The Global Centre for Risk and Innovation (GCRI)
Risk Academy, a Nexortium programmeRisk Science and MethodsDepartment of Risk Management
Models that are wrong or misused, and the controls that manage them
A model is a decision tool with an error term, and model risk is what happens when the error is ignored.
risksacademy.comrisk-sciencediscipline
Twin figures for the central Apennines: L'Aquila, Amatrice and Norcia, counted from its layers at their stated dates.
For Model risk and validation: the faculty's twin of L'Aquila on the planet map, the globe and in 3D. Pick a generator, switch layers, run the instruments; every layer prints its provider and date.
Drag to move, right drag or Shift with a drag to turn and tilt, Ctrl with the wheel to zoom. Keyboard: arrows move, Shift with arrows turn and tilt, + and - zoom, 0 resets, V steps through the views, Escape clears.
Flat plan of the same data: relief, the three reference epicentres with magnitude and depth, and the numbers below; the sampler's figure shows one precomputed field with its parameters. The 3D twin opens on devices with WebGL once its data and library have been checked.
The map loads from this site as it nears the view (MapLibre 6.9.1, checked by hash).
The discipline teaches model risk governance under SR 11-7 (2011) and the PRA's SS1/23, in effect since 17 May 2024, model inventories, independent validation and back-testing, monitoring and drift, explainability and fairness, third-party and generative AI models under ISO/IEC 42001:2023 and the NIST AI Risk Management Framework, and human-in-the-loop controls, with the twin's Gutenberg-Richter fit, its standard error and its sample-size refusal as the first validation exercise. A graduate can inventory a model, validate it against what happened and write the finding that limits its use.
This area covers the risk that decisions rest on models that are wrong or misused, and the controls that manage it: model inventories and governance, validation and back-testing, monitoring and drift, explainability and fairness, third-party and generative AI models, and human-in-the-loop controls. It is taught in the department of Risk Management, Faculty of Risk Science and Methods, through 1 course with it as primary discipline and 2 more that also teach it.
8 subtopics, taught across its courses and labs.
Recent developments in model risk and validation, each with its source; sources checked on 16 October 2026. Summaries are short readings of the source; follow the link for the full account.
News and research as they are published, per discipline, with the faculty's other tools.
The newest research, preprints, news and humanitarian reports for Model risk and validation, each with its source and date, load here. Open the research and news hub
From the Academy's risk taxonomy: the discipline's own entries and those of its primary courses, with how many courses teach each.
No course with this primary discipline is open yet; these are planned, so you can prepare with the courses also taught here.
Courses with this primary discipline0 open, 1 in preparation
These courses count in their own primary discipline and also teach this one; they do not count towards its achievement as primary courses.
Also taught here2 courses that count in another discipline
Cited as places where the subject is practised; the institutions named are sources here, and Risk Academy hosts every course.
Nexus Foundry system pages describe what each system and its rooms are designed to do; they are not a service on offer, and studying here gives no access to them.
Open courses in connected disciplines teach the methods this discipline will build on.