><section id=\"nx-sec-field\" class=\"nx-section\" data-hue=\"finance\" 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\">Geography<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">Connected activity in California.<\/h2><p class=\"nx-lede\">For analysis and uncertainty, in GRA's spatial-finance reading, the map opens on night lights and population density with night lights tonight from NASA GIBS, framed on California; 4 further NASA layers wait in the list.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><div class=\"nx-cmap-field\" data-nx-map=\"ctx-field\" data-cmap=\"california:digital\" data-ml-src=\"digital\" data-ml-plan=\"p-73164d56\"><div class=\"nx-wm\" data-nx-water=\"ctx-digital\" data-wm-domain=\"ctx-digital\" data-wm-tiles=\"on\" data-wm-flat=\"on\" data-wm-focus=\"-124.5,32.4,-114,42\" data-ws-live=\"off\" data-claim=\"INTEGRATED\" data-wm-panel=\"closed\" data-wm-mode=\"2d\"><div class=\"nx-wm-stage\" tabindex=\"0\" role=\"application\" aria-roledescription=\"interactive map\" aria-label=\"Connected activity, California: satellite and model layers from NASA on a 3D terrain of ASTER GDEM elevation. Arrow keys move; with Shift they turn and tilt in 3D; plus and minus zoom, 0 resets; I inspects, question mark lists the keys.\" aria-describedby=\"nx-wm-help\"><canvas class=\"nx-wm-canvas\" aria-hidden=\"true\"><\/canvas><p class=\"nx-wm-noscript\">The interactive map needs JavaScript; the layer list and sources are below.<\/p><div class=\"nx-wm-presets\" role=\"group\" aria-label=\"Quick views\"><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"ntl,people||||\" aria-pressed=\"false\">Lights and people<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"ntl||||\" aria-pressed=\"false\">Night lights<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"people||||\" aria-pressed=\"false\">Population<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"true||||\" aria-pressed=\"false\">True colour<\/button><\/div><div class=\"nx-wm-panel\" id=\"nx-wm-panel\" role=\"region\" aria-label=\"Map layers\"><div class=\"nx-wm-panel-head\"><p class=\"nx-wm-panel-title\">Layers <span class=\"nx-wm-count\">2<\/span><\/p><button type=\"button\" class=\"nx-wm-icon nx-wm-panel-close\" data-wm-act=\"panel\" aria-label=\"Close the layer list\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-panel-body\"><div class=\"nx-wm-group\"><p class=\"nx-wm-group-title\">Connected activity, for this page<\/p><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"ntl\" aria-pressed=\"true\" data-wm-z=\"20\" data-wm-lag=\"0\" data-wm-op=\"0.9\" data-wm-short=\"Night lights\" data-wm-prov=\"NASA LAADS DAAC\" data-wm-kind=\"Satellite radiance, corrected for moonlight and atmosphere\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Night-time lights, daily<\/span><span class=\"nx-wm-layer-src\">NASA LAADS DAAC VIIRS Black Marble (VNP46A2) \u00b7 <span data-wm-date=\"ntl\">12 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"ntl\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"people\" aria-pressed=\"true\" data-wm-z=\"21\" data-wm-lag=\"0\" data-wm-op=\"0.8\" data-wm-short=\"Population density\" data-wm-prov=\"NASA SEDAC (CIESIN, Columbia University)\" data-wm-kind=\"Census-based estimate, static (2020)\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Population density, 2020<\/span><span class=\"nx-wm-layer-src\">NASA SEDAC (CIESIN, Columbia University) Gridded Population of the World v4.11 \u00b7 <span data-wm-date=\"people\">static<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"people\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"true\" aria-pressed=\"false\" data-wm-z=\"22\" data-wm-lag=\"1\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite image\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">True colour<\/span><span class=\"nx-wm-layer-src\">NASA LANCE VIIRS NOAA-20 corrected reflectance \u00b7 <span data-wm-date=\"true\">13 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"true\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"cover\" aria-pressed=\"false\" data-wm-z=\"23\" data-wm-lag=\"0\" data-wm-time=\"latest\" data-wm-op=\"0.7\" data-wm-short=\"Land cover\" data-wm-prov=\"NASA LP DAAC\" data-wm-kind=\"Satellite classification; latest year GIBS publishes\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Land cover type (IGBP), yearly<\/span><span class=\"nx-wm-layer-src\">NASA LP DAAC MODIS Terra and Aqua land cover (MCD12Q1) \u00b7 <span data-wm-date=\"cover\">2024<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"cover\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"flood\" aria-pressed=\"false\" data-wm-z=\"24\" data-wm-lag=\"0\" data-wm-short=\"Flood water\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite detection; clouds leave gaps\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Flood water, 3-day composite<\/span><span class=\"nx-wm-layer-src\">NASA LANCE VIIRS Global Flood Product \u00b7 <span data-wm-date=\"flood\">14 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"flood\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"lstd\" aria-pressed=\"false\" data-wm-z=\"25\" data-wm-lag=\"0\" data-wm-op=\"0.8\" data-wm-short=\"Land temperature, day\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite 8-day composite; persistent cloud still leaves gaps\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Land surface temperature, day, 8-day composite<\/span><span class=\"nx-wm-layer-src\">NASA LANCE VIIRS NOAA-20 Level 3, 8-day \u00b7 <span data-wm-date=\"lstd\">14 Sep 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"lstd\" hidden><\/div><\/div><\/div><\/div><div class=\"nx-wm-rail\" role=\"toolbar\" aria-orientation=\"vertical\" aria-label=\"Map controls\"><button type=\"button\" class=\"nx-wm-icon nx-wm-open\" data-wm-act=\"panel\" aria-controls=\"nx-wm-panel\" aria-expanded=\"false\" aria-label=\"Layers\" title=\"Layers\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M8 2.5l-6.5 3.5 6.5 3.5 6.5-3.5zm-6.5 6.5 6.5 3.5 6.5-3.5m-13 2.8 6.5 3.5 6.5-3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"tools\" aria-controls=\"nx-wm-menu\" aria-expanded=\"false\" aria-label=\"Expert tools\" title=\"Expert tools\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3 4.5l10 0m-10 3.5 10 0m-10 3.5 10 0m-7.5-8.5 0 3m5 .5 0 3m-3.5.5 0 3\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><span class=\"nx-wm-sep\" aria-hidden=\"true\"><\/span><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"in\" aria-label=\"Zoom in\" title=\"Zoom in\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M8 3v10M3 8h10\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"out\" aria-label=\"Zoom out\" title=\"Zoom out\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3 8h10\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"reset\" aria-label=\"Reset the view\" title=\"Reset the view\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.2 8a4.8 4.8 0 1 0 1.5-3.5M3.2 2.6v2.6h2.6\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"full\" aria-label=\"Full screen\" title=\"Full screen\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M2.5 6l0-3.5 3.5 0m7.5 3.5 0-3.5-3.5 0m-7.5 7.5 0 3.5 3.5 0m7.5-3.5 0 3.5-3.5 0\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-menu\" id=\"nx-wm-menu\" role=\"menu\" aria-label=\"Expert tools\" hidden><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"inspect\">Inspect a point<kbd>I<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"measure\">Measure distance<kbd>M<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"compare\">Compare two dates<kbd>C<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"share\">Copy a link to this view<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"png\">Export as PNG with credits<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"xt\" data-wm-xt=\"nD8AHC9C+3M3ObZpd9R\/Lxb2bo29sfEuijTslQu3cAY=\">More expert tools<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"keys\">Keyboard shortcuts<kbd>?<\/kbd><\/button><\/div><div class=\"nx-wm-keys\" role=\"dialog\" aria-label=\"Keyboard shortcuts\" hidden><p class=\"nx-wm-keys-title\">Keyboard, with the map focused<\/p><dl class=\"nx-wm-keys-list\"><\/dl><button type=\"button\" class=\"nx-wm-icon nx-wm-keys-close\" data-wm-tool=\"keys\" aria-label=\"Close the shortcuts\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><p class=\"nx-wm-hint\" hidden>Hold Ctrl or \u2318 and scroll to zoom<\/p><p class=\"nx-wm-toolbar\" role=\"status\" hidden><\/p><div class=\"nx-wm-tip\" role=\"tooltip\" hidden><\/div><div class=\"nx-wm-pin\" hidden><div class=\"nx-wm-pin-head\"><p class=\"nx-wm-pin-title\"><\/p><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"unpin\" aria-label=\"Close the card\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-pin-chart\"><\/div><div class=\"nx-wm-pin-body\"><\/div><\/div><div class=\"nx-wm-dock\"><div class=\"nx-wm-time\" role=\"group\" aria-label=\"Imagery date\"><button type=\"button\" class=\"nx-wm-icon\" data-wm-step=\"prev\" aria-label=\"One day earlier\">\u2039<\/button><p class=\"nx-wm-time-label\">Latest available<\/p><button type=\"button\" class=\"nx-wm-icon\" data-wm-step=\"next\" aria-label=\"One day later\">\u203a<\/button><span class=\"nx-wm-track\" role=\"slider\" tabindex=\"0\" aria-label=\"Imagery date, up to 30 days back\"><\/span><button type=\"button\" class=\"nx-wm-latest\" data-wm-step=\"latest\" aria-pressed=\"true\">Latest<\/button><\/div><div class=\"nx-wm-chips\" role=\"group\" aria-label=\"Legends\"><\/div><p class=\"nx-wm-attrib\">NASA GIBS \/ EOSDIS \u00b7 ASTER GDEM (METI, NASA) \u00b7 Blue Marble (NASA) \u00b7 \u00a9 OpenStreetMap contributors (ODbL) \u00b7 Natural Earth<\/p><div class=\"nx-wm-legends\" aria-live=\"polite\" hidden><\/div><\/div><\/div><div class=\"nx-container nx-wm-below\"><p class=\"nx-wm-status\" role=\"status\">Loading the latest NASA imagery.<\/p><p id=\"nx-wm-help\" class=\"nx-wm-help\">Drag to move. Ctrl or \u2318 and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.<\/p><p class=\"nx-caption\"><span>For analysis and uncertainty, in GRA's spatial-finance reading, the map opens on night lights and population density with night lights tonight from NASA GIBS, framed on California; 4 further NASA layers wait in the list.<\/span><span data-honesty=\"true\">Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.<\/span><\/p><details class=\"nx-wm-credits\"><summary><span class=\"nx-wm-credits-line\">Data: NASA GIBS \u00b7 ASTER GDEM \u00b7 Blue Marble \u00b7 \u00a9 OpenStreetMap contributors \u00b7 Natural Earth \u00b7 NASA\/NOAA VIIRS \u00b7 CIESIN\/Columbia, NASA SEDAC HBASE \u00b7 GDACS<\/span><span class=\"nx-wm-credits-more\">Sources and licences<\/span><\/summary><p class=\"nx-wm-credit\"><ul class=\"nx-wm-credit-list\"><li data-wm-credit=\"nasa.gibs.field-layers\">We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.gibs.water-layers\">We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.laads.black-marble\">VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\">NASA open data<\/a><\/li><li data-wm-credit=\"sedac.gpw-v4\">Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" rel=\"noopener\">CC BY 4.0<\/a><\/li><li data-wm-credit=\"nasa.lance.viirs-water\">VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.modis-viirs.land\">MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa-meti.aster-gdem-v3\">ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\">NASA open data<\/a><\/li><li data-wm-credit=\"naturalearth.all-scales\">Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. <a class=\"nx-link\" href=\"https:\/\/www.naturalearthdata.com\/about\/terms-of-use\/\" rel=\"noopener\">Public domain<\/a><\/li><li data-wm-credit=\"nasa.gibs.reference-osm\">\u00a9 OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.openstreetmap.org\/copyright\" rel=\"noopener\">ODbL<\/a><\/li><li data-wm-credit=\"nasa.earth-observatory.blue-marble\">Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\">NASA open data<\/a><\/li><li>Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, \u00a9 OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.<\/li><li>Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, \u00a9 MapLibre contributors.<\/li><li>Observed (EO): NASA\/NOAA VIIRS (Suomi NPP). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).<\/li><li>Context: CIESIN\/Columbia, NASA SEDAC HBASE. Center for International Earth Science Information Network (CIESIN), Columbia University, and NASA Socioeconomic Data and Applications Center (SEDAC): Global Human Built-up And Settlement Extent (HBASE) 2010; Seto, Guneralp and Hutyra 2012, Global Grid of Probabilities of Urban Expansion to 2030; Global Urban Heat Island (UHI) Data Set, 2013.<\/li><li>Live: GDACS (EC JRC \/ UN OCHA) Events are indicative, not official warnings.<\/li><li>Optional layers (4 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.<\/li><\/ul><p class=\"nx-wm-credit\"><strong>Layers and dates<\/strong><\/p><ul class=\"nx-wm-credit-list\"><li>Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC \u00b7 <span data-wm-date=\"ntl\">12 Oct 2026<\/span><\/li><li>Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 \u00b7 <span data-wm-date=\"people\">static<\/span><\/li><li>True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE \u00b7 <span data-wm-date=\"true\">13 Oct 2026<\/span><\/li><li>Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC \u00b7 <span data-wm-date=\"cover\">2024<\/span><\/li><li>Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE \u00b7 <span data-wm-date=\"flood\">14 Oct 2026<\/span><\/li><li>Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE \u00b7 <span data-wm-date=\"lstd\">14 Sep 2026<\/span><\/li><\/ul><\/p><\/details><\/div><\/div><div class=\"nx-live-slot nx-live-slot--map\" data-nxf-slot=\"map\" data-nxf-kind=\"map\" data-nxf-resource=\"nexus:\/\/gra\/A-P07\/research\/methods\/#map\" data-nxf-title=\"AI and Financial Model Risk live map\" data-nxf-height=\"560\" hidden><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-methods\" class=\"nx-section\" data-hue=\"project\" 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\">Methods<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">The methods in use.<\/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><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\/technology\/ai-ml\/\" aria-label=\"Artificial intelligence and machine learning: 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\/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><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\/ai-assurance\/\" aria-label=\"AI evaluation and assurance 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\/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><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\/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><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\/probability-statistics\/\" aria-label=\"Probability and statistics: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><\/ol><\/div><\/div><\/div><\/section><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gra\/A-P07\/research\/methods\/#evidence\" data-nxf-title=\"Evidence records\" data-nxf-height=\"520\" hidden><\/div><section id=\"nx-sec-pg-nx-gra-ap07-me-xai\" class=\"nx-section\" data-hue=\"finance\" data-tone=\"alt\" 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\">Methods<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">Explainability and fairness methods, with limits.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th>Method<\/th><th>Gives<\/th><th>Limit<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Method\">SHAP and other attribution methods<\/td><td data-label=\"Gives\">Contribution of each input to a prediction<\/td><td data-label=\"Limit\">Correlated inputs blur attribution<\/td><\/tr><tr><td data-label=\"Method\">Counterfactual explanations<\/td><td data-label=\"Gives\">What change would alter the decision<\/td><td data-label=\"Limit\">May suggest infeasible changes<\/td><\/tr><tr><td data-label=\"Method\">Group fairness metrics<\/td><td data-label=\"Gives\">Outcome differences across groups<\/td><td data-label=\"Limit\">Metrics can conflict<\/td><\/tr><tr><td data-label=\"Method\">Challenger models<\/td><td data-label=\"Gives\">Independent benchmark<\/td><td data-label=\"Limit\">Shares data weaknesses<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-pg-nx-gra-ap07-me-uq\" class=\"nx-section\" data-hue=\"project\" data-variant=\"split\" 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\">Uncertainty<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">Quantifying what the model does not know.<\/h2><\/div><div class=\"nx-section-body\"><p class=\"nx-p\">Prediction intervals and calibration checks show when a model is outside its experience. Methods at <a class=\"nx-link\" href=\"https:\/\/therisk.global\/risk-management\/stem\/uncertainty-quantification\/\">GCRI uncertainty quantification<\/a>; topic depth at explainability and fairness.<\/p><\/div><\/div><\/section><section id=\"nx-sec-uncertainty\" class=\"nx-section\" data-hue=\"finance\" 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\">Uncertainty<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">How uncertainty is reported.<\/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\">State assumptions<\/h3><p class=\"nx-p nx-mt-1\">Each analysis lists its assumptions and the data it depends on.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">02<\/span><div><h3 class=\"nx-h4\">Quantify where possible<\/h3><p class=\"nx-p nx-mt-1\">Ranges and confidence are reported alongside central estimates.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">03<\/span><div><h3 class=\"nx-h4\">Validate and compare<\/h3><p class=\"nx-p nx-mt-1\">Models are checked against observations and, where possible, against other models.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">04<\/span><div><h3 class=\"nx-h4\">Publish limits<\/h3><p class=\"nx-p nx-mt-1\">What an analysis cannot show is stated beside what it can.<\/p><\/div><\/li><\/ol><\/div><\/div><\/section><section id=\"nx-sec-terms\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" data-variant=\"split\" 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\">Key terms<\/span><\/div><h2 id=\"nx-s-8\" 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\">Uncertainty quantification<\/td><td data-label=\"Definition\">Characterising and propagating the uncertainties in a model to state confidence in its outputs.<\/td><\/tr><tr><td data-label=\"Term\">Sensitivity analysis<\/td><td data-label=\"Definition\">Repeating an analysis under different assumptions to show how much the result depends on them.<\/td><\/tr><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\">Artificial intelligence and machine learning<\/td><td data-label=\"Definition\">Artificial intelligence and machine learning develop algorithms that learn patterns from data to classify, predict or generate outputs.<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-pg-sources\" class=\"nx-section\" data-hue=\"finance\" 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\">Sources<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Where this page'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.nist.gov\/itl\/ai-risk-management-framework\"><span>NIST AI Risk Management Framework 1.0<\/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><\/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\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-s-10-sec\" class=\"nx-section\" data-hue=\"project\" 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\">Questions<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>Are the methods open?<\/summary><div class=\"nx-answer\">Method descriptions are public on the STEM Commons. Code and data follow their own licences and access terms, listed in the source register.<\/div><\/details><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-tone=\"alt\" aria-labelledby=\"nx-rel-11\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Related<\/span><h2 id=\"nx-rel-11\" class=\"nx-h3 nx-mt-2\">Around AI and Financial Model Risk.<\/h2><nav class=\"nx-related nx-mt-3\" aria-label=\"Related\"><a href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/sources\/\">Financial source and licence register <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\/ai-financial-model-risk\/\">AI and Financial Model Risk 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\/ai-financial-model-risk\/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-12\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">AI and Financial Model Risk<\/span><h2 id=\"nx-close-12\" 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=AI%20and%20Financial%20Model%20Risk%3A%20Analysis%20and%20uncertainty\">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\/ai-financial-model-risk\/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\/ai-financial-model-risk\/research\/methods\/#faq\",\"isPartOf\":{\"@id\":\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/#webpage\"},\"inLanguage\":\"en\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"Are the methods open?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Method descriptions are public on the STEM Commons. Code and data follow their own licences and access terms, listed in the source register.\"}}]},{\"@type\":\"DefinedTermSet\",\"@id\":\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/#terms\",\"name\":\"Key terms: Analysis and uncertainty\",\"inLanguage\":\"en\",\"isPartOf\":{\"@id\":\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/#webpage\"},\"hasDefinedTerm\":[{\"@type\":\"DefinedTerm\",\"name\":\"Uncertainty quantification\",\"description\":\"Characterising and propagating the uncertainties in a model to state confidence in its outputs.\",\"inDefinedTermSet\":{\"@id\":\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/#terms\"}},{\"@type\":\"DefinedTerm\",\"name\":\"Sensitivity analysis\",\"description\":\"Repeating an analysis under different assumptions to show how much the result depends on them.\",\"inDefinedTermSet\":{\"@id\":\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/#terms\"}},{\"@type\":\"DefinedTerm\",\"name\":\"Model validation\",\"description\":\"Independent testing that a model performs as intended and is fit for a stated use.\",\"inDefinedTermSet\":{\"@id\":\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/#terms\"}},{\"@type\":\"DefinedTerm\",\"name\":\"Artificial intelligence and machine learning\",\"description\":\"Artificial intelligence and machine learning develop algorithms that learn patterns from data to classify, predict or generate outputs.\",\"inDefinedTermSet\":{\"@id\":\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/#terms\"}}]}]}<\/script>\n\n<!-- nx-rev:913aa53cb43971b3 -->","protected":false},"excerpt":{"rendered":"<p>LightDarkAuto A-P07 \u00b7 EVIDENCE \u00b7 methodsGRA dossier \u00b7 service level R0 GRA\u00b7AI and Financial Model Risk\u00b7In development Methods and uncertainty Analysis and uncertainty The methods AI and Financial Model Risk &hellip; <a href=\"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/research\/methods\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Analysis and uncertainty&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":77,"menu_order":180,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"_buddyx_sub_header_visibility":"","_buddyx_sub_header_title_visibility":"","_hide_show_side_panel":"","_buddyxpro_page_sidebar":"","_buddyxpro_page_disable_header":"","_buddyxpro_page_disable_footer":"","_buddyxpro_page_content_width":"","_buddyxpro_page_header_style":"","_buddyxpro_page_color_mode":"","_buddyxpro_page_loader":"","footnotes":""},"class_list":["post-90","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/wp-json\/wp\/v2\/pages\/90","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/wp-json\/wp\/v2\/comments?post=90"}],"version-history":[{"count":1,"href":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/wp-json\/wp\/v2\/pages\/90\/revisions"}],"predecessor-version":[{"id":135,"href":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/wp-json\/wp\/v2\/pages\/90\/revisions\/135"}],"up":[{"embeddable":true,"href":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/wp-json\/wp\/v2\/pages\/77"}],"wp:attachment":[{"href":"https:\/\/globalriskalliance.com\/ai-financial-model-risk\/wp-json\/wp\/v2\/media?parent=90"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}