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var(--h-text); } .vtab[aria-selected=\"true\"] { background: var(--h-elevated); color: var(--h-text); box-shadow: inset 2px 0 0 var(--h-accent); } .vtab[aria-selected=\"true\"]:dir(rtl) { box-shadow: inset -2px 0 0 var(--h-accent); } .arrow:dir(rtl) { scale: -1 1; } .vtab:focus-visible { outline-offset: -2px; } .vt-l { font: 500 13.5px\/1.2 var(--h-sans); letter-spacing: -0.005em; } .vt-d { font: 400 11.5px\/1.3 var(--h-body); color: var(--h-muted); } .vpane { display: grid; grid-template-columns: repeat(var(--cols, 3), minmax(0, 1fr)); gap: 0 28px; min-width: 0; animation: nxh-in var(--h-base) var(--h-ease); } .vpane[hidden] { display: none; } @keyframes nxh-in { from { transform: translateY(4px); } to { transform: none; } } .rail.slim { padding: 0; background: none; border: 0; } .viz { height: 200px; margin: -6px 0 18px; } .viz canvas { display: block; width: 100%; height: 100%; } .p-body[data-rail=\"none\"] { grid-template-columns: repeat(var(--cols, 3), minmax(0, 1fr)); } .col { display: flex; flex-direction: column; gap: 26px; min-width: 0; } .g-head { display: flex; align-items: center; justify-content: space-between; gap: 12px; padding-block-end: 10px; border-block-end: 1px solid var(--h-line); } .g-head .eyebrow { color: var(--h-text-2); } .g-head a.eyebrow:hover { color: var(--h-text); } .g-desc { font: 400 11.5px\/1.25 var(--h-body); color: var(--h-muted); display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2; white-space: normal; overflow: hidden; min-width: 0; } .rows { margin-top: 6px; } .row { display: flex; align-items: center; gap: 12px; min-height: 44px; padding: 5px 8px; margin: 0 -8px; border-radius: 5px; transition: background-color var(--h-fast) var(--h-ease); } .row:hover, .row:focus-visible { background: var(--h-hover); } .row:focus-visible { outline-offset: -2px; } .row[aria-current] .r-t { color: var(--h-accent); } .itile { display: inline-flex; width: 32px; height: 32px; align-items: center; justify-content: center; border: 1px solid var(--h-line); border-radius: 5px; color: var(--h-text-2); flex: none; transition: border-color var(--h-fast) var(--h-ease), color var(--h-fast) var(--h-ease); } .row:hover .itile, .row:focus-visible .itile { border-color: var(--h-line-strong); color: var(--h-text); } .r-txt { display: block; min-width: 0; flex: 1; } .r-t { display: block; font: 500 13.5px\/1.2 var(--h-sans); letter-spacing: -0.005em; color: var(--h-text); white-space: nowrap; overflow: hidden; text-overflow: ellipsis; } .r-d { display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2; margin-top: 3px; font: 400 12px\/1.35 var(--h-body); color: var(--h-muted); white-space: normal; overflow: hidden; } .row .arrow { opacity: 0; color: var(--h-muted); transition: opacity var(--h-fast) var(--h-ease), transform var(--h-fast) var(--h-ease); } .row:hover .arrow, .row:focus-visible .arrow { opacity: 1; transform: translateX(2px); } .row.compact { min-height: 38px; padding-block: 3px; gap: 10px; } .row.compact .itile { width: 28px; height: 28px; } .row.compact .itile .ic { width: 15px; height: 15px; } .vpane .row.compact .r-t { font-weight: 450; color: var(--h-text-2); } .vpane .row.compact:hover .r-t, .vpane .row.compact:focus-visible .r-t { color: var(--h-text); } .rail { display: flex; flex-direction: column; padding: 20px; background: var(--h-elevated); border: 1px solid var(--h-line); border-radius: 5px; min-width: 0; } .feat { display: block; margin-top: 10px; border-radius: 5px; } .feat-t { display: flex; align-items: center; gap: 8px; margin-top: 0; font: 500 15px\/1.25 var(--h-sans); letter-spacing: -0.01em; color: var(--h-text); } .feat-d { display: block; margin-top: 4px; font: 400 12.5px\/1.45 var(--h-body); color: var(--h-muted); } .feat:hover .feat-t .arrow { transform: translateX(2px); } .acts { display: flex; flex-direction: column; gap: 8px; margin-top: 18px; } .btn { display: inline-flex; align-items: center; justify-content: center; gap: 8px; height: 40px; padding: 0 16px; border-radius: 5px; font: 500 13px\/1 var(--h-sans); white-space: nowrap; transition: background-color var(--h-fast) var(--h-ease), border-color var(--h-fast) var(--h-ease); } .btn.primary { background: var(--h-primary-bg); color: var(--h-primary-ink); } .btn.primary:hover { background: var(--h-primary-hover); } .btn.secondary { border: 1px solid var(--h-line-strong); color: var(--h-text); } .btn.secondary:hover { border-color: var(--h-text); background: var(--h-hover); } .pts { margin: 18px 0 0; border-block-start: 1px solid var(--h-line); } .pt { display: flex; flex-direction: column; gap: 5px; padding: 10px 0; border-block-end: 1px solid var(--h-line); } .pt-v { font: 400 12px\/1.45 var(--h-body); color: var(--h-text-2); } .p-foot { display: flex; flex-wrap: wrap; align-items: center; gap: 8px 20px; padding: 12px 24px; border-block-start: 1px solid var(--h-line); } .p-foot a { font: 400 12.5px\/1 var(--h-sans); color: var(--h-muted); min-height: 24px; display: inline-flex; align-items: center; } .p-foot a:hover { color: var(--h-text); } .ctx { border-block-start: 1px solid var(--h-line); } .ctx .wrap { height: var(--h-ctx-h); gap: 16px; } .crumbs { display: flex; align-items: center; gap: 8px; flex: none; min-width: 0; font-size: 13px; } .crumbs li { display: flex; align-items: center; gap: 8px; min-width: 0; white-space: nowrap; } .crumbs li + li::before { content: \"\/\"; color: var(--h-muted); } .crumbs a { color: var(--h-muted); min-height: 24px; display: inline-flex; align-items: center; } .crumbs a:hover { color: var(--h-text); } .crumbs a[aria-current] { color: var(--h-text); font-weight: 500; } .vsep { width: 1px; height: 18px; background: var(--h-line-strong); flex: none; } .inl { display: flex; align-items: center; gap: 2px; min-width: 0; flex: 1; overflow-x: auto; scrollbar-width: none; } .inl::-webkit-scrollbar { display: none; } .inl a[hidden] { display: none; } .inl a { display: inline-flex; align-items: center; height: 32px; padding: 0 10px; border-radius: 5px; font-size: 13px; color: var(--h-text-2); white-space: nowrap; } .inl a:hover { background: var(--h-hover); color: var(--h-text); } .inl a[aria-current] { color: var(--h-text); font-weight: 500; box-shadow: inset 0 -2px 0 var(--h-accent); border-radius: 0; } .ctx .trig { height: 32px; font-size: 13px; flex: none; border: 1px solid var(--h-line-strong); } .ctx .trig[aria-expanded=\"true\"]::after { display: none; } .drawer { position: fixed; inset: var(--nxh-bottom, 56px) 0 0 0; z-index: 3; background: var(--h-canvas); color: var(--h-text-2); overflow-y: auto; overscroll-behavior: contain; padding: 8px 20px 40px; border-block-start: 1px solid var(--h-line); } .drawer[hidden] { display: none; } .d-sec { border-block-end: 1px solid var(--h-line); } .d-btn { display: flex; align-items: center; justify-content: space-between; gap: 12px; width: 100%; min-height: 56px; padding: 8px 0; text-align: start; } .d-btn .d-l { display: block; font: 500 16px\/1.2 var(--h-sans); color: var(--h-text); letter-spacing: -0.01em; } .d-btn .eyebrow { display: block; margin-top: 6px; white-space: normal; line-height: 1.45; } .d-btn[aria-expanded=\"true\"] .chev { transform: rotate(180deg); } .d-body { padding: 0 0 18px; } .d-body[hidden] { display: none; } .d-group + .d-group { margin-top: 18px; } .d-group .g-head { margin-bottom: 4px; } .d-acts { display: grid; grid-template-columns: 1fr 1fr; gap: 8px; margin-top: 16px; } .d-links { display: flex; flex-direction: column; padding: 12px 0; border-block-end: 1px solid var(--h-line); } .d-links a { display: flex; align-items: center; justify-content: space-between; min-height: 44px; font: 500 15px\/1.2 var(--h-sans); color: var(--h-text); } .d-net { padding: 18px 0 0; } .d-net ul { margin-top: 10px; display: grid; grid-template-columns: 1fr 1fr; gap: 0 16px; } .d-net a { display: flex; align-items: center; min-height: 40px; font-size: 14px; color: var(--h-text-2); } .d-net a[aria-current] { color: var(--h-text); font-weight: 500; box-shadow: inset 2px 0 0 var(--h-accent); padding-inline-start: 10px; } .d-net a[aria-current]:dir(rtl) { box-shadow: inset -2px 0 0 var(--h-accent); } .d-crumbs { padding: 14px 0 4px; } @media (max-width: 1279px) { .panel .r-d, .panel .g-desc { display: none; } .p-body { grid-template-columns: repeat(var(--cols, 3), minmax(0, 1fr)) 232px; gap: 0 24px; } .p-body.tabbed { grid-template-columns: 184px minmax(0, 1fr) 232px; } .vpane { gap: 0 24px; } .vt-d { display: none; } .row { min-height: 38px; } } @media (max-width: 1199px) { .nx-lang__label { display: none; } .nx-lang__code { display: inline; } .theme .tl { position: absolute; width: 1px; height: 1px; overflow: hidden; clip: rect(0 0 0 0); } .theme button { padding: 0 7px; } .end .contact { display: none; } } @media (max-width: 959px) { :host { --h-gutter: 16px; --h-bar-h: 56px; --h-ctx-h: 40px; } .net, .main, .end .contact, .end .acct { display: none; } .bar .wrap { justify-content: space-between; } .burger { display: inline-flex; } .ctx .inl, .ctx .vsep, .ctx .trig { display: none; } .crumbs { flex: 1; overflow: hidden; } .crumbs li:not(:first-child):not(:last-child) { display: none; } .crumbs li:last-child { overflow: hidden; } .crumbs li:last-child a { overflow: hidden; text-overflow: ellipsis; display: block; line-height: 24px; } } @media (prefers-reduced-motion: reduce) { *, *::before, *::after { transition: none !important; animation: none !important; } } .f { position: relative; background: var(--h-elevated); color: var(--h-text); border-top: 1px solid var(--h-line); font: 400 14px\/1.5 var(--h-body); -webkit-font-smoothing: antialiased; } .f::before { content: \"\"; position: absolute; left: 0; right: 0; top: -1px; height: 2px; background: var(--h-rule); } .f-wrap { max-width: var(--h-max); margin: 0 auto; padding: 44px var(--h-gutter) 24px; } .f-head { display: grid; grid-template-columns: minmax(0, 1fr) auto; align-items: end; gap: 16px 40px; padding-bottom: 32px; } .f-id { min-width: 0; } .f-site { font: 500 22px\/1.25 var(--h-sans); letter-spacing: -0.015em; color: var(--h-text); text-decoration: none; } .f-site:hover { text-decoration: underline; text-underline-offset: 3px; } .f-role { margin: 8px 0 0; color: var(--h-text-2); font-size: 14px; line-height: 1.55; max-width: 76ch; } .f-acts { display: flex; flex-wrap: wrap; align-items: center; gap: 8px; } .f-act { appearance: none; display: inline-flex; align-items: center; gap: 8px; min-height: 36px; padding: 0 14px; border: 1px solid var(--h-line-strong); border-radius: 5px; background: var(--h-canvas); color: var(--h-text); font: 500 13px\/1 var(--h-sans); text-decoration: none; cursor: pointer; white-space: nowrap; } .f-act:hover { background: var(--h-hover); } .f-docs { background: var(--h-primary-bg); border-color: var(--h-primary-bg); color: var(--h-primary-ink); } .f-docs:hover { background: var(--h-primary-hover); border-color: var(--h-primary-hover); } .f-row { border-top: 1px solid var(--h-line); padding: 26px 0 30px; } .f-row-h { margin: 0 0 22px; } .f-cols { display: grid; grid-template-columns: repeat(5, minmax(0, 1fr)); gap: 28px 32px; } .f-col { min-width: 0; } .f-col > summary { list-style: none; cursor: default; display: flex; align-items: center; justify-content: space-between; gap: 8px; margin-bottom: 10px; } .f-col > summary::-webkit-details-marker { display: none; } .f-ch { display: inline-flex; align-items: center; gap: 10px; min-width: 0; font: 600 13.5px\/1.3 var(--h-sans); color: var(--h-text); } .f-ci { display: inline-grid; place-items: center; flex: none; width: 26px; height: 26px; border: 1px solid var(--h-line); border-radius: 5px; background: var(--h-canvas); color: var(--h-text-2); } .f-ci .ic { width: 14px; height: 14px; } .f-chev { display: none; } .f-col ul { list-style: none; margin: 0; padding: 0; display: grid; gap: 0; } .f-col a { color: var(--h-text-2); text-decoration: none; font: 400 13.5px\/1.35 var(--h-body); display: inline-flex; align-items: center; min-height: 28px; padding: 3px 0; } .f-col a:hover { color: var(--h-text); } .f-col a:hover > span:last-child { text-decoration: underline; text-underline-offset: 3px; } .f-li { display: inline-flex; width: 16px; height: 16px; margin-inline-end: 10px; color: var(--h-muted); flex: none; transition: color var(--h-fast) var(--h-ease); } .f-li .ic { width: 15px; height: 15px; stroke-width: 1.6; } .f-col a:hover .f-li { color: var(--h-text); } .f-col a[aria-current=\"page\"] { color: var(--h-text); font-weight: 500; } .f-bar { display: flex; flex-wrap: wrap; align-items: center; gap: 8px 24px; padding-top: 18px; border-top: 1px solid var(--h-line); color: var(--h-muted); font: 400 12.5px\/1.4 var(--h-body); } .f-copy { font: 500 12px\/1.4 var(--h-mono); letter-spacing: 0.02em; color: var(--h-text-2); } .f-links { list-style: none; margin-block: 0; margin-inline: auto 0; padding: 0; display: flex; flex-wrap: wrap; gap: 4px 20px; } .f-links a { color: var(--h-text-2); text-decoration: none; display: inline-flex; align-items: center; min-height: 24px; } .f-links a:hover { color: var(--h-text); text-decoration: underline; text-underline-offset: 3px; } @media (max-width: 1080px) { .f-cols { grid-template-columns: repeat(3, minmax(0, 1fr)); } .f-head { grid-template-columns: 1fr; align-items: start; } } @media (max-width: 720px) { .f-wrap { padding: 32px 16px 20px; } .f-head { gap: 14px; padding-bottom: 24px; } .f-site { font-size: 20px; } .f-row { padding: 14px 0 16px; } .f-row-h { margin-bottom: 6px; } .f-cols { grid-template-columns: 1fr; gap: 0; } .f-col { border-bottom: 1px solid var(--h-line); } .f-col > summary { cursor: pointer; min-height: 48px; margin: 0; } .f-chev { display: block; flex: none; transition: transform var(--h-fast) var(--h-ease); } .f-col[open] .f-chev { transform: rotate(180deg); } .f-col ul { padding-bottom: 10px; } .f-col a { min-height: 40px; } .f-links { margin-inline-start: 0; } } .itile.ccf { border-color: transparent; font: 14px\/1 \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Noto Color Emoji\", sans-serif; } .row.cty { gap: 7px; min-height: 26px; padding-block: 2px; align-items: flex-start; } .row.cty .itile.ccf { width: 16px; height: 16px; margin-top: 1px; } .row.cty .r-t { font: 400 11px\/1.35 var(--h-mono); letter-spacing: 0.01em; color: var(--h-text-2); white-space: normal; overflow: visible; text-overflow: clip; word-break: normal; overflow-wrap: normal; hyphens: none; } .row.cty:hover .r-t, .row.cty:focus-visible .r-t { color: var(--h-text); } .row.cty .arrow { display: none; } .onp { display: none; position: relative; border-block-start: 1px solid var(--h-line); background: inherit; } :host([data-stuck][data-onp]) .onp { display: block; } .onp .wrap { height: 40px; gap: 16px; } .onp-l { flex: 0 0 auto; } .onp-list { --onp-fs: 0px; --onp-fe: 0px; display: flex; align-items: center; gap: 2px; flex: 1; min-width: 0; margin: 0; padding: 0; list-style: none; overflow-x: auto; overflow-y: hidden; overscroll-behavior-x: contain; scroll-snap-type: x proximity; scroll-padding-inline: 40px; scrollbar-width: none; -webkit-mask-image: linear-gradient(to right, transparent 0, #000 var(--onp-fs), #000 calc(100% - var(--onp-fe)), transparent 100%); mask-image: linear-gradient(to right, transparent 0, #000 var(--onp-fs), #000 calc(100% - var(--onp-fe)), transparent 100%); } .onp-list:dir(rtl) { -webkit-mask-image: linear-gradient(to left, transparent 0, #000 var(--onp-fs), #000 calc(100% - var(--onp-fe)), transparent 100%); mask-image: linear-gradient(to left, transparent 0, #000 var(--onp-fs), #000 calc(100% - var(--onp-fe)), transparent 100%); } .onp-list[data-fade~=\"start\"] { --onp-fs: 40px; } .onp-list[data-fade~=\"end\"] { --onp-fe: 40px; } .onp-list > li { flex: none; scroll-snap-align: start; } .onp-list::-webkit-scrollbar { display: none; } .onp-list a { display: inline-flex; align-items: center; height: 30px; padding: 0 10px; border-radius: 5px; font: 400 13px\/1 var(--h-body); color: var(--h-muted); white-space: nowrap; text-decoration: none; transition: color var(--h-fast) var(--h-ease), background var(--h-fast) var(--h-ease); } .onp-list a:hover { background: var(--h-hover); color: var(--h-text); } .onp-list a:focus-visible { outline: 2px solid var(--h-accent); outline-offset: -2px; } .onp-list a[aria-current] { color: var(--h-text); font-weight: 500; box-shadow: inset 0 -2px 0 var(--h-accent); border-radius: 0; } .onp-n { flex: 0 0 auto; font: 500 11px\/1 var(--h-mono); letter-spacing: 0.08em; color: var(--h-muted); font-variant-numeric: tabular-nums; direction: ltr; unicode-bidi: isolate; } .onp-prog { position: absolute; inset-inline-start: 0; inset-block-end: -1px; height: 2px; width: var(--onp-p, 0%); background: linear-gradient(90deg, var(--h-a), var(--h-b), var(--h-c)); transition: width 120ms linear; pointer-events: none; } @media (max-width: 760px) { .onp-l { display: none; } .onp .wrap { height: 38px; gap: 10px; } } @media (prefers-reduced-motion: reduce) { .onp-prog, .onp-list a { transition: none; } } @media print { .onp { display: none !important; } } :host([data-a11y~=\"readable-font\"]) .h, :host([data-a11y~=\"readable-font\"]) .h * { font-family: Verdana, \"Atkinson Hyperlegible\", Tahoma, Arial, sans-serif !important; } :host([data-a11y~=\"dyslexia-font\"]) .h, :host([data-a11y~=\"dyslexia-font\"]) .h * { font-family: \"OpenDyslexic\", Verdana, Arial, sans-serif !important; } :host([data-a11y~=\"letter-spacing\"]) .h * { letter-spacing: var(--readabler-letter-spacing, 0.05em) !important; } :host([data-a11y~=\"font-sizing\"]) :is(.main .menus, .net ul, .inl, .crumbs, .onp-list, .end) { zoom: var(--a11y-font, 1); } :host([data-a11y~=\"highlight-links\"]) a { outline: 2px solid var(--readabler-color, #ffda00) !important; outline-offset: 2px; text-decoration: underline !important; } :host([data-a11y~=\"highlight-focus\"]) :focus-visible, :host([data-a11y~=\"highlight-focus\"]) :focus { outline: 3px solid var(--readabler-color, #ffda00) !important; outline-offset: 2px !important; } :host([data-a11y~=\"highlight-hover\"]) :is(a, button, summary):hover { outline: 2px dashed var(--readabler-color, #ffda00) !important; outline-offset: 2px; } :host([data-a11y~=\"dark-contrast\"]) { --h-canvas: #000000; --h-elevated: #0a0a0a; --h-sunken: #000000; --h-hover: #1f1f1f; --h-line: rgba(255, 255, 255, 0.55); --h-line-strong: #ffffff; --h-text: #ffffff; --h-text-2: #ffffff; --h-muted: #f0f0f0; --h-accent: #ffda00; color-scheme: dark; } :host([data-a11y~=\"light-contrast\"]) { --h-canvas: #ffffff; --h-elevated: #ffffff; --h-sunken: #ffffff; --h-hover: #e6e6e6; --h-line: rgba(0, 0, 0, 0.6); --h-line-strong: #000000; --h-text: #000000; --h-text-2: #000000; --h-muted: #111111; --h-accent: #0000cc; color-scheme: light; } :host([data-a11y~=\"stop-animations\"]) *, :host([data-a11y~=\"stop-animations\"]) *::before, :host([data-a11y~=\"stop-animations\"]) *::after { animation: none !important; transition: none !important; scroll-behavior: auto !important; } :host([data-a11y~=\"hide-images\"]) img { visibility: hidden !important; } :host { --h-code: \"IBM Plex Mono\", ui-monospace, \"SFMono-Regular\", Consolas, \"Liberation Mono\", monospace; } :host(:lang(ar)), :host(:lang(fa)), :host(:lang(ur)) { --h-sans: \"IBM Plex Sans Arabic\", \"IBM Plex Sans\", \"Noto Sans Arabic\", \"Segoe UI\", Tahoma, \"Geeza Pro\", sans-serif; --h-body: \"IBM Plex Sans Arabic\", \"IBM Plex Sans\", \"Noto Sans Arabic\", \"Segoe UI\", Tahoma, \"Geeza Pro\", sans-serif; --h-mono: \"IBM Plex Sans Arabic\", \"IBM Plex Sans\", \"Noto Sans Arabic\", \"Segoe UI\", Tahoma, \"Geeza Pro\", sans-serif; --h-code: \"IBM Plex Mono\", \"IBM Plex Sans Arabic\", ui-monospace, \"SFMono-Regular\", Consolas, monospace; --nx-lh-body: 1.8; --nx-lh-heading: 1.45; --nx-weight-heading: 500; --nx-weight-strong: 500; font-synthesis-weight: none; font-synthesis-style: none; font-variant-numeric: lining-nums; text-justify: inter-word; } :host(:lang(ar)) *, :host(:lang(fa)) *, :host(:lang(ur)) * { letter-spacing: 0 !important; text-transform: none !important; } :host(:lang(ar)) :is(code, kbd, samp, pre, var, data, .nx-code, .nx-uni, .nx-num, [data-nx-code], [data-num], [class*=\"-code\"], [class*=\"-uni\"], [class*=\"-num\"]), :host(:lang(ar)) :is(code, kbd, samp, pre, var, data, .nx-code, .nx-uni, .nx-num, [data-nx-code], [data-num], [class*=\"-code\"], [class*=\"-uni\"], [class*=\"-num\"]) *, :host(:lang(fa)) :is(code, kbd, samp, pre, var, data, .nx-code, .nx-uni, .nx-num, [data-nx-code], [data-num], [class*=\"-code\"], [class*=\"-uni\"], [class*=\"-num\"]), :host(:lang(fa)) :is(code, kbd, samp, pre, var, data, .nx-code, .nx-uni, .nx-num, [data-nx-code], [data-num], [class*=\"-code\"], [class*=\"-uni\"], [class*=\"-num\"]) *, :host(:lang(ur)) :is(code, kbd, samp, pre, var, data, .nx-code, .nx-uni, .nx-num, [data-nx-code], [data-num], [class*=\"-code\"], [class*=\"-uni\"], [class*=\"-num\"]), 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src=\"'+o(e.img)+'\">':'<span class=\"acct-av acct-av--i\" aria-hidden=\"true\">'+o(t.charAt(0).toUpperCase())+\"<\\\/span>\";var a=e.img?'<img loading=\"lazy\" decoding=\"async\" class=\"acct-av acct-av--l\" alt=\"\" width=\"36\" height=\"36\" src=\"'+o(e.img)+'\">':'<span class=\"acct-av acct-av--l acct-av--i\" aria-hidden=\"true\">'+o(t.charAt(0).toUpperCase())+\"<\\\/span>\";var i='<a href=\"'+o(ta())+'\">'+o(R(\"myProfile\",\"My profile\"))+\"<\\\/a>\";if($.notifications!==false)i+='<a href=\"'+o(Pe($.notifications||\"members\/me\/notifications\/\"))+'\">'+o(R(\"notifications\",\"Notifications\"))+\"<\\\/a>\";if($.messages!==false)i+='<a href=\"'+o(Pe($.messages||\"members\/me\/messages\/\"))+'\">'+o(R(\"messages\",\"Messages\"))+\"<\\\/a>\";if($.settings!==false)i+='<a href=\"'+o(Pe($.settings||\"members\/me\/settings\/\"))+'\">'+o(R(\"settingsPrivacy\",\"Settings and privacy\"))+\"<\\\/a>\";var r=l.querySelector('#wp-admin-bar-logout > a, a[href*=\"action=logout\"]');if(r)i+='<a class=\"acct-out\" href=\"'+o(r.getAttribute(\"href\"))+'\">'+o(R(\"signOut\",\"Sign out\"))+\"<\\\/a>\";return'<details class=\"acctm\"><summary class=\"acct-pill acct-pill--in\" aria-haspopup=\"true\" aria-expanded=\"false\">'+n+'<span class=\"acct-lbl\">'+o(t)+'<\\\/span><\\\/summary><div class=\"acctm__p acct-panel\" role=\"group\" aria-label=\"'+o(R(\"yourAccount\",\"Your account\"))+'\"><div class=\"acct-who\">'+a+'<span class=\"acct-nm\">'+o(t)+\"<\\\/span><\\\/div>\"+i+\"<\\\/div><\\\/details>\"}var ae=C.menus||[];var y=C.context||null;var M=C.network||{items:[]};var m=\"<style>\"+st+'<\\\/style><div class=\"h\" part=\"header\">';var ct=M.show!==false;if(ct)m+='<nav class=\"net\" aria-label=\"'+o(M.title||M.label)+'\"><div class=\"wrap\"><span class=\"eyebrow\"><span class=\"rule\"><\\\/span>'+o(M.label)+\"<\\\/span><ul>\";for(var pe=0;ct?pe<M.items.length:false;pe++)m+='<li><a href=\"'+o(M.items[pe].u)+'\"'+(M.items[pe].title?' 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:where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n1ef7ogx.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 id=\"nx-sec-field\" 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 Banking Nexus<\/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\">Model and AI risk<\/h1><p class=\"nx-scene-lede\">Banks rely on models to grant credit, set provisions, price products, compute capital and detect fraud, and a growing share of those models use machine learning. <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> is the potential for loss or poor decisions when a model is wrong or misused. This page sets out how model and AI risk arises, how validation and governance contain it, and which supervisory and legal frameworks now apply to automated credit decisions.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/globalriskalliance.com\/banking-nexus\/contact\/\">Make an enquiry <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\/banking-nexus\/topics\/\">Back to Topics<\/a><\/div><\/div><\/section><section id=\"nx-s-1-sec\" class=\"nx-section\" data-hue=\"finance\" 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\">Model and AI risk on the record.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-es-fig\" data-es-layout=\"console\"><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\">Banking Nexus \u00b7 topic<\/span><\/div><ol class=\"nx-register-rows\"><li><a href=\"#nx-sec-question\"><span class=\"nx-register-n\">01<\/span><span class=\"nx-register-k\">The question<\/span><span class=\"nx-register-v\">4 mechanisms<\/span><\/a><\/li><li><a href=\"#nx-sec-field\"><span class=\"nx-register-n\">02<\/span><span class=\"nx-register-k\">Field<\/span><span class=\"nx-register-v\">hexagonal field plate<\/span><\/a><\/li><li><a href=\"#nx-sec-indicators\"><span class=\"nx-register-n\">03<\/span><span class=\"nx-register-k\">Indicators<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">7<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-sources\"><span class=\"nx-register-n\">04<\/span><span class=\"nx-register-k\">Sources<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">6<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-decisions\"><span class=\"nx-register-n\">05<\/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\">06<\/span><span class=\"nx-register-k\">Methods<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">4<\/span><\/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=\"climate\" aria-label=\"The question, Exposure, loss and capital, Indicators, Sources\"><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=\"The question, Exposure, loss and capital, Indicators, Sources\"><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-1\" aria-controls=\"nx-sec-question\" aria-selected=\"true\" data-key=\"p1\">The question<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-2\" aria-controls=\"nx-sec-audience\" aria-selected=\"false\" data-key=\"p2\">Exposure, loss and capital<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-3\" aria-controls=\"nx-sec-indicators\" aria-selected=\"false\" data-key=\"p3\">Indicators<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-1-tab-4\" aria-controls=\"nx-sec-sources\" aria-selected=\"false\" data-key=\"p4\">Sources<\/button><\/div><section id=\"nx-sec-question\" class=\"nx-section nx-band-panel\" data-hue=\"climate\" data-variant=\"band\" 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\">The question<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">Model and AI risk: how the risk develops.<\/h2><p class=\"nx-lede\">Credit automation and validation. 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=\"M22 12h-2.48a2 2 0 0 0-1.93 1.46l-2.35 8.36a.25.25 0 0 1-.48 0L9.24 2.18a.25.25 0 0 0-.48 0l-2.35 8.36A2 2 0 0 1 4.49 12H2\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Drift and regime change<\/h3><p class=\"nx-p nx-mt-1\">Models learn from past data. When the economy, customer behaviour or products change, relationships shift and accuracy decays, often quietly until losses or complaints reveal 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=\"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\">Opacity weakens challenge<\/h3><p class=\"nx-p nx-mt-1\">Complex machine learning models can be hard to explain to credit officers, customers and supervisors. Effective challenge, a pillar of model governance, is weaker when no one can say why a model decides as it does.<\/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=\"M16 21v-2a4 4 0 0 0-4-4H6a4 4 0 0 0-4 4v2\"\/><circle cx=\"9\" cy=\"7\" r=\"4\"\/><path d=\"M22 21v-2a4 4 0 0 0-3-3.87\"\/><path d=\"M16 3.13a4 4 0 0 1 0 7.75\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Bias produces unfair outcomes<\/h3><p class=\"nx-p nx-mt-1\">Training data reflect past lending patterns. Variables that proxy for protected characteristics can produce discriminatory outcomes, adding conduct, legal and reputational risk to <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 credit-risk\" data-tk=\"Nexus risk vocabulary\" data-td=\"The risk of loss from a borrower or counterparty failing to meet obligations.\" data-ts=\"NRS-C1\" data-tr=\"draft\">credit risk<\/a>.<\/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=\"4.5\" r=\"2.5\"\/><path d=\"m10.2 6.3-3.9 3.9\"\/><circle cx=\"4.5\" cy=\"12\" r=\"2.5\"\/><path d=\"M7 12h10\"\/><circle cx=\"19.5\" cy=\"12\" r=\"2.5\"\/><path d=\"m13.8 17.7 3.9-3.9\"\/><circle cx=\"12\" cy=\"19.5\" r=\"2.5\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Models interact and herd<\/h3><p class=\"nx-p nx-mt-1\">Many banks use similar vendors, data and techniques. Common models can produce herding in credit supply or market responses, and errors compound when one model's output feeds another.<\/p><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-audience\" class=\"nx-section nx-band-panel\" data-hue=\"finance\" 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\">Exposure, loss and capital<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">What Model and AI risk means for exposure, loss and capital.<\/h2><p class=\"nx-lede\">The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-au\" data-au-voice=\"finance\" data-au-n=\"1\"><figure class=\"nx-au-c\" data-au-fig=\"scenario-pathways\"><h3 class=\"nx-h4\">Scenario pathways<\/h3><p class=\"nx-p nx-au-what\">How Model and AI risk could be stressed under the scenario families central banks and supervisors use.<\/p><div class=\"nx-au-fig\"><svg class=\"nx-au-svg\" viewBox=\"0 0 560 214\" role=\"img\" aria-label=\"Combined transition and physical pressure under three scenario families\" focusable=\"false\"><line class=\"nx-au-ax\" x1=\"46\" y1=\"190\" x2=\"450\" y2=\"190\"\/><line class=\"nx-au-ax\" x1=\"46\" y1=\"16\" x2=\"46\" y2=\"190\"\/><path class=\"nx-au-ln\" d=\"M46 155.2l80.8-38.3 80.8-13.9 80.8 7 80.8 10.4 80.8 8.7\"\/><text class=\"nx-au-t\" x=\"458\" y=\"133.1\" text-anchor=\"start\">Orderly<\/text><path class=\"nx-au-ac\" d=\"M46 155.2l80.8-3.5 80.8-13.9 80.8-73.1 80.8 10.5 80.8 19.1\"\/><text class=\"nx-au-t\" x=\"458\" y=\"98.3\" text-anchor=\"start\">Disorderly<\/text><path class=\"nx-au-ln nx-au-dash\" d=\"M46 155.2l80.8-7 80.8-10.4 80.8-13.9 80.8-20.9 80.8-27.8\"\/><text class=\"nx-au-t\" x=\"458\" y=\"79.16\" text-anchor=\"start\">Hot house world<\/text><text class=\"nx-au-t\" x=\"46\" y=\"206\" text-anchor=\"middle\">2025<\/text><text class=\"nx-au-t\" x=\"126.8\" y=\"206\" text-anchor=\"middle\">2030<\/text><text class=\"nx-au-t\" x=\"207.6\" y=\"206\" text-anchor=\"middle\">2035<\/text><text class=\"nx-au-t\" x=\"288.4\" y=\"206\" text-anchor=\"middle\">2040<\/text><text class=\"nx-au-t\" x=\"369.2\" y=\"206\" text-anchor=\"middle\">2045<\/text><text class=\"nx-au-t\" x=\"450\" y=\"206\" text-anchor=\"middle\">2050<\/text><text class=\"nx-au-t\" x=\"40\" y=\"33.4\" text-anchor=\"end\">high<\/text><text class=\"nx-au-t\" x=\"40\" y=\"172.6\" text-anchor=\"end\">low<\/text><\/svg><\/div><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Scenario family<\/th><th scope=\"col\">Transition risk<\/th><th scope=\"col\">Physical risk<\/th><th scope=\"col\">What a stress test asks<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Scenario family\">Orderly<\/td><td data-label=\"Transition risk\">Early, gradual policy<\/td><td data-label=\"Physical risk\">Lower<\/td><td data-label=\"What a stress test asks\">Can the book absorb a steady repricing?<\/td><\/tr><tr><td data-label=\"Scenario family\">Disorderly<\/td><td data-label=\"Transition risk\">Late, abrupt policy<\/td><td data-label=\"Physical risk\">Lower to medium<\/td><td data-label=\"What a stress test asks\">What breaks under a sudden repricing and credit migration?<\/td><\/tr><tr><td data-label=\"Scenario family\">Hot house world<\/td><td data-label=\"Transition risk\">Limited policy<\/td><td data-label=\"Physical risk\">High and rising<\/td><td data-label=\"What a stress test asks\">Where do physical losses concentrate in collateral and insurance?<\/td><\/tr><\/tbody><\/table><\/div><figcaption class=\"nx-caption\"><span>Scenario families as defined by the NGFS; the curves are an illustrative combined pressure index, not NGFS variables or forecasts.<\/span><\/figcaption><\/figure><\/div><div class=\"nx-chips nx-au-fw\" aria-label=\"Frameworks cited\"><span class=\"nx-chip\">NGFS climate scenarios \u00b7 Network for Greening the Financial System<\/span><span class=\"nx-chip\">IFRS S2 Climate-related Disclosures \u00b7 ISSB<\/span><span class=\"nx-chip\">TCFD recommendations \u00b7 Financial Stability Board TCFD<\/span><span class=\"nx-chip\">Principles for the effective management of climate-related financial risks \u00b7 Basel Committee on Banking Supervision<\/span><\/div><\/div><\/div><\/section><section id=\"nx-sec-indicators\" class=\"nx-section nx-band-panel\" data-hue=\"climate\" data-variant=\"split\" 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\">Indicators<\/span><\/div><h2 id=\"nx-s-4\" 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\">Model inventory coverage<\/td><td data-label=\"Unit\">count of models by tier and validation status<\/td><td data-label=\"Cadence\">quarterly<\/td><td data-label=\"Source type\"><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> management records<\/td><td data-label=\"Label\"><span class=\"nx-chip\">REPORTED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Discriminatory power of credit scorecards<\/td><td data-label=\"Unit\">Gini coefficient or area under the curve<\/td><td data-label=\"Cadence\">annual<\/td><td data-label=\"Source type\">Model validation<\/td><td data-label=\"Label\"><span class=\"nx-chip\">MODELLED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Population stability index<\/td><td data-label=\"Unit\">dimensionless<\/td><td data-label=\"Cadence\">monthly<\/td><td data-label=\"Source type\">Model monitoring<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Calibration gap of default predictions<\/td><td data-label=\"Unit\">difference between predicted and observed default rates<\/td><td data-label=\"Cadence\">annual<\/td><td data-label=\"Source type\">Back-testing<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Overdue validation findings<\/td><td data-label=\"Unit\">count by severity<\/td><td data-label=\"Cadence\">quarterly<\/td><td data-label=\"Source type\">Model risk reports<\/td><td data-label=\"Label\"><span class=\"nx-chip\">REPORTED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Approval rate ratio across groups<\/td><td data-label=\"Unit\">ratio of approval rates<\/td><td data-label=\"Cadence\">annual<\/td><td data-label=\"Source type\">Fair lending analysis<\/td><td data-label=\"Label\"><span class=\"nx-chip\">ESTIMATED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Overrides of automated decisions<\/td><td data-label=\"Unit\">share of decisions overridden<\/td><td data-label=\"Cadence\">monthly<\/td><td data-label=\"Source type\">Credit decision logs<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"indicators\" data-nxf-kind=\"indicator\" data-nxf-resource=\"nexus:\/\/gra\/A02\/topics\/model-and-ai-risk\/#indicators\" data-nxf-title=\"Indicators\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-sources\" class=\"nx-section nx-band-panel\" data-hue=\"finance\" aria-labelledby=\"nx-s-5\" role=\"tabpanel\" data-band-tab=\"nx-band-1-tab-4\"><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 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\">Federal Reserve and OCC supervisory guidance on <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> management (SR 11-7)<\/td><td data-label=\"What it gives\">Expectations for model development, validation and governance<\/td><td data-label=\"Licence class\">Public domain<\/td><\/tr><tr><td data-label=\"Source\">PRA supervisory statement on model risk management principles for banks<\/td><td data-label=\"What it gives\">UK principles for model identification, governance and validation<\/td><td data-label=\"Licence class\">Free, Bank of England terms of use<\/td><\/tr><tr><td data-label=\"Source\">ECB guide to internal models<\/td><td data-label=\"What it gives\">Supervisory expectations for internal ratings-based and other internal models<\/td><td data-label=\"Licence class\">Free, attribution<\/td><\/tr><tr><td data-label=\"Source\">EBA follow-up report on machine learning for IRB models<\/td><td data-label=\"What it gives\">Supervisory analysis of machine learning in <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 credit-risk\" data-tk=\"Nexus risk vocabulary\" data-td=\"The risk of loss from a borrower or counterparty failing to meet obligations.\" data-ts=\"NRS-C1\" data-tr=\"draft\">credit risk<\/a> models<\/td><td data-label=\"Licence class\">Free, attribution<\/td><\/tr><tr><td data-label=\"Source\">US Home Mortgage Disclosure Act data<\/td><td data-label=\"What it gives\">Loan-level application and decision data used in fair lending analysis<\/td><td data-label=\"Licence class\">Public domain<\/td><\/tr><tr><td data-label=\"Source\">FSB and BIS reports on artificial intelligence in finance<\/td><td data-label=\"What it gives\">Assessments of financial stability implications of artificial intelligence<\/td><td data-label=\"Licence class\">Free, attribution<\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gra\/A02\/topics\/model-and-ai-risk\/#evidence\" data-nxf-title=\"Sources\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><\/div><\/div><\/section><section class=\"nx-section\" data-band=\"auto\" data-band-id=\"nx-band-2\" data-tone=\"alt\" data-hue=\"climate\" aria-label=\"Decisions, Core questions, Mechanisms, Methods and limits\"><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=\"Decisions, Core questions, Mechanisms, Methods and limits\"><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-1\" aria-controls=\"nx-sec-decisions\" aria-selected=\"true\" data-key=\"p1\">Decisions<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-2\" aria-controls=\"nx-sec-core-questions\" aria-selected=\"false\" data-key=\"p2\">Core questions<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-3\" aria-controls=\"nx-sec-mechanisms\" aria-selected=\"false\" data-key=\"p3\">Mechanisms<\/button><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-2-tab-4\" aria-controls=\"nx-sec-methods-and-limits\" aria-selected=\"false\" data-key=\"p4\">Methods and limits<\/button><\/div><section id=\"nx-sec-decisions\" class=\"nx-section nx-band-panel\" data-hue=\"climate\" data-variant=\"band\" aria-labelledby=\"nx-s-6\" 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\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Decisions<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">Who decides, and what the evidence serves.<\/h2><p class=\"nx-lede\">Banking Nexus 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\">Bank board and <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> committee<\/td><td data-label=\"The question\">What model risk appetite to set and which uses of AI are acceptable<\/td><td data-label=\"Evidence this page serves\">Model inventory, tiering and validation findings<\/td><\/tr><tr><td data-label=\"Who decides\">Independent model validation function<\/td><td data-label=\"The question\">Whether a model is fit for purpose and what conditions or limits apply to its use<\/td><td data-label=\"Evidence this page serves\">Back-testing, benchmarking, explainability and fairness tests<\/td><\/tr><tr><td data-label=\"Who decides\">Prudential and conduct supervisors<\/td><td data-label=\"The question\">Whether internal models can be approved for capital and whether automated decisions treat customers fairly<\/td><td data-label=\"Evidence this page serves\">Validation reports, outcome data and governance evidence<\/td><\/tr><tr><td data-label=\"Who decides\">Data protection and market surveillance authorities<\/td><td data-label=\"The question\">Whether credit scoring <a class=\"nx-link nx-term\" href=\"https:\/\/docs.therisk.global\/organization\/systems\" data-tc=\"Systems\" data-tk=\"Nexus Standards\" data-td=\"The twenty Nexus systems, NXS-CMD to NXS-LAB\">systems<\/a> meet legal duties on transparency, accuracy and <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 human-oversight\" data-tk=\"Nexus risk vocabulary\" data-td=\"Arrangements that keep competent people able to understand, monitor and override automated decisions.\" data-ts=\"NRS-C1\" data-tr=\"draft\">human oversight<\/a><\/td><td data-label=\"Evidence this page serves\">Technical documentation, impact assessments and testing records<\/td><\/tr><\/tbody><\/table><\/div><h3 class=\"nx-h4 nx-mt-4\">Outputs this topic produces<\/h3><ul class=\"nx-list\"><li>Guides to validating machine learning credit models, including explainability and fairness tests<\/li><li>Comparisons of model risk management expectations across jurisdictions<\/li><li>Research on herding and concentration in AI vendors and data<\/li><li>Briefings on how the EU AI Act and similar rules apply to credit scoring<\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-core-questions\" class=\"nx-section nx-band-panel\" data-hue=\"finance\" data-variant=\"split\" aria-labelledby=\"nx-s-7\" 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\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Core questions<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">Shared questions the industry asks.<\/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\">Do models perform as intended?<\/h3><p class=\"nx-p nx-mt-1\">Whether models remain accurate and stable outside the conditions they were built on.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">02<\/span><div><h3 class=\"nx-h4\">Can decisions be explained?<\/h3><p class=\"nx-p nx-mt-1\">Whether credit decisions made with complex models can be explained to customers and supervisors.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">03<\/span><div><h3 class=\"nx-h4\">Are outcomes fair?<\/h3><p class=\"nx-p nx-mt-1\">Whether models produce unjustified differences across groups.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">04<\/span><div><h3 class=\"nx-h4\">What happens when many banks use similar models?<\/h3><p class=\"nx-p nx-mt-1\">Whether shared models and data create correlated decisions.<\/p><\/div><\/li><\/ol><\/div><\/div><\/section><section id=\"nx-sec-mechanisms\" class=\"nx-section nx-band-panel\" data-hue=\"climate\" aria-labelledby=\"nx-s-8\" 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\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Mechanisms<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">How the risk arises and transmits.<\/h2><\/div><div class=\"nx-section-body\"><p class=\"nx-p\"><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> arises from errors in design, data or use, and from using models beyond their intended scope. It can cause losses, mispriced risk and unfair treatment.<\/p><p class=\"nx-p\">Machine learning can capture complex patterns but may rely on spurious correlations, degrade as conditions change and resist explanation. Validation must test not only accuracy but stability, bias and behaviour in stress.<\/p><p class=\"nx-p\"><a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 data-quality\" data-tk=\"Nexus risk vocabulary\" data-td=\"The fitness of data for a given use, judged by accuracy, completeness, timeliness, consistency and resolution.\" data-ts=\"NRS-C1\" data-tr=\"draft\">Data quality<\/a> and representativeness shape outcomes. Models trained on historical decisions can reproduce past exclusion; alternative data can widen access or introduce new biases.<\/p><p class=\"nx-p\">Herding is a systemic concern. If many lenders use similar models, vendors or data, they may tighten or loosen credit together, amplifying cycles.<\/p><p class=\"nx-p\">Generative AI introduces new risks in customer service, coding and document analysis, including fabricated outputs and data leakage, which require controls and <a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 human-oversight\" data-tk=\"Nexus risk vocabulary\" data-td=\"Arrangements that keep competent people able to understand, monitor and override automated decisions.\" data-ts=\"NRS-C1\" data-tr=\"draft\">human oversight<\/a>.<\/p><\/div><\/div><\/section><section id=\"nx-sec-methods-and-limits\" class=\"nx-section nx-band-panel\" data-hue=\"finance\" data-variant=\"band\" aria-labelledby=\"nx-s-9\" role=\"tabpanel\" data-band-tab=\"nx-band-2-tab-4\"><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\">Methods and limits<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">How evidence is gathered, and where it stops.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Method or data<\/th><th scope=\"col\">What it shows<\/th><th scope=\"col\">Its limit<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Method or data\">Independent validation<\/td><td data-label=\"What it shows\">Model soundness and limits<\/td><td data-label=\"Its limit\">Depends on validator independence and skill<\/td><\/tr><tr><td data-label=\"Method or data\">Back-testing<\/td><td data-label=\"What it shows\">Performance against outcomes<\/td><td data-label=\"Its limit\">Past conditions may not recur<\/td><\/tr><tr><td data-label=\"Method or data\">Fairness testing<\/td><td data-label=\"What it shows\">Differences across groups<\/td><td data-label=\"Its limit\">Choice of fairness metric matters<\/td><\/tr><tr><td data-label=\"Method or data\">Monitoring for drift<\/td><td data-label=\"What it shows\">Changes in performance<\/td><td data-label=\"Its limit\">Detects problems after they emerge<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><\/div><\/div><\/section><section class=\"nx-section\" data-band=\"auto\" data-band-id=\"nx-band-3\" data-hue=\"climate\" aria-label=\"Methods, 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=\"Methods, Questions\"><button class=\"nx-tab\" type=\"button\" role=\"tab\" id=\"nx-band-3-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-3-tab-2\" aria-controls=\"nx-s-11-sec\" aria-selected=\"false\" data-key=\"p2\">Questions<\/button><\/div><section id=\"nx-sec-methods\" class=\"nx-section nx-band-panel\" data-hue=\"climate\" aria-labelledby=\"nx-s-10\" role=\"tabpanel\" data-band-tab=\"nx-band-3-tab-1\"><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\">Methods<\/span><\/div><h2 id=\"nx-s-10\" 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\/banking-nexus\/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\">Credit decisioning with explainability \u00b7 Early warning and transaction monitoring<\/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\/banking-nexus\/stem\/probability-statistics\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">02<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Probability and statistics<\/span><span class=\"nx-mledger-role\">Estimating default and loss parameters \u00b7 Operational loss 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><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/banking-nexus\/stem\/financial-engineering\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">03<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Financial and risk engineering<\/span><span class=\"nx-mledger-role\">Expected credit loss modelling \u00b7 Counterparty exposure and valuation adjustments<\/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\/financial-engineering\/\" aria-label=\"Canonical \u00b7 STEM Commons: Financial and risk engineering\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/banking-nexus\/stem\/financial-economics\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">04<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Financial economics and macro-finance<\/span><span class=\"nx-mledger-role\">Macro-financial stress scenarios \u00b7 Credit cycle and buffer calibration<\/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\/science\/financial-economics\/\" aria-label=\"Canonical \u00b7 STEM Commons: Financial economics and macro-finance\">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\">Validation tests a model against the data a bank holds; it cannot fully anticipate a change of regime. Explainability tools approximate a model's behaviour and can mislead. Fairness has several definitions that cannot all be satisfied at once. Public data rarely reveal which models banks use. Banking Nexus describes validation practice and supervisory expectations; it does not validate, approve or certify any model.<\/p><\/aside><\/div><\/div><\/div><\/section><section id=\"nx-s-11-sec\" class=\"nx-section nx-band-panel\" data-hue=\"finance\" aria-labelledby=\"nx-s-11\" role=\"tabpanel\" data-band-tab=\"nx-band-3-tab-2\"><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\">Questions<\/span><\/div><h2 id=\"nx-s-11\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>What is model risk?<\/summary><div class=\"nx-answer\">The potential for adverse consequences from decisions based on incorrect or misused model outputs, whether from errors in design, data, implementation or use.<\/div><\/details><details><summary>Is machine learning allowed in regulatory capital models?<\/summary><div class=\"nx-answer\">Supervisors have not prohibited it, but internal models must meet requirements on explainability, data, validation and governance that complex techniques can find harder to satisfy.<\/div><\/details><details><summary>How is credit scoring treated under the EU AI Act?<\/summary><div class=\"nx-answer\">AI systems used to evaluate the creditworthiness of natural persons are classed as high risk, which brings requirements on risk management, data governance, transparency and human oversight.<\/div><\/details><details><summary>Does GRA validate banks' models?<\/summary><div class=\"nx-answer\">No. It validates no model and assesses no firm. It researches validation methods and shared risks.<\/div><\/details><details><summary>Is AI in credit decisions harmful?<\/summary><div class=\"nx-answer\">It can widen or narrow access, depending on design, data and governance. Research examines both effects.<\/div><\/details><details><summary>Why is herding a concern?<\/summary><div class=\"nx-answer\">Because correlated decisions across lenders can amplify credit cycles even if each model is sound on its own.<\/div><\/details><\/div><\/div><\/div><\/section><\/div><\/div><\/section><section id=\"nx-sec-nr-gateway\" class=\"nx-section\" data-hue=\"climate\" 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's quarterly publication. 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