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xaKCg2qUaGEzauHC0OLVEc1Bq84XVEfs2hGKjP77VjQnF+6qqJhfXxXcsNt2R1Ho9ebryydE79k25\/SiovOb1xja954unvjqnbBN29Oyjm+JzklpLDzYlHN2X33komOxhXOuxKe+iFajEYPsiP\/8ucPsV2WEzTOPPbFpVaopWlp1KufKSr+03EvFbm3XTxTldF\/ZW1WwelFSUnH0nMra2Iao1b7lW8Pid58\/kXrq+JY7Rbm39p8q3TV74bKO1IBjCVvbo5u3XSmJu1E3JcFzTWTc1Dk7J81FqCvrxKWiMp9TsV2t6NULwUdL2rKWkoZdwWfTc1ZsyissrwuZUlyvazmWv7Fozwf5nevSzjfNqWgtbMiKXpeyun72kqqs7rK81nEVhRkxLXE1iwKjG14sddmA5g\/0Clxqi+atOV3aXVG2d\/O+dfmXiy7vbdp3Nipue+D0kuPHz24paU86t1h\/YlHzqYLcgpaiwj0lWdsiy7pRU1nFob3dtSda13VlL8nyz2psTQgv3R\/cmrVxUnn8nnjkcXrzcuvkwOFzI\/090cSQ2NTEm+3VlwMPnMvvOtaAHC7dLY1Nr0o8emJdbmN9zLrje+edaViZ15gcm5K6s\/HY5cotEScrmvd1RNbVdtbGbl4acb6htcDn6H6\/pLMtNXtn7a89XHokonLlzAWum2eNcXXaMKq5OaOz+XxRfPvVxVvHn8zPGp5eP35b5nnfQ2f2V7eX+ocd3LKv+Nj1v3uvLKgpik08Oi03s\/ZmZX7BqfBtx6pvLC8rSj1Y1ug+afGp8ANHjx8oTz2Ruakmb3LkiuWxTh6LZM8h65r4bZP3FZaV5u3b7Zt8uvHYkWMZZzqK8+JntR6tDz6WeDQv5cb51mPGkunnzr689254iTEl4tyaCzWG+eFVmbt21V3IaK7P6ag6ebhxb0tF266MpEvJJXvbD+oWT1kTvkk3Z95zizriEreuHVnelr8zK644Lyz9Vnpt4oS\/b+++VpE0o2JzbVZZ2on0s7VL0iZVpAVtLT9lTLuUVl11NjF6x4H8mOaUgIzMws3VHxdvTGus3rshaU5Y+j6vlKiQwXpNwCSXFSssfMPHLT3evK05as4W17P2JWeac5ftv1o9eWdZxsGMvOqolPiu53aFlI6\/UlgXVJFxKKFqX0wsSogqKzzul5tZcCRHO3fpDMfI6LBNpWvOReRUlsaklRyaW3ulAqGpiyYNnLts8uzIWYblBW2dV04faHjh9oKu\/PqcNxujV3XdjNGkXZvjfTjnRkHhmbcWFuWMr67eWNOV2VCpqePz9zef2f\/y1qquivRZR0+uSDqS9+K63TUtmWmBp+8uGtwaYouGI0TskZPdmBB7NCcrrrypqPZm2fytq9eMazuwK7e9tbxj8478V5r884sjC9JKr+6MqcrMXp1asuVybOXZAwVnt5weossr2FUdUzVoW97FzMbUg4Vri2MvNXufqT2nixuKVlm7mKHFaAWyp5Mne6PlJVGJA66GnUi6Unp096nEwAuvlrWVHyyOSzuTWnr46HN5dftqDs9vzQ7cu7AsrSKueW9R5pabjftbQyJjNt441RQ7fV1M5r4N142j21IOlZx\/TscNdffzddUumubpHu0ud5i5XLax6eBrS1fW5BlfKqoqnBVVXaras+eV1xfsTVy85PUnPx6+df+h8FOBv2fmxUUVJ8tDUFr+3pIjkSWFnSm3S3LbXinOyt3cGNLqUh9sO2C82Sw75PDcoADEn9EhO7RgktZkiOOgiag6Cs06u710d55vx\/4rQ2vjiqt2z2ypvlJx77MbvU8\/FJ4IJ5PS63JaS\/JXvL3rXENS9+LWzKzghI0Ls\/Jaj7W9XpRV0TIrQqd3HIS8Rir4ey82PPQVWiLfV\/hzU1fLLKYs3BZztKL4xNGcq0vr3KuKcrpmTi+vHisIS778SBDu3Cr\/5n5v7atV5fvqIud0XG47XLHAmBu0eVdGd2TR4em3utveiFs\/eyEaqVXZLEFD0JVTx69\/\/Z7w8smetDef147H9jZo2pjw8euPo6NbqvZUVu4uMHYHJI5Hs14ThG9uCA9u1Qkv\/vNeoRDUsSMuZFNd5l2UMaG8uGZXWM3G4vi1iWs7EJrrpXbzXjDAe8asqSjiqfD3j4W2b4TSi19+1DDNk0yYMhY5jeavtq5Kud6dv7sy\/eLCv0+3TVo4Pl8ouDD64fmy94S7wufvXG3Jqa4p6QzrursVtzYe2r197cvHutvPpLycvn6yI5qxwW46GoMQ2jzztdc\/zv\/xu7fLPxeE51t0CRsH62yIfPSqqeVBd+raTnWuz+zIbFqxbtWUgY+EQ99cOf75ly8X3ul98YcnR09cvLwzr2vPjpjtnXXHY1aX22ek7S7eVrMtLA4ZvMKmKMY4ONlTNGlb\/nvvC59f+2XChJPdSxyQJ5ocgKYitFGtRnVHN1RVr5609PTKPf4WaB76JOyFe1eED+qEVxreuDCzsvJltLO4Ore58HjxkXfTD+\/dG7P5aKEzijZZtxwtkLl5qB1m+08+uashPO5yybXUw10VxZlnJphPDxvLz0AOyGc4GjpxRlN+dNeN9cjeE03xGP9ZR\/eP7\/xY1Him\/vgKVNBy+ExmyfZ9wY11WwdOOjgj7HjQa82OkbEuaJz3OrRhKFrltmw7aly6OyK3bEfqhM5LnYdOVVzJsES2KGaBjx1GYxw9Z1K0dORAhBLM0aY18wNmL18gdAjrr+73b8w+24wOnLy78PCiq\/cqcouiyk9vja1v7UB+KAwtGDAcwbPAOHjE\/rcSm0rS8lPPRR7KPZ8Vd6HlUpDWYbUm1hehRWMRQjZopoMOJYe6I4T2+A8dv3pU6IZJmxPO+WTP6i7ZeVYVVXNhz7TQsAkzh6J5CKmHoLlT1i5bg3zQ8OWj\/LZs80AvpM81nLsdVXZxe3TphfroK+XnN5qM9NroM79hLJLrbMYNQp7IXLdsyiY0VR8+y2nR2rVLsG\/RRcfTxYml+w8uiax4rsl2PLVBAWixHxqkWz5mQXiEi6XcVjNx7uxRkzvi0l\/fUB6SfuBMZdP1E\/s7D+QVn5yHtCvGDzq9sapm\/yQHhGYi20mOUwJshiiWITRROc\/TNc43FbmjXRmVJjtqcpqjJnmvnoZQ5JLFAdTTuG7lxrE2syb4mQZN8t+E5tR2ZJT737lcUTQzagQq23upflNp0LBNQQdPGKMueqQ1Zu6qzL863FGJ\/M2QzSyF3\/xloxZH+kbNsV7uMzo42L+oqCItb+gSowIt9JevW7Jx9TD7hW6z3cchD\/mysCHrvOa\/uB6FZ2Vlh+1NaQk\/VJXrmb8ie2FNy87D6xsXH9xZe9l\/S\/d245196adVwyYZ7JwHeS8wmb8gYdScKSrN+Bn2CE30RZZJrusXoGkLJyC5dfSMVSs99RPQuNmuU4ehaauRi3Vu+wvNOerkE2WlR\/ZnDauOrkg9VJ99ISU97eS6He7Gdxej5L2JuTeuDRvm4jXJxwmhkch2wmg8YQEa7jTW3m3JrFEqhDborbzJxKHTkF7tb65QjUND0EZkvcEJjTOgm9syQrZcXagpbgnNSM9tX9RW3FhX3HCqOKelqyvvkNXzeaRmb2J36iKEHM0WrXZEBhvzkaqpHuMDh9jKl6ARCt\/RU71ZLc6aMBxZIje0xkE3ct3kAasnrkYT1nkeK8pVlCUUl5w2D67NKz+xeMHYsmN3X5l\/ZE+BoTa92KnkVsrlpsKoF0s3IMWEKQihkWQCosjJfbwCeSD9sAkcmoSGIIul5mOQxySTEQM2zJ+v5pagYVHL1q1eM6EhrzKvsWDDltU1DR1h7ZVLdzUFzErN3X6m6kpeVxLa3J10qvX8mym1+7d\/tMYPLdOhsWgsGjFjtDtClq4IubghHRqNHCfqXZcP9po4xkk7wA05DkSTw5D57BANmuh7ce+hytobhbtnL4tqeP7kzvTIjsHbG+tbl67VZ6dWlLxQ2fi+awPqLC040YEcNs5Y7bfQgFah0Sh4VVJiSXrTjWvL\/PHCe5++diNgtoWFdrpmELfS39NkKpemWjZYFb5uYlBcy5ElyS0n8zZf30Ozlo8vO9KdVldYWvVSYfL066u4edfLK87Un4vJLqk7s634b51zkktIbWL20oKKzLUxNaHFrRGXs42+wu4XhdkhIwMU310RXhHevoUsBriiYUvWrQ86X11dez7\/xpzYwsyGTVP3FHVXdxbFGMumhu6rXrInvLRrxLGL27oil1+KvXPqdldpUfDxrZWLM67l7G66WLAutz7Pu\/ZwfNOKpT8Kd+clrPEejQ6994nw6pMvgoMDggI9o0eh9NZuh\/jmtTkN9d2382d23q7MW12yZUfPj4+e\/1QQrr0j3M9Nfje2pDA121ibN+zo0obkQ3c2Z+WXRWzNyi9snJ609Jpx2ImYelvhnaff7hTe+KXjkXDjh0uv3RUUvh7z56F54eEdIXeP5dScrVvXsFnfFdrW0F1+qizjkx9vCsKPwR\/e2X778yOtu+Oah7W3FUWjnLQt62+Vt3dMCtmeurc+sqrC\/kRyDdp3rPFC75OvhReERuHtDz\/77sujwm+bXddNcfZBKL0k6+XS8\/a7ViWsqMutOXCgLcpiVcz+y5fqbgrCl69fvPpJz2uXo7OvpJ\/Ia0roXtHRvPbgmSu7p2VlzE3bfqO7sHNOePuRpYe7lr\/x8mPhSZ7Q8uDhzs6jwm+fCJ+jiNBVKOn5ldlhWSX+L+2blDQ29dKYoIKSeaH7tqXkXhcE4eTHD1+\/2HRZSM5ojf\/nZRS3PzC13A9lZe0\/YlpfWZa7rz6jsTQxOb69ruDIoTvC80L2P764\/ZLw5dc\/nBE6Ri+NRDHGmxdOnitM35988XzElIPzw8tVHRfON3U+n3l2yZnez7+6\/U3X91ff\/aJMEITGorK8t6pPn0JljYnXQjcfXL0o8i1t8szZ9gfcd9ZXVwU0HK7p+PDaehRYViF81lsSgmomTEF+HdknXy5KW7\/0UlTxmcKdTSfWXivbXb0rN\/6FbcdvfXf03UPC4cwU4cGlTz58vWJpZnptW076ofD67qTK0Nystn2xaQ3zDofuqTjaXRJal9x0ozrb9nAWKrXanJe5seroxnzk2NA9teDA+eS0vOtte+P2HimK3VmT3db23PPBN8M6i4+99MOt2z++WnZJSBa+\/+rWC5eH7ZsXNLvuRn3n+vwyj4qkpOWZO4qSV4dta9tkW5Ges1TVXLwvOTz34PmU6tprxbk1N4wX0g+X3K6MiCxuOH72ysm\/Ne3IKMovvtmwq6m0YFzknraDu1HR6y09wo0l+bcObUrxzK7sXtNeU3Gw8NSe6YX70tLX7K9O6iwt7m5q2NK2sGjvgcL1cz33DN5ZMaOpIDOz4Fpb95iWpFeNx+p9ZqGM6K7ik+U3g8s2qlasLay\/cLguObi2sWx\/8YaZbf6Xb986mD4j55BnZWpK0tG4ppxz3aX73p5VcSLfMeF6VfbkhszmsmWnk+sTd5RVrquu3jqoqDmzrv7WwWtHT7Vk52R11DV3HjXU5McaK0dtP15yOnbX8hf2x+55MX\/FyDvHJi\/NvbDV52\/ntp2tQNGpTa8VhZXvS3+r5lXDwX1llakt27Obaw9lb4wo37d1eVNSXlrC4qK8A6cPNmS\/2BDTtacm4XLK7vamVv0y\/70JxbE5mye3V2Sg3NbjGS2lR67l7Sla2Jawc0Lb+jUHilOnbb5VfqijbFRlecbBmpLE2u69RbOOxV1oXpqx5Oaa7qOVp3KKYuq31B3MS5+al7svu6qi5f09Z\/Y2Tt1yqqh4levhiMn7d0xZX32hdOfWhBMvJdc27itKfyEtZ3vtmg3RebsmrkndvS+lKb4yLTbqxKZTzZWZpYdLWo+cTUhOTT64ZOves10NyV3RDp1N+1Oqt2YkOHd3JayZnFx64c6FzJac0sKOY+1Fx68sLy9tPjAnKz9v95tn0tPSOluqlqAXdiVWJh6q2VZyJmXvhC3b\/Dpv7miv3BSaO2VDSNvBirm78lpCT287n3Fs48yiY9lJR9L31pgWxS7bmLO5vdsJtS7bkD7lqGcELljX0nY8qfxQVXpW1cXIjOJZrSev5OYtCbi4vSs4Iye\/Y\/3m4qbzm\/c17\/nydkrpjv2pRZ2l56dnF1XMQSlpxS8febEzKc064mjdwNRza3Ycre1IaL98IjElM\/y19uWdTWcW7KwtnlYXU9xtmjf+havTG0o7j4eV7DlekHtmw\/G3di+q6yzb0JJcmlIwv7C4at\/OY9mVLVnZuy7X500Mamu7fXj0xZjGquUt+zJWHt93MuhoW\/Ox9IKtljXx2zcmbus+VJhScW5ac13uuuTjrbXnm\/Rr5rTltOa0GTYVTi8MC\/fPv7TsxfgdL5qU7uwuQ9mLVgaGJM7IS2xbG36squLEsqqi5dtWVbYn726+vWDf3YoLOalJR+KyhjaeWFxY3Z6VEuK\/tfLY8SaUntGc01ygb14R3x19uuHssnrPAxGX6kZ079p7IOB6eePt2YWFFrcv76842FLRPLvJPXJrYlhqXEl+WdRVY\/Ox+fsDS41LUNnhlFHldUcTNu7eEXvqdHrexiPh5+rK4idvqzl0M2hz0p6EubnHSrwObjx4bPntq\/l1rSW1poGh9XtqYzK3Jm6r+KA1u7yi8tC6xpaCzj1t+yu7Wk6s31hff6l2a9bhwoIjJ\/2fy8o6M3l\/4uU1nXF7DjQkpGVXHjo2sfpyzObG1pMF11tSS8+dO7Cz8sTylXvCM05k3zlevz+w48Lu4pkpDTs3n5jXtr3mxSVb\/A4d7qr59MhGnjcdaj2IpzIapD82Qo4xfv3Nh9aUoxQjjBHCcpWaIIxtrWwwR5W8xkplIsMYYxMTc7WcQwhhQjDhd61cLBs2VEawlUxFMMYUA2RiQginkJtSTinztlxoKceYhM9O5DAhShkvxxhhQk1kPM8rOCWmnG6YtZmZFQfU48aNk8lZEMoRwk+PNFCFmsdYznMQn+MowpgjHOE5Qig1pTbESq4gVOExdiiBsJjIOYqJQunEy9UjB7uZaOxnhagJphyL6lp\/GtIlhONkFFNzRw2WyXjoGZbzhFCNhVpJCKbwAmHCsf8SDnICXRAhRMGbyGVy4mw7w+U5mUrhIlc5RjqNtDQD2bBscLA5RZiq7Rzs1JSTqUyowtLGwsaSwzIzmZnDbI1KQTBScDzlGAcoySkVlIjaIUR5Ba+WKzkTpaXMnnr5nXKykTkrRqhkLD7mLSwJ5u3cTTQyU4WKYkIUA2w97a0JdvKysDCzoRwlhKOUEIIxwRgRrFJaUYwJYeGxXE6pysSJk3PWcooVxrP2CuKgCXQwZyJghDlzTqG242VU7rx4AEGEH+uxeehASlUOFuZmakhBrRvobDLATkYo5hFP7GwHEYwp0wyTgXYywvODeQ5TQvDIzG+M4wnGMp7IzTREQSlRWZo7DZYRzPF2o8xAepmZDUcwpQSSpoTIHFbwSs7JlCdOZhZYLrOzGKLieI0ZxRyhmMplnNokQSYjMo4qRkxKcJEhhHmKOTM5pkTlU3+7tiNjiKPCUmnjNNSGEKoa4jRp9HAlRygIw3Fq+xm8\/YDQMTLCaQaqLU3tVKZKTmm1y1Gp4BSYUIXKUqXChFdzlFeqFAqoa55Q3lRBLMw++\/7pg8dPfyk7UdGlN1cb5pkTIvdu\/6nTkyOYU5tSolBxrIEJR4hqfMBQu2FDTK3NbUYlXXVT8jyPEeJkchkHo04VNkM0ULJUpiIKTKBu7vX09jztffLt5\/d6en5YMcqRx2Z24avf\/2SLCeVMZApqbhitwJiaWprBBHCZ5+k6eBin5NXE1NbFnKccgRHkFJTn5GqFhldSrJTZKDRKquaVSkr5W\/d7e3qfPvrHTz2C8KOXXEGIpcPmeXPHEoIIJ1cotHGLFAhRSinm1GNihyplKg1oSNWctUZhqlSJo0x4wiksvO0GUmJpbcfLZbyFmYWZUjMoov7vv\/76zddffHtfEHobKcGYp3JKeKgs2cDhJnaTJikJxpxSRTgzW1dLBaUyQjgN8BHMmQ+AZQemJ1HazlqsoAhbWVvLLRQcb+XuZq8xHzBs06e\/\/vLrtz8\/6un97QN7OWElC8sWR1Sjtg6W246whgCwPA32HqXgmYPMScnxckI0IyxgIoMDxjLbuaYcxpaGFfa2cko4jUZpMdZOqcq79taH3\/\/y69Neofe98TIZZUsAkQ3m1WYGDhNeRogp8GJTtVpGCcxgRxc5iyq3ZfpQzRBYs0w0MCfkVoPlclh9qEKOCeZ5i9UXvv\/qu2+e9PT2fOnPK03lShWPqVWgJYflHCW8hhAnDiGes5KpKGGrzvAFKkw4Oac2UzAeiwBrDnOcjIfJzvOEA6E5UzM5rzS3tSr4++OHD3979LCn51HnFF8Hc3MLjcLJ2WgJkw385OawWMuVljxb8WGxdlQQTDiiMFk0wJkSMmDxcBnl1PYeQ4cOMaeY8DA7efPBJpzSQk2WPRR6Hvz64Lf7D36+e2zzUIVCxlE1p+Bl4sJpY2WHqYxTObmaYkJ5TIlC5mphyskpofarjky1wZhysMrysxKnjp0+hsPUREGxTGOlUpn7efqkPBbg6e19+uTRk6dfa2E+EZ6qLazMqQLyl6mJ0pnDqsFOhOPkmKMmnNLUhIfvi7lX\/XRrTEzNTAkh3Nbs9YOGWisJr1IoMZHxFGs80s7\/2ivGF3p7e3p6ev7hTTHF0H2ZCQ9qwNDK7HiisFSKyxqRmcgtVaZmlMMqfqjMhFCeo4STy4dqOKwwMyOcQqngZFaUICvj\/R5B+D1+ryD0Prw5huOIjDdTyhQc5S1UGOoVY6IwseXRs0fu7u8IFYrtrG2pXGHCy6iaU8HocBZK3pQfYTJonNcGiw1vQfI9gtDb84hp1CsIPfeyJwxdNGsMBOXU9hzlBnMYUZUJfPOs+x5sp7WEQiHD1BbQW8rJLMxU0IRyHFWRASNPnP74p0ePIeMvwup\/NN6Zeu\/JI5HgySvOFgOfs2LFPMZFIVN7z1RhOU\/RH+GtkQwWWJmMKDk5lanlaqWM4+S8+C0n9mYvvPXkUd+w7re2tr6D7ty5cyfqp\/tsLHo\/LFk9e4qMx7zCVk2VVJ6\/et5pe+t+D0KUKCxtKcKct8lgXq0215ja2w9SEKLwW1rf\/fBRb68AwX7t87\/Dns\/EsX78XYRawSsQJiZyTobxb++\/9Yk3c5AQEKIw0RBE7E54qzjFECX7uHKEj\/y5p5fpwJ5NvzeA5ok9fcX0zSRXpYZ9zIkMk2\/v\/fo47U5\/AljXOI5gk6WHzTCWDRxkylEi57ghX0H7p0\/64odbSwl+EDslCL3vHjjijhGmvMKRkk\/f\/r7n+zvPCFBffMTJHTEm5koOISKzlLFqHrX8vUdQLn1l2RtE0TNBEVK+8UTo61nv054HZXYcz5uoKH30sEfofY\/0i08wosphlIdhkvEK2XBLU5ncQnfqxyc9T4WnrNR7e3sextuwnRZiewma8Bsb8r6+9Xz2tyNJ6XcvdPcw7zaxA8ybKFw0mChd1NBaZifniEJOiHXgg8ewEPQ1f\/z0+2g5Vcg42AgwDmLy4ROgFX5\/eh599bjnKZsl3yRM4+7cuYMVCmJiMX2UkiJO7c1hzHlUpO\/JquhauPrjJ8JTWATEpvff+OXJq46yIRpKeJ5tzjDG5rd6ent\/ftIrSJ8PHvWyqnpwxsiPCTiyTzWAs1ZaqZDaejWPZUNuffjj108f9zx40tsr9Dz9om9J6H30zce\/zVdjExuOPttsYYRU\/+wVHj7+9eFH3\/3Ri+9+hd97e3p7n\/763S+\/3fZLu\/ySA6+ST3YaKFdUvv+YoSzmkwfffvMzK8Invz7++YWTIzVyM0u2wA6240EgbPFqz6PzZ3ImDFl+9ty9Jz1iWzYkUNVPfv3mp4df\/v2rB1+E2etsLOT8sOn\/\/IWFfvr4Sa\/w5MG39++zse158Nujb4vWzBimokrCc3KNk8qc8FQjt4+8Ujps5ZCBPCdT6xteSGx\/6fHPz\/rR2\/v0l58+\/\/Xn3l7h6ZMffnn7woEZu5t+gi+r0Nv7y2\/3n9z\/7ZdecaHs7Xn89PGdcCcz3tSaJ1Ru6b16vbVSplJqVBo5J1Ooh1qaywe7O1OFariV8Mca++TBg6c9LERvz\/efPYLNTQ9bIYXe3vs9z+at2N2e7iMurrzZyHlDeUo4paWbpYZn+2TY38l4a7X3io0DYKsi\/K4RC\/x7AfevAoH1o+8nG6\/zNpzC3HTgwNG2akoVynGjhxDxrCTjqHyQXm01XK+WP4svidP7r9H7vep98vBJb89vRS68Yuh0c7Vq4BAznuf5AZsCFRhhdu5wVcnMeIwI2wIK\/\/nTL\/7Dnx\/29vx9A+UwJ7cdMkSjkHOEyOU+HXUajIjMhCq8fFUcpghWFIwgfk+vJP2nvT29P7Ml7MHFbx897f1dkF6R4sn9x48eZVmyjytxtLVWqWQyM2uisdbzcIy04mXrj\/tATyjh4KDyyxf1x7+73\/u09\/Hjpz\/\/8N1vb3Xlho+Y3\/X46auwYMx92iM8\/Dry\/PTdGx6L8Z8+fPTtXSex3qlKaeM11gbOd7zaSsbJeKdp7hrNKBXs4+xUZjDndg4xN5kw9uTtS+tirs1zsBxlBts8zK97WQXxB\/7aI\/zWt7q+JzzpfdrzpOdhldJExVEC+xbMDfe041V9WoiLHVIoCRwPOYV4DoYDjaOTJVVpOMzZ2wxQa8xkcj6GLanY3vySui++7f2enqe9T3t+8CfswATjR9RD5GwbTHG\/DyDGMiu1OSZm6ymFzQZRKU2UKkKIymnwAMVCzxFUwz6rSPoFbHz064NeQfhxHMZYqbSSKSghChXGxNZKSVC\/LyzMA54ndP1dwptBb8xtXAcPogSTAdMGUu9JWkyQ9IvJGNJ6fngq9P7oZ87BRsnKdPVgS1MrFyIzc3eQ\/yk+HKc5tYZ\/rpo3rLfBSO440c7UDARVW48hlhoFRqj\/R\/\/OnTufP\/7p3ru7B8hklGIqmzrn3CRHRxs7TDSDHDi+f3zEDugKTMnYaFc1xvajJtorLKmKMx+8UK8AffGf4iN+\/qOeL9ZoMMJqa7UCE95uia25g405WxLgSC7xZRLJeB4TGh49REF5W3trJaeWjTZdONjfgsP42X5L5WDDMkNEGfl+b89dtgmi5jA75XIFb2KpYKPLPpH\/Ep\/KiFxuymNMVZa2NtamjmYejjlLtml4TmEnl8spxlzQteKxUHlYY2G58PVPbGDFIkoLIi4FRAaHAdBBSeXoD0VZfM7WXCk3dWHXGmaOjkreztFMwanlShiZAXK1mULhtHRt5ZqN1uYythPmR0xkRw6Z3QY1bPgQIrzaylQFBx+Ot2P3Rfh39TFn4+Ri4uTO3lKN3IQfoHS0UVCq4ahc6cRbWzramrh4BNjz5hp13\/UH+wxi3mSETMV+VausTRVmPJSomTUl8iEWKjUnfiqJvKD7mAwmBrvN4KmKKqjSEt4QynEamQOnkNuNmbl8qMpSxT+LT9hpT2WMDLeEL5eL9WBN3OEAuXgYIhozTjEydpBCRTCSW89f4sNjTgHHX4QI5rGCaJQ8Iaa8OUxMOVHxKk4tk8mtzeFCivUZUdjmUns3b+0w64HeMbYybOkNVyIQH2s0cplN+BAr+1FWMqVm5rjRBFMllcH4wbmDYkooR9U83IFgyjlqTIiclylVVnCNJaOgORyiMO\/obmcq02hc7XmOzvd3FqXDiI4a7sCPHmujshug0ZgOUMh4Tg43M5Qo1SroupKjPOdITWBECDZVKzFRaHTDYgdrCDFfOV9FsEpuzzvbGHgedpdmPCFELmMJwklFNtjEgrey5XmNi5oQM1NzMU\/KE56z5Cmm2hUj5JgggojpaDWxcTEjnJVKqdGaA\/bSLku4RdOoVpnYsOkvd4KhUrLrQ1as8oHUglcQ+P5SzFk6qOBETQmVyXmqsXTg5LaDB7AzOJaNiHIgVCODXTOv0DqoiMz2mL85UZhgS7PtphNM1VAZA9R2PEwAlaktIZwywJpiouSxTOHCUc7B18GUo1TGE9jGIqwapJHb6T1h8UeYt7TlCbGScQSOMiYaghWOkzVsHC2clYRX2nMcz7srLAhPeWKpMNMoLDgHa8p0NXcYQzDvOEwttzIfP1LNqzRwXlKqLCnhVOZKXuk2djBRcjzmOCXVwBXCcBXPm1iam8E4axw0nMxigIxynIXcFlY6Ys7zbt75GhdbOQwLJ5epCKJyW7nKRO7uouBhE8xRHhMiN5UpCFVt3DWOyDkTzFMLpbsKtjeAKdSO7D5SCVtmuVwpVznJ5USsTWJpPYIzN9fwlGh4+A5jOQiHEa+Uy2VwIaKALyqlVEWp+XffROKBLhPgs2ZqDYudAk7YmFi5q6BSeDnPcRzhVJMGmCuJeOqzdRjO2yrNZaZKBxmFK10HXsZ21QT99fz1\/PX89fz1\/PX8n\/fgvuuZ\/9Xo\/1sUuP\/zvxv9300gifq\/wfCneP9ugn8N9m9l+L+N9O9j+I\/C\/JsI\/uMg\/5aB\/n8M8D+vpf+k8f90Tvznrf5H8f9Ljf77BP\/lJv8thv+e\/3+5xX+7w9JG\/2G\/\/nsDhv\/T5386b\/D\/i+ff9KH4t4b\/LzP8z1etf08V\/\/X89fz1\/PX89fz1\/PX8f\/zwyIAt0QDMIw5\/Kyjwx4IL\/lbwwTIUjC3RcxhwsD8RFuHvhDAsR9ewNWrDclSEvxPK8KfCCfy9cAsr0E\/YGv2d4WDfEz7GPwi\/YVfUjH1RDtaiLdgKbWftoL0rehOPR+cZLsa71te+iPkBP\/B9IqQwnjHoS+SNXkZj0DlkgS4iDr2NLNA3aCyyxd6oBwEONvQD+iPi4NeCvhYOo4+EG+gb4V2Ggx\/gYH8s\/IKg3wvRXbQWnUALUBXyQnWMB\/gWoUdoHfoYAS7yQx49DAe\/0SgLmaP9jAf4FqMVeD2ajBehUdgHabEWTce+aA1ejDLwBhSNAQcb9BB1mc78oB\/iOBiY7iK+huFggx6gSxIaj\/chZ5yEVHgdMmU8wLcNReB9aAHDwQYe4ANc9HvE8gYe4FOhPcQWGYkSLSA\/CkvIZ0I0+VHYS9yQnkxA9mQcIsQGyYgSORMb5EXcUCCZiGYyHGxoJ7Z3Zn4w\/jDe9wRT8oMwjOGinzOz\/yFMYjxLkTUJRE\/wUvQ5Ho++wsADfMvQNBKIxjAcbOABPsDBD+oF6gN4gG8X2keyUCTZiZaRILSKLEMJJAhl9f1cxeKJ+ULeSeQjWoO+pnvRRzQK3aRx6BzNQbdoPfqYvoi+oScR4GB30250m76Kimgrqqd5qIhuQ9vpLhRFS9F2egQV07+jenqJ4WBH01toB32vDwe\/ULSYbkIz6D60hFYyHPwAB3sm7URL6V3GD3mcpWtQHV3PeIAP+CEPwEX+1j6+bcyvkD6HttF5jAf4zlN7fJv2om76T9RAv0UlVIYbqSM+T2fiO9QVAw52CfXEjXQOBhz8oB+QdzT9Fe2gqj7ckeFgx9CheCf1xR\/Tx+hb+inTCXQBHuD7hI7G31JzhoMNPMAn4q+yfkDewAN8H9JJ6Cs6FH1ATdENaonO0rHoJvVj4\/E1XcJwsEEPUZexzO8MfSrUUoQKqQOqpW59uB\/DwQY9QBeI+xX9VfiAfixcp\/cEaAftHxEd4qkdekgI+pjI0JtkMPqEeKLHZCOS0ZkMB\/tNMh99QkIYDn5vkB+FbvKr0EFM0HkytA\/3ZDjYHWQSOk8Wo8HUCo2lj4VB9DOBp\/8UgAf4BtNpSEtHMxxs4AE+EQe\/N4SPyd8E4AE+Z9qIXGkWcqbxSE63osckH8npITSEvoZc6VmGg\/2EXEEK+lYfvpX1A\/J+i+xBn5JihoMf4GC\/TTrQPXKD1SPU5XS6FGnpSsYDfFCPUJeAi\/yNfXzxzA\/6AXkDD\/BlkrGomFigDPJUiCaCEEgcUAxxQ1lkNSohUxkOdhCZhWLIegQ4+G0kXwszyffCBCJHs4hTH+7GcLAnEG80i8xFoDfofpR8JBSTewLwAJ+o91CGgw08wHecVKMLZC86RqJQKYlDWSQblZJ6dJy8gC6QkwwHO5t0ozLySh8ex\/KF\/ILINhRLDjAc\/AAHO5i0ojhykekq1sV8Nt7AA3ygK+gLONhiHicZDn6QL+QHPMAXSb1REnVCm6gCLaIaNJ0OR4vpBDaPYT4DDjaMjzhOw5lfAL0vQH1BHUE9ifgEhov1NY2Nkzg\/ECqgXwtJ9HsBeIAP5oc4TxyYDTzAJ+Lg946wkH4gAA\/wfYnS0C8oAn2BlqKX0Qp0DW1Gr6BM9CU6hX5FFQwH+xpqQK+gMwwHv6vIH7WiGagKbUCtaEsfnslwsKtRHmpDzUiDjcgBz0Ua7IV+QeMZD\/CZ4FLkgHcyHGzgAT4RB79h6CU0ivEAnyn+BTnid5Epvol+Rc+jf6JP0W\/oATLDLtgRKzHgYH+FLPB9NAIDDn7QD8j7OnoNvYo+Zzj4AQ72dSSgV5E1NuC\/oan4IvLALWgAPsx4gM+AeeyHv0GAi\/yQB\/DdZH7QD1GnU4xvC9qNUlEwSkTz0Bq0CC1AkWgtSkVb0VG0FxUxHGzYd4j7j0jmNx9NRJ5oKhqNViFPFNuHpzIcbNh3wP5D1Bt0d0epyMB4gA\/0Bt0BBxt4gE\/EwW8QWo1cGA\/w1aDvUDt6E9Wgy2gvuo62ovdRGvoJ1aKBuB1RDDjYsO+A\/Qfgot9Rljfsj2CfBDj4AQ62uH8yxaC3WC8NrA6AB\/hEvT9n4yHyQx7Ad5n5QT8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type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-mount\" 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auto;padding:0 16px;font-family:ui-sans-serif,system-ui,-apple-system,\"Segoe UI\",sans-serif;line-height:1.55;overflow-wrap:break-word}#nxe-n1ef7ogx.nxe :where(*,*::before,*::after){box-sizing:inherit}#nxe-n1ef7ogx.nxe :where(section,header,footer,nav,aside){display:block;margin:0 0 32px}#nxe-n1ef7ogx.nxe :where(h1,h2,h3,h4){line-height:1.2;margin:24px 0 12px;font-weight:600}#nxe-n1ef7ogx.nxe :where(p,ul,ol,dl,table,figure,details){margin:0 0 16px}#nxe-n1ef7ogx.nxe :where(ul,ol){padding-left:20px}#nxe-n1ef7ogx.nxe a{color:inherit;text-decoration:underline;text-underline-offset:2px}#nxe-n1ef7ogx.nxe table{border-collapse:collapse;width:100%;display:block;overflow-x:auto}#nxe-n1ef7ogx.nxe :where(th,td){padding:6px 8px;text-align:left;vertical-align:top;border-bottom:1px solid;border-color:inherit}#nxe-n1ef7ogx.nxe svg{display:none}#nxe-n1ef7ogx.nxe svg.nx-i{display:inline-block;width:18px;height:18px;vertical-align:-3px}#nxe-n1ef7ogx.nxe :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 class=\"nx-hero\" data-layout=\"console\" aria-labelledby=\"nx-title-1\"><div class=\"nx-container\"><div class=\"nx-theme-toggle\" role=\"group\" aria-label=\"Appearance of this page\" hidden><button type=\"button\" data-mode=\"light\" aria-pressed=\"false\">Light<\/button><button type=\"button\" data-mode=\"dark\" aria-pressed=\"false\">Dark<\/button><button type=\"button\" data-mode=\"auto\" aria-pressed=\"true\">Auto<\/button><\/div><div class=\"nx-folio\" aria-label=\"Document reference\"><strong>A02 \u00b7 TOPIC \u00b7 model-and-ai-risk<\/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\">Banking Nexus<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">Established<\/span><\/div><div class=\"nx-accent-row\"><span class=\"nx-accent-rule\" aria-hidden=\"true\"><\/span><span>Topic dossier \u00b7 Banking Nexus<\/span><\/div><h1 id=\"nx-title-1\" class=\"nx-hero-title\">Model and AI risk<\/h1><p class=\"nx-tagline\">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. Model risk 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\" 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\/banking-nexus\/topics\/\">Back to Topics<\/a><\/div><\/div><div class=\"nx-hero-panel\"><div class=\"nx-register\"><div class=\"nx-register-head\"><span class=\"nx-eyebrow\"><strong>Dossier<\/strong><\/span><span class=\"nx-eyebrow\">A02 \u00b7 topic<\/span><\/div><ol class=\"nx-register-rows\"><li><a href=\"#nx-sec-brief-answer\"><span class=\"nx-register-n\">01<\/span><span class=\"nx-register-k\">In brief<\/span><span class=\"nx-register-v\">Definition and scope<\/span><\/a><\/li><li><a href=\"#nx-sec-question\"><span class=\"nx-register-n\">02<\/span><span class=\"nx-register-k\">The question<\/span><span class=\"nx-register-v\">4 mechanisms<\/span><\/a><\/li><li><a href=\"#nx-sec-terms\"><span class=\"nx-register-n\">03<\/span><span class=\"nx-register-k\">Key terms<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">3<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-field\"><span class=\"nx-register-n\">04<\/span><span class=\"nx-register-k\">Field<\/span><span class=\"nx-register-v\">H3 field plate<\/span><\/a><\/li><li><a href=\"#nx-sec-indicators\"><span class=\"nx-register-n\">05<\/span><span class=\"nx-register-k\">Indicators<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">7<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-pipeline\"><span class=\"nx-register-n\">06<\/span><span class=\"nx-register-k\">Pipeline<\/span><span class=\"nx-register-v\">Run graph<\/span><\/a><\/li><li><a href=\"#nx-sec-sources\"><span class=\"nx-register-n\">07<\/span><span class=\"nx-register-k\">Sources<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">6<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-decisions\"><span class=\"nx-register-n\">08<\/span><span class=\"nx-register-k\">Decision holders<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">4<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-methods\"><span class=\"nx-register-n\">09<\/span><span class=\"nx-register-k\">Methods<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">4<\/span><\/span><\/a><\/li><\/ol><p class=\"nx-register-foot\">GRA \u00b7 Established \u00b7 service level R0<\/p><\/div><\/div><\/div><\/div><\/section> <nav class=\"nx-index-strip\" data-nx-spy=\"true\" aria-label=\"On this page\"><div class=\"nx-container\"><a href=\"#nx-sec-brief-answer\"><span>01<\/span>The short answer<\/a><a href=\"#nx-sec-field\"><span>02<\/span>From a satellite tile to an exposure\u2026<\/a><a href=\"#nx-sec-question\"><span>03<\/span>Model and AI risk: how the risk\u2026<\/a><a href=\"#nx-sec-terms\"><span>04<\/span>Terms used on this page<\/a><a href=\"#nx-sec-indicators\"><span>05<\/span>What is measured, and how well<\/a><a href=\"#nx-sec-pipeline\"><span>06<\/span>From sources to decisions<\/a><a href=\"#nx-sec-sources\"><span>07<\/span>Where the evidence comes from<\/a><a href=\"#nx-sec-decisions\"><span>08<\/span>Who decides, and what the evidence\u2026<\/a><\/div><\/nav> <section id=\"nx-sec-brief-answer\" class=\"nx-section\" data-hue=\"finance\" data-variant=\"band\" 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\">Model risk is the potential for loss or poor decisions when a model is wrong or misused. Banks rely on models to grant credit, set provisions, price products, compute capital and detect fraud, increasingly with machine learning, so drift, opacity, bias and herding are governed through model risk management and validation.<\/p><\/div><\/div><\/section><section id=\"nx-sec-field\" class=\"nx-section\" data-hue=\"climate\" data-tone=\"alt\" aria-labelledby=\"nx-s-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Spatial finance<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">From a satellite tile to an exposure update.<\/h2><p class=\"nx-lede\">How satellite radar turns a flood into an exposure update. Synthetic scene; no real event or place.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><figure class=\"nx-fk nx-sf\" data-fk=\"geoai-eo\" data-gl=\"sf:geoai-eo\" data-sf=\"geoai-eo\" data-sx-credit=\"synthetic scene and schematic model\" data-sx-src=\"Synthetic scene ~ illustrative, not data\" data-sf-learn-views=\"pipeline pr\" aria-label=\"Interactive figure: the four steps of a flood mapping workflow on a synthetic radar scene, from the tile to the detected flood and an update of affected buildings. The panel steps through or plays the sequence.\" data-nx-z=\"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\"><figcaption class=\"nx-fk-cap\"><span>How satellite radar maps a flood and updates the count of affected buildings.<\/span><span data-honesty=\"true\">Synthetic scene and schematic model; no real event or place.<\/span><\/figcaption><\/figure><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"map\" data-nxf-kind=\"map\" data-nxf-resource=\"nexus:\/\/gra\/A02\/topics\/model-and-ai-risk\/#map\" data-nxf-title=\"Banking Nexus live map\" data-nxf-height=\"560\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-question\" class=\"nx-section\" data-hue=\"finance\" data-variant=\"split\" aria-labelledby=\"nx-s-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">The question<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">Model 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 credit risk.<\/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-terms\" class=\"nx-section\" data-hue=\"climate\" 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\">Key terms<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">Terms used on this page.<\/h2><p class=\"nx-lede\">Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Term<\/th><th scope=\"col\">Definition<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Term\">Model risk management<\/td><td data-label=\"Definition\">The governance, development standards, validation and inventory controls that limit model risk, as US guidance SR 11-7 sets out.<\/td><\/tr><tr><td data-label=\"Term\">Population stability index<\/td><td data-label=\"Definition\">A measure of how much the distribution of a model's input or score has shifted since development.<\/td><\/tr><tr><td data-label=\"Term\">High-risk AI system<\/td><td data-label=\"Definition\">Under the EU AI Act, a category that includes AI used to evaluate the creditworthiness of individuals.<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-indicators\" class=\"nx-section\" data-hue=\"finance\" data-variant=\"band\" aria-labelledby=\"nx-s-6\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Indicators<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">What is measured, and how well.<\/h2><p class=\"nx-lede\">Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.<\/p><\/div><div class=\"nx-section-body\" data-lv=\"register\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Indicator<\/th><th scope=\"col\">Unit<\/th><th scope=\"col\">Cadence<\/th><th scope=\"col\">Source type<\/th><th scope=\"col\">Label<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Indicator\">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\">Model risk 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-pipeline\" class=\"nx-section\" data-hue=\"climate\" data-tone=\"alt\" aria-labelledby=\"nx-s-7\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Canvas<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">From sources to decisions.<\/h2><p class=\"nx-lede\">The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-plate\" data-wide=\"true\"><div class=\"nx-plate-label\"><span class=\"nx-eyebrow\"><strong>Pipeline canvas<\/strong> \u00b7 Model and AI risk as a run graph<\/span><span class=\"nx-eyebrow\">Design, not a record<\/span><\/div><div class=\"nx-figure-frame\" data-scene=\"true\"><svg class=\"nx-figure nx-ui nx-dag\" viewBox=\"0 0 1200 564\" data-nx-dag=\"true\" data-w=\"1200\" data-h=\"564\" role=\"img\" aria-labelledby=\"nx-dag-a02-topics-model-and-ai-risk-sr117-t nx-dag-a02-topics-model-and-ai-risk-sr117-d\" data-nx-z=\"zVzJcuO8tX4VFLNJ6po0MXGoarnK11b6d8Ut9\/Xw\/+klTcESyxKpkJSHXmWZdR7ivkL2eZQ8SQoDRZCaQJPdyaLboCQenAHn48EHEJ+m7Kk4+7SKypLlKUimIyt9s6fRzI5cZJfZKokLe5lN2cKO0qkdJXaeFM92kUPo29OsLCzwmkzL+ciCngXmLJnNS9lWIh\/SpCxG1rpg+d0qitlN+lAw6+xTnOTxgoF4ERX8ay7rKWGLqQXit5EVWCB+F3\/ykeU6vnV69ulUSTz7tIzyZ5Z3VDbK8+zVAi8Je\/3f7G1kucAFAeA9sKc\/jyxfNL6NLGIBKf83aZdXXf+ijPMskOUJS8uRFa3LzC7KKC\/tnL2wXFi2isp5bZfqdjqyvgDe5TUIAAHXovPvwiwpvY9V9iJ5Yf8h01TfBvadyqGWs7isZcRR+hJpgwi5bj2MqEcskL9xvU7Vjft\/95QsFiNrnS9+\/7tuI\/gPG+EbrVZRyhY2l2gB7k8LvIv\/d\/buuVzAIkm10TyPktwuLPAGxX1vqLrpHYobwDuqbizZm9bzMkszsLaT9BmJrmEg+sbUAk9ZWtpF8p2NLOg61AL8TjtK43mWjywRKgssGM8Ru1hFcZLOeO64hC2ts3ydFuAUPEbpc5LO7JS9rfm19At3yOZCc9KnU95F2zlpNmV2Gc3A2i4f7cdoOmNCVRxAR2qL4MZVIdJQIZDRxHvNrkTb\/FshlCBfCcXYaToh2PLBMplOF2yXEyD3weX47urzBNw+TCrDZrUG5aMFplEZ2VFcJlk6sr5n2dJOUgvk2YKNrMd1WWapBcroMUmnTI6KKE8iexE9soX8PUhSa2uEz5OVMCUMfIdI\/9RDCRFHw03+BfcQOT4wwjB0fOkYcmxs7PeL63HH\/E\/lj9OZgU+yddnNKfyG\/V6hpBo1Q3jF8x04kFf+9be\/m\/rlKTF3Cf\/tfm+4YdsXWCTAR3yBfCccyBd\/vLo39cVqEb0bO0P8eK83AurxcdD0ByE8iz7gj8APKijp7Y+v1+ffdIfsMcCnW0M7dD84tAMXO3gg9a\/Pv9083IN\/\/gNc3+4G+VmeraUNSOYTDHA9JDF1oBYECNVzOjhkBpZPCSUu9BtGhKaPM4jkeLy9uwfXV5PxMfUxdYWu7yPLD+snuO861K8twAiZW+BtJIa4jxFXk8vx1\/Hkcjy5B7+eX19dnt9f3UyOGUQhcfztmLQt6hITimqR\/eLy+ebX8e3kfHJxNC6eHzoobMeF8Kca\/FhcvGAjsV9cHu422jcLXjadMSD\/VGUvR76iZCte1cirpzxbjqwkfVHXZTaypuxFTIjm1yydiWipihn6oUN9gIgHLgCCuLqAXt0MfdWsqnWbpdPOlW5drIt6d9sw+2mxmah0U+u0k59ow0\/CMxs\/xcVuN2FCHEiUPtgPqguMRBMSBLCHVPPnuambWt3c5B1wUxZ9yE2YupU+mLr\/NW5qqXXQTamYF2huChpu4uNn46VotdrtJuoGjg9FeC4AJai6IKFoctUo8lSzv5uEh7SKiYnap4sVbRSVEuzHmZwihdCpnge+U1caFDv65Asfm3wpqaV6yvhqegFDUYSZTLzOnpJ0mqSzQi+NPhxMPsqNg8kH0SaY\/OK\/JZhbVpgGE4Vw+GBi1x04mA3Tw4bpImYb25Plngh6PnZQqODBd\/3qwqN1M4SqOVAEj9gBYfNhvtQNWfIZzS5DAj5V85QhgQ+riwCJJoeYgFLV\/EmGoIYhQvWNIfm+qiREoXhoBRBcVBfckO0m5p76CTl11I7DWRW61VQY4VDLKoL0uWTHrBIukEJJYJxVjzmL4nmHnGrWlTkzqytdFzkEK1iELt1cQeL\/iMrSIIbHDDkcQuq7CsNawBjo8+mOIfRc13E7A2POpuyFLbJVhyjy2dhe63NWmoURe9VVGIimCKOLXNUePo6cka2I2WmWNo2qkpJ\/q095FLlzlb6wtMzydxClU1AmLK9sfl+xkcWbBasrgKhkI+vyZjJWnyzhyMpeU5aDNFqyafUpGlmCr9bkiVnlyPpjkhcl4ES8Mf+0reIJUHqdAGHvTvb7MXuTVABW9I5fz8OJ15iH+0F7CaMpas6iqaks5HWUpRHxbVkQ7RGSxNxjvBRR4AY1kkFHS6KlWnP0CzmzxftqboEyj9LiKcuXI0s0F1HJfk\/gCYL4D3KUY0AcGrs2BMiGDgWE\/18QwJsAOvSFxi6ANuJtW3xS2MTmbf7D718w8PkPgPiBvKXg30tB20BQRGkheQMI1varx5dluFOVuYi01hkgl3LWHin\/+uv\/V+l\/mJao3EjCI\/ByhJW4PL8\/vxvfH+sUNTr1TIiQMy3LutnkeybiN+l6eD1Jrndh4vgK54lGgns6CQ5p94UkSLEDlWAKm6HouIx0U7OO7VXsVcZDyFewJYUil7EFMucjC8vh2GLQD0IsbkBsTQMo\/LqUDyIxJqdZvF6ytGyAbBkVzwcRljc4ERwVxXq54hR+oSHtIlkmZaR\/+nGs3aXrCeAKmkCtLFaGg1tDecaQq8vrBbvIpRtBPwB6pfgG\/OJ58BL8gr8bQyVCtYp74LIdbGO41M3vC5n353d\/MsNLvVczzNyRN90NNMNPLQkNEBSFoYPJD0BQzFkE8hMRVGVUXFlSI6jhTRSZ3SQJyo49NW5q9nQA4PfS4RLgN9SfwsyLLI3ZqlxHC1Bk63SasqJo4PssKlkT328fJpOryWcN4ss543XLP\/8BpqxIZqmG7xypVyyd1o8Nhe9X9RfgJVokUzH+jLF+l94ngCt7AvJ1mibp7EhlLQhhSUC6eIDq2kyeeYWtyYN+D7jHvlsrFg4O91L8CXRDBfc+QAsKqC3+2dQc9HFYK4rcnaDfjrox6OtOILQf6H8+vx+bgb7eKw1NkLidSd2t85FJP1paGiA+IdSpltWxVzMjtEFufQDxiY8dVwkmfh\/EV6C0D\/SjOOZAs1bwyOGVYE8YFYvOxd6vXGl\/AJNVVsqbjqI\/kH+0XuVqwk4BB0D9L2u23hAUzeU7CeubRQAFjzfrMs6WrABRGi3ei+QYpv\/fw\/hhfKlB+mMUP9slK0oOpDWcP7I0nnMKqBgUzbfUraBcGW6K5IItHhDJD8n7CJJjRIdBctx4JAyK5Bj6AyI5X4LdheRbEe+MdJji\/wCOY89k+8qZnj7dLQtcoz42uWgC4RQ6tNq4SLTtMI1Vvw9BuOdAJZjSPhAuMeh42a5jsNhmYFJM67jbuukQW8LipEg2a0HN5VeJvPUapMKy89UqzzY1uGKi23IE6J4\/3P9yc3t1\/03DXcGdgzhbLpOyZEyD3jhLp4mYo4HsCawL1kTgz9kLy9Mojc35EqXpCajUOwHRupxneVK+H4ZcueA9HFdiKM8YcnV5vbgSijcb134EVyLFa1wJAv4cuhx5X6BrjLeU1lruoUtUrM2wSLe6N6s8vri603YdHkZavWczmqSVMN0NNKNItrLPAHNp6Dsk3CJKPL8vUeJh6OBwCKJkA0HHYbfKqU4cRuMmU7ZE7tfoymzvqJHD5vLhsoXUV8vVghkQ2lvFcZylZZ4tdB47nkfpjIFFNmvCMn8XzXitsNKnIq1Nql+5c2U4KDaUZwzFurxeUOyFm923PwKKpfh+tLUPaxX3rfJVMTYDKt3on0dW672aoXCVEd2tMoTfTXoZ4K4fuI7nbeFu\/1o3cKmDvCFw17TWrbJnBxTuv0luExsAPze71CSA1puiFGB9ydKkzJqbLsTz+Ah+TvPkqeQk14rlPA9l1brB0nKes2KeLabFx7FUqXYi3zk0g1K5d244SthQnjGU6vJ6UcKBh2vFhqeEpXiNEsYAwgW2KUAAA2x7xoAaBLWieyhhFWgz4NEN70sDf7m5HF+b4anerRkPvCtDuptoxgXX6WaArSGhDsJbVHB\/bA290AnwEFSwKbZW6WTI5arlP7lhriuB22BcG\/tNJbTm7X0XX1meZNMkBjnjb90foW85laXha5SmfInkKcvFrhgA9a1tTPGz7OPg2lKuImuFXqYIOwhVayjvIwjbj6rVsvBHULUKYQegajWE3UfVtqLdGYZ+IlGr92pG1G6lSnfzzNjaOu9MUJb6joe32Nr+WyxC33NcPARbqwfFDGONudoGxgr7u99F+5S9pIXNZRObb1mZ5KwraTBlgqQqNB5Y4nGc5VPwzFblxwFZatSFNlB7ugfc7mYo0Hy\/my6wF3MAXRRsJP0A6kDJ78cdQJfUSu4hD2SYzRCqYfTPow4a3RpudNMS4wO2GW4RrtPMZJMwdMPq0JBBGQTItx+Tn8kgbNLoOBuwTNJkGW2\/QCgOK6ocLx96QZ1EVDupiBDttImmkOVyxz5kIRLTytViP8nmtC\/+QtVGsJQLu8jliyKDyZU7OIRcHzvVXM4J+8qtHj9NyZj0l1yvOQrZIapOOhnAG7rWUGDTD5GMXYcM5mk5a2rKHcLPDY1JqI5Q+agv5GRP5gVSs+FaDg70kyukHFRlcocDwghSJ4Txxun+fEfSTQTV+e7rJ5NBpJ+fduxUEymLeK0nm\/GjiKiNXuD+6suYH83CCZKbyVg72wRcfLu43tSl2x6R\/oB8l7HwiNhuzB3C60XuEEoMTIG+BCzikY8+V+UxOZt3fo5pjF2Py+Y6q2Z3rbE8x2cIvX9tTWX2qU34KiVXWjS6q0zUQ763wq3l7336Uh9WblbN7jpTnw7l5ha3uU9r31XDWTS6a+y7Aw3n2w4EQQUHrdnzvj7Ptl+k3F3HlXkUP6ssVejlE+2UA\/1cRa1+awlZ2I9Rvl1T+ES9zavL9Knj7xZq5oHQdcyo6LNdLzgZeyEQc4pB\/IBIdTRgU2p3T0DdE9SFZn7Ytfnf2A9hTy9sKkEsn\/EtmT1HA5XVlIkX9m6hPOYC6tK+Q0Eremo3NOX2dQRCZm5oQftR46HXMwv0upq41Wkquty+pmNkOga2thMcNR95A8aeb\/4Md8jt6wBixhi3H5BHjcf+YKZTWk2odKn7DW\/Qj69NvrE64PLNrpStrl+VooqOfLWFk7CDAo\/6xEOB54W+b7Vrg1ScnSXQGqobVCFWtWWVgBpVQtNy+cqEDAtf9AtV+a6\/8bd9LgY6FGQ7SxtiK1242NDpRUdPbn7bf1xmPaHxibs1oyENOzrMaHyKBpnSXE3uvo4v7m9u+Xzmbnw9vrgfX4LJzeWeVY9tBlFcFXaZlAvWVM1rqYZ2vUbFn5+875lW0huaHny4ZBRhu\/ltMr5tdClGepIW6mgOq9aBW\/gCdiz6UHenLsdffdJeVelodhj2Mvtq8vXh\/m6P3Um6WvNj780ND832FKiKUdgrTyHpZjWFPYP9cH\/A7GxddrS7rc8eu6tjxsBrUs5Bwc+aT8r3jqajfgEf\/3p1OdYOLW3Zzl6SKROboMyNR6HhsmPCXqvDN0CWAsmEdzSf9Iv8w+T65uJP+yK\/ThdZ\/Nwp8sQo8s3S8N8=\"><title id=\"nx-dag-a02-topics-model-and-ai-risk-sr117-t\">Model and AI risk: model risk lifecycle<\/title><desc id=\"nx-dag-a02-topics-model-and-ai-risk-sr117-d\">Every model is inventoried and tiered; development is documented; independent validation tests conceptual soundness, outcomes and benchmarks; approval sets limits of use; monitoring and periodic review keep it current until it is retired. Design of the process, not a record of a run.<\/desc><\/svg><\/div><\/div><p class=\"nx-caption\"><strong>Fig. 02<\/strong><span>Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.<\/span><\/p><\/div><\/div><\/section><section id=\"nx-sec-sources\" class=\"nx-section\" data-hue=\"finance\" aria-labelledby=\"nx-s-8\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Sources<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">Where the evidence comes from.<\/h2><p class=\"nx-lede\">Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.<\/p><\/div><div class=\"nx-section-body\" data-lv=\"register\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Source<\/th><th scope=\"col\">What it gives<\/th><th scope=\"col\">Licence class<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Source\">Federal Reserve and OCC supervisory guidance on model risk 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 credit risk 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><section id=\"nx-sec-decisions\" class=\"nx-section\" data-hue=\"climate\" data-tone=\"alt\" data-variant=\"band\" aria-labelledby=\"nx-s-9\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Decisions<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Who decides, and what the evidence serves.<\/h2><p class=\"nx-lede\">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 model risk 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 systems meet legal duties on transparency, accuracy and human oversight<\/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\" data-hue=\"finance\" data-variant=\"split\" aria-labelledby=\"nx-s-10\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Core questions<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">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\" data-hue=\"climate\" data-tone=\"alt\" aria-labelledby=\"nx-s-11\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">10<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Mechanisms<\/span><\/div><h2 id=\"nx-s-11\" class=\"nx-section-title\">How the risk arises and transmits.<\/h2><\/div><div class=\"nx-section-body\"><p class=\"nx-p\">Model risk arises from errors in design, data or use, and from using models beyond their intended scope. It can cause losses, mis-priced 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\">Data quality 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 human oversight.<\/p><\/div><\/div><\/section><section id=\"nx-sec-methods-and-limits\" class=\"nx-section\" data-hue=\"finance\" data-variant=\"band\" aria-labelledby=\"nx-s-12\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">11<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods and limits<\/span><\/div><h2 id=\"nx-s-12\" 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><section id=\"nx-sec-methods\" class=\"nx-section\" data-hue=\"climate\" data-tone=\"alt\" aria-labelledby=\"nx-s-13\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">12<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods<\/span><\/div><h2 id=\"nx-s-13\" class=\"nx-section-title\">How it is studied, and what the methods cannot say.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-methods\" data-limits=\"true\"><ol class=\"nx-mledger\" aria-label=\"Methods\"><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/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\" 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\" target=\"_blank\" rel=\"noopener\">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\" 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\" target=\"_blank\" rel=\"noopener\">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\" 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\/financial-engineering\/\" aria-label=\"Financial and risk engineering: canonical page on the STEM Commons\" target=\"_blank\" rel=\"noopener\">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\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/science\/financial-economics\/\" aria-label=\"Financial economics and macro-finance: canonical page on the STEM Commons\" target=\"_blank\" rel=\"noopener\">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-14-sec\" class=\"nx-section\" data-hue=\"finance\" aria-labelledby=\"nx-s-14\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">13<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Questions<\/span><\/div><h2 id=\"nx-s-14\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>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><section class=\"nx-section\" data-tone=\"alt\" aria-labelledby=\"nx-rel-15\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Related<\/span><h2 id=\"nx-rel-15\" class=\"nx-h3 nx-mt-2\">Around Banking Nexus.<\/h2><nav class=\"nx-related nx-mt-3\" aria-label=\"Related\"><a href=\"https:\/\/globalriskalliance.com\/banking-nexus\/topics\/credit-and-counterparty-risk\/\">Credit and counterparty risk <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\/banking-nexus\/topics\/capital-and-liquidity\/\">Capital and liquidity <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\/banking-nexus\/topics\/bank-operational-resilience\/\">Bank operational resilience <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\/banking-nexus\/topics\/climate-and-nature-bank-risk\/\">Climate and nature risk in banking <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\/banking-nexus\/topics\/payment-dependencies\/\">Payment dependencies <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\/banking-nexus\/topics\/banking-and-real-economy\/\">Banking and the real economy <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\/banking-nexus\/\">Banking Nexus 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\/banking-nexus\/counterparts\/\">Counterparts across the Consortium <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/\">The Global Risks Alliance home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/trust\/\">GRA governance and trust <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/nav><\/div><\/section><section class=\"nx-closing\" aria-labelledby=\"nx-close-16\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Banking Nexus<\/span><h2 id=\"nx-close-16\" class=\"nx-section-title\">Bring your expertise to this field.<\/h2><p class=\"nx-lede\">The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"mailto:contact@globalriskalliance.com?subject=Banking%20Nexus%3A%20Model%20and%20AI%20risk\">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\/banking-nexus\/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\/banking-nexus\/topics\/model-and-ai-risk\/#faq\",\"isPartOf\":{\"@id\":\"https:\/\/globalriskalliance.com\/banking-nexus\/topics\/model-and-ai-risk\/#webpage\"},\"inLanguage\":\"en\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"What is model risk?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"The potential for adverse consequences from decisions based on incorrect or misused model outputs, whether from errors in design, data, implementation or use.\"}},{\"@type\":\"Question\",\"name\":\"Is machine learning allowed in regulatory capital models?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"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.\"}},{\"@type\":\"Question\",\"name\":\"How is credit scoring treated under the EU AI Act?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"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.\"}},{\"@type\":\"Question\",\"name\":\"Does GRA validate banks' models?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"No. It validates no model and assesses no firm. It researches validation methods and shared risks.\"}},{\"@type\":\"Question\",\"name\":\"Is AI in credit decisions harmful?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"It can widen or narrow access, depending on design, data and governance. 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