Illustrative: a chamber of seats in blocs with a vote sweeping across, or delegations around a table and the exchanges between them

Risk Academy, led by the Nexus Consortium · Course catalogue · Finance and Economics

Banking and Financial Stability

Financial regulation and supervision

Financial regulation and supervision, taught twice over: as the working methods of the field and as its frontier since 2024, with labs on the Academy's tools, open data and the Nexus Standards.

Core course Frontier course

The discipline

01Core course · L2 Intermediate

Financial regulation and supervision: foundations and practice

This area covers the objectives and instruments of financial regulation: prudential and macroprudential regulation, supervisory approaches and data, conduct and consumer protection, cross-border supervision, fintech regulation, crisis management and disclosure regimes.

Level
L2 Intermediate
Study time
about 24 hours (planning estimate)
Status
In authoring
Prerequisites
An L1 course in the area, or an entry review

Why now

Gives boards and supervisors a shared reference for governing generative and agentic AI in financial institutions. Financial Stability Board, Sound Practices for Responsible Adoption of Artificial Intelligence (AI): Final report, 15 October 2026

Learning outcomes

  1. Define prudential regulation and the other key terms of the discipline and use them correctly in a written case
  2. Explain prudential regulation and macroprudential policy with a worked example and its source
  3. Apply the discipline's method to a documented case and explain each result with its source
  4. Analyse a named case against supervisory approaches and data, stating evidence, date and limits

Modules

  1. Prudential regulation
    • Prudential regulation
    • Macroprudential policy
    • Supervisory approaches and data
  2. Conduct and consumer protection
    • Conduct and consumer protection
    • Cross-border supervision
    • Fintech regulation
  3. Crisis management and resolution
    • Crisis management and resolution
    • Disclosure regimes
  4. Lab: the discipline's method
    • A higher minimum capital ratio lowers the yearly probability of a banking crisis, whose cost is large, and raises the cost of bank credit a little; the regulator sets the minimum where the marginal benefit meets the marginal cost.
    • Work the method through a documented case and explain each result
    • Read the method's sources and stated values

Labs with Academy tools

Nexus Standards

Teaches

  • NRS-F1 Financial stability and systemic financial risk
  • NRS-P9 Legal, compliance and regulatory risk
  • NRS-M8 Method fabric: Financial risk
  • NRS-M12 Method fabric: Policy, regulation and governance

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C5 Scenarios and stress testing
  • NRS-C6 Systemic and cascading risk
  • NRS-C8 Evidence, uncertainty and provenance

Assessment

  • 40%Lab recordWork the discipline's method through a documented case and explain each result with its source and date
  • 40%Case memoApply the discipline's methods to a named place or organisation, stating evidence and limits
  • 20%Key terms checkShort answers on the key terms, marked against the definitions

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Intermediate, 4 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

References

  1. Financial Stability Board, Sound Practices for Responsible Adoption of Artificial Intelligence (AI): Final report, 15 October 2026
  2. Basel Committee on Banking Supervision, An assessment of the long-term economic impact of stronger capital and liquidity requirements, 2010
  3. Laeven and Valencia, Systemic banking crises database II, 2020
  4. Hanson, Kashyap and Stein, A macroprudential approach to financial regulation, 2011
02Live map

People and hazards in Eastern Europe

Where people live, night-time lights and the floods and fires public institutions answer to, over Eastern Europe.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 2

People and hazards

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

People and hazards, framed on Eastern Europe.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONETSources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Live: NASA EONET Events are indicative, not authority warnings.
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • Optional layers (3 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026

03How learning runs

How learning runs, as a process you can run

Select a scenario and press Play: course, pathway, practice, faculty, cells and record.

04What is changing

Frontier course · L3 advanced, programme courses and standards

Financial regulation and supervision: frontier methods

The methods, data, tools and studies that changed financial regulation and supervision between 2024 and 2026, taught by reproducing them on open data.

Level
L3 Advanced
Study time
about 28 hours (planning estimate)
Status
Planned
Prerequisites
Financial regulation and supervision: foundations and practice; Working knowledge of a scripting language (Python or R) for the labs

Why now

Gives boards and supervisors a shared reference for governing generative and agentic AI in financial institutions. Financial Stability Board, Sound Practices for Responsible Adoption of Artificial Intelligence (AI): Final report, 15 October 2026

Learning outcomes

  1. Explain what changed in financial regulation and supervision since 2024 and cite the studies, data or rules behind each change
  2. Reproduce FSB finalises sound practices for AI adoption in finance on open data and state the uncertainty of the result
  3. Evaluate a 2024 to 2026 study: its question, data, method, limits and what it changes for practice
  4. Design an analysis that combines a frontier method with the faculty's instruments, and justify each choice

Modules

  1. FSB finalises sound practices for AI adoption in finance
    • The FSB set out 12 sound practices covering organisation-wide AI governance and lifecycle risk management, including materiality assessment, data quality, explainability, human oversight, cyber risk and third-party AI dependencies.
    • Gives boards and supervisors a shared reference for governing generative and agentic AI in financial institutions.
    • Financial Stability Board, 15 October 2026
  2. FSB consults on principles for regulatory and supervisory modernisation
    • The FSB is consulting on eight high-level principles to keep regulatory and supervisory frameworks effective, efficient and forward-looking while preserving resilience, with comments due 8 January 2027.
    • May influence how jurisdictions recalibrate or simplify rules without weakening agreed international standards.
    • Financial Stability Board, 14 October 2026
  3. Review finds national factors drive uneven reform implementation
    • The FSB's G20 Implementation Monitoring Review finds legal frameworks, market structure and political capacity mainly explain uneven implementation of post-crisis reforms, and recommends targeted changes to how standards are developed.
    • Helps explain cross-border regulatory divergence that complicates compliance and supervisory reliance.
    • Financial Stability Board, 14 October 2026
  4. DORA applies across the EU financial sector
    • The European Supervisory Authorities reminded firms that the Digital Operational Resilience Act applies from 17 January 2025 without a transition period, requiring registers of ICT third-party arrangements and major ICT incident reporting.
    • Makes ICT risk, third-party dependency and incident reporting binding supervisory obligations for EU financial entities.
    • European Supervisory Authorities (EBA, EIOPA, ESMA), 4 December 2024
  5. Reproduction lab
    • Extend the discipline's method with one frontier method and compare its results
    • State the uncertainty and the limits of the result
    • Peer review against a shared checklist
  6. Technology that helps and the risks it carries
    • AI models, tokenisation and regulatory technology.
    • Model risk, cyber accumulation, exposure to quantum attacks on cryptography, and concentration on third-party cloud providers.

Labs with Academy tools

Nexus Standards

Teaches

  • NRS-F1 Financial stability and systemic financial risk
  • NRS-P9 Legal, compliance and regulatory risk
  • NRS-M8 Method fabric: Financial risk
  • NRS-M12 Method fabric: Policy, regulation and governance

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C5 Scenarios and stress testing
  • NRS-C6 Systemic and cascading risk
  • NRS-C8 Evidence, uncertainty and provenance

Assessment

  • 50%Method reproductionReproduce one frontier method on open data and state the uncertainty of the result
  • 30%Study reviewA critical review of a 2024 to 2026 study: question, data, method, limits, what it changes
  • 20%Peer reviewReview two other learners' reproductions against a shared checklist

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Expert, 6 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

References

  1. Financial Stability Board, Sound Practices for Responsible Adoption of Artificial Intelligence (AI): Final report, 15 October 2026
  2. Financial Stability Board, FSB consults on high-level principles for regulatory and supervisory modernisation, 14 October 2026
  3. Financial Stability Board, G20 Implementation Monitoring Review: 2026 report, 14 October 2026
  4. European Supervisory Authorities (EBA, EIOPA, ESMA), DORA application (JC 2024 99), 4 December 2024
  5. Basel Committee on Banking Supervision, An assessment of the long-term economic impact of stronger capital and liquidity requirements, 2010
  6. Laeven and Valencia, Systemic banking crises database II, 2020
  7. Hanson, Kashyap and Stein, A macroprudential approach to financial regulation, 2011
05Take part

Take part in the work

Start from who you are.

06Questions

Questions, answers and key terms

Is the course free?
Yes. Every course and learning material of Risk Academy, led by the Nexus Consortium, is free to study, self-paced or with a cohort. Ordinary participation has no fee; paid work, internships and fellowships are separate arrangements.
What does completing a course give me?
A completion record: the course, its version, the date and what was assessed, private by default and shared by you. It stacks into discipline, department and programme achievements. A record states what was studied and assessed and does not certify competence; it is not a licence, a professional title or an employment status.
Where do the data and the places come from?
Every faculty teaches on a twin of a real place built from open data; each layer carries its provider, licence and date, and every result on the Academy states its source. Maps and figures are indicators for teaching, never an assessment of a place.
How do I take part beyond the course?
Form a competence cell of three to seven people, study a shared pathway, take a supervised assignment in the National Working Groups, or bring a cohort from your institution. For organisations.

Key terms

Term

Prudential regulation

Rules that keep financial institutions safe and sound, such as capital and liquidity requirements.

Term

Supervisory review

A supervisor's assessment of an institution's risks, controls and capital.

Term

Proportionality

Applying rules in proportion to an institution's size, complexity and risk.

Term

Conduct risk

The risk that a firm's behaviour harms customers or market integrity.

ReportsContribute

Contribute evidence from this page.

Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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