nexustandards.com/finance · 1 taught
Finance, Insurance and the Economy
NRS-M8 Financial risk
1standard1discipline
Illustrative: a chain of blocks each linked by hash to the one before, with a Merkle tree under the newest
Risk Academy, led by the Nexus Consortium · Finance and Economics · Department of Banking and Financial Stability
Money laundering, sanctions, fraud, identity crime and risk-based monitoring
Financial crime and fraud
Financial crime and fraud covers money laundering, terrorist financing, sanctions evasion, fraud and scams, identity fraud and cyber-enabled financial crime, and the risk-based controls that detect and prevent them.
- Courses
- In preparation
- Levels
- In development
- Labs
- In development
- Money laundering
- Terrorist financing
- Sanctions compliance
- Fraud and scams
- Identity fraud
- Cyber-enabled financial crime
- Suspicious activity monitoring
- Beneficial ownership
Courses in development extend the scope to one further subject: Anti-money laundering and sanctions controls.
02Maps
Build a twin of any place
Search any place or open the world; the layers and generators follow financial crime and fraud on the planet map, the globe and in 3D.
Finance and EconomicsAny placeTwin builder
- Terrain 0 to 66 m
- 30 power plants, 11,875 MW
- 7 refineries and chemical works
- 2 port land
- 29 named works
- 154 named industrial sites
- Surface water extent, OPERA DSWx (HLS): read live when the 3D twin opens
- Built-up and settlement extent, HBASE 2010: read live when the 3D twin opens
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.
2 live layers, checked 17 Oct 2026Date: newest
Places4
Layers5
iCredits
- Terrain Surface height in whole metres on a grid of about 320 by 370 metres, read from one overview of the 30 m product at build time; the plain lies between sea level and about 66 m. Produced using Copernicus WorldDEM-30 © DLR e.V. 2010–2014 and © Airbus Defence and Space GmbH 2014–2018 provided under COPERNICUS by the European Union and ESA; all rights reserved. read 2026-10-17. Estimate: A digital surface model: trees and roofs are in the heights. Relief exaggeration is printed on the stage.
- Power plants The 30 plants inside the box with nameplate capacity in MW and primary fuel, from the 2021 release, drawn as columns by capacity: the portfolio's assets. Power plants: Global Power Plant Database v1.3.0 (2021), World Resources Institute and partners, CC BY 4.0. release 1.3.0, 2021-06-02. Estimate: A 2021 snapshot, never current operating status; capacity is nameplate.
- Refineries, terminals and industrial sites Named refineries, chemical works, terminals, port land and industrial sites, each as one point with its tags as mapped. © OpenStreetMap contributors, ODbL 1.0. data as of 2026-05-31. Estimate: Points as mapped; no asset value, ownership or operating status is implied.
- Surface water extent, OPERA DSWx (HLS) Open and partial surface water on the date shown, draped on the terrain around the assets. OPERA Dynamic Surface Water Extent from HLS, NASA JPL OPERA (contains modified Copernicus Sentinel data; USGS Landsat), via NASA GIBS, with the product date. Live: this page requests gibs.earthdata.nasa.gov when the layer is opened; the data date is printed with it. 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). Estimate: A classification from optical imagery; clouds leave gaps; never a flood warning, a return-period hazard or a risk rating.
- Built-up and settlement extent, HBASE 2010 Built-up extent in 2010 from Landsat as the exposure footprint around the assets. CIESIN, Columbia University, and NASA SEDAC: Global Human Built-up And Settlement Extent (HBASE) 2010. Live: this page requests gibs.earthdata.nasa.gov when the layer is opened; the data date is printed with it. 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). Estimate: A 2010 classification; the year is printed.
Why this place: One box of about 77 by 66 kilometres holds the petrochemical complex of the Houston Ship Channel, Galveston Bay's refineries and terminals, and a city whose insured losses from Hurricane Harvey (2017) and the February 2021 freeze are the standard cases for catastrophe accumulation, protection gaps and the pricing of flood and power-outage risk. Data quality: the Global Power Plant Database lists the region's 30 plants with capacity and fuel, OpenStreetMap maps 192 refineries, terminals, works and industrial sites, Copernicus DEM GLO-30 covers the low relief, and OPERA surface-water detection and HBASE built-up extent load live from NASA GIBS. It connects to the Insurance, reinsurance and protection gaps, Disaster risk finance, Actuarial science, Climate and nature financial risk, Market, liquidity and treasury risk and Public finance and sovereign debt disciplines of the atlas.
Flat plan of the same data: relief as contours from the inline grid, the plants by capacity, the industrial points by kind and the numbers below. The 3D twin opens on devices that can draw it, once its data and code have been checked.
The boundaries, names and designations shown do not imply any judgement on the legal status of any territory, or any endorsement or acceptance of such boundaries. Countries: Natural Earth (public domain).
03Live map
Activity and exposure in the Gulf of Mexico coast
Night-time lights and population, a proxy for economic activity, with the floods and fires that put assets at risk, over the Gulf of Mexico coast.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 2
Activity and exposure
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
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.
Activity and exposure, framed on the Gulf of Mexico coast.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
- 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
- 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 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.
- 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 (4 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- 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
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
04The subject
The subject, methods and measures and debates and bodies
The field and its scope
For compliance officers, investigators, analysts and policy staff who need to understand how illicit money moves through the financial system and what the controls can and cannot detect.
Quantities and units
Methods and their limits
Each method is listed with what it assumes and where it fails.
What the field debates
Bodies that set practice, and the data they publish
Bodies and standards are named so learners can find and apply their published work; the Academy teaches their use and links to the publisher, and no affiliation is implied.
05The method
From a transaction to a suspicious activity report: base rates and alert precision
Illicit transactions are rare, so even an accurate monitoring rule produces mostly false alerts; the false positive rate, not the detection rate, decides how much analyst time a bank spends and how many reports reach the financial intelligence unit.
Sources: Sharman, Shopping for anonymous shell companies: an audit study of anonymity and crime in the international financial system (2010); Levi and Reuter, Money laundering (2006); Pol, Anti-money laundering: the world's least effective policy experiment? Together, we can fix it (2020).
06At a glance
At a glance, with 5 related topics
Financial crime and fraud at a glance
risksacademy.comfinance-economicsdiscipline
- Open, 0
- In preparation, 1
- Also taught here, 2
- Subtopics, 8
Nexus Standards it teaches and relies on
The Nexus Standards the discipline teaches toward, grouped by master standard, with the disciplines that teach each.
nexustandards.com/society · 1 taught
Governance, Security and Society
NRS-H118 Organised crime and illicit economies
1standard1disciplinenexustandards.com/systemic-risk · 1 taught
Systemic Risks
NRS-P9 Legal, compliance and regulatory risk
1standard1discipline
Nexus Standards at the AcademyThe Academy proposes how each discipline teaches toward the Nexus Standards; the mapping is open for public review.
Research and tools
Research and preprints as they are published, by discipline, with the faculty's other tools.
The hub lists the newest research and preprints for Financial crime and fraud, each with its source and date. Open the research hub
Hazard families it covers
From the Academy's risk taxonomy: the discipline's own entries and those of its primary courses, with how many courses teach each.
Hazard families
- Fraud and misconductscope
What is changing now
Recent developments in financial crime and fraud, each with its source; sources checked on 16 October 2026.
Courses in this discipline
Courses for this discipline are in development; until they open, study it through the connected courses and open lessons below.
The courses from connected disciplines below also teach this field.
Courses from connected disciplines that also teach this field
Each course has its primary discipline elsewhere and teaches this field as part of its scope.
07Console
How Financial crime and fraud is taught, as a process you can run
Press Play to run this process from this page's own data.
08Practice
Practice, learning and connections
How technology helps and what risk it brings
Achievements in this discipline
Pathways that teach it
Where the subject is practised
- The Global Risks Alliance (GRA)Financial Crime and Fraud RiskConsumer scams, Cyber enabled financial crime, Financial crime data rights, Financial sanctions risk, Identity fraud, Money laundering risk, Payments fraud, Suspicious activity controls
Field platforms of the ecosystem where the subject is studied and applied.
The two Foundry systems where it is practised
- FoundryNXS-GRX systemEntity resolution across recordsFusion room
- NXS-NSF systemAuthorisation and purpose limits on sensitive dataAuthority room
Foundry system pages describe what each system and its rooms are designed to do; the courses teach the methods these systems apply.
Across the ecosystem
09Take part
Take part in Finance and Economics
Start from who you are.
10References
Core references and where to begin
Start with Levi, then Financial Action Task Force, then Pol.
11Questions
Questions, answers and key terms
Is study here 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 courses in financial crime and fraud?
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
Money laundering
Disguising the criminal origin of funds so they appear legitimate.
Term
Know your customer
Verifying customers' identities and understanding their activities.
Term
Beneficial owner
The natural person who ultimately owns or controls a legal entity.
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.
Risk Academy
Related
Around Financial crime and fraud
Financial crime and fraud
Prepare with a related course
Open courses in connected disciplines teach the methods this discipline will build on.