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GRAFinancial Crime and Fraud RiskIn development
Readiness checklist

Reader questions and safeguards

The questions a programme in financial Crime and Fraud Risk should be able to answer before a competent institution reviews it.

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Publisher
The Global Risks Alliance
Field
Financial stability, Cyber and digital resilience, Governance and institutions
Status
In development
Service level
R0: information and enquiries

Programme board

Bank B monitoring · Reader questions and… · Cycle 3 of 4

  • Workstreams active
    5Active
  • Milestones due this quarter
    7Watch
  • Decisions pending with owners
    3Watch
  • Open risks
    10
Quarter review dueGRA · Financial Crime and Fraud Risk

Workstreams

by stage

Scoping02
Customer risk model refreshWS-899 · owner: Investigations team
Network analytics pilotWS-040 · owner: MLRO
In delivery02
FIU feedback loopMilestone M5 · slipping
Scenario tuningMilestone M4 · on plan
Review01
Trade-based laundering typologiesIndependent reviewer named
Closed01
Fraud and AML convergenceClosure note on record

Gates

  1. Requestowner named
  2. Scoping noteboundary
  3. Qualifiedinputs
  4. BuildFoundry
  5. Testcontrolled
  6. Publishwith limits
  7. Decisionauthority

Financial Crime and Fraud Risk · Programme boardProgramme board, in outline: domain structure with placeholder names and illustrative values, not a record.

01In brief

The short answer.

The Financial Crime and Fraud Risk readiness checklist is a working aid of seven questions a programme should answer before a competent institution reviews it: purpose, evidence, ownership, governance, data, risks and monitoring. It is not a standard; reviewers apply their own rules, and decision holders such as payment regulators and legislators keep their authority.

02Canvas

Scoping to review.

Canvas · scoping to reviewDesign, not a record
Reader questions and safeguards: the policy cycleA problem reaches the agenda, options are formulated and appraised, consultation tests them, the mandate holder decides, implementation and monitoring follow, and evaluation feeds the next agenda. Design of the process, not a record of a run.

Fig.A programme from scoping to the owner's decision. Design, not a record.

03Geography

Activity and exposure in Mexico.

Night-time lights and population, a proxy for economic activity, with the floods and fires that put assets at risk, framed on Mexico; each layer is a dated NASA product.

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

Layers 2

Activity and exposure

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · 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.

Night-time lights and population, a proxy for economic activity, with the floods and fires that put assets at risk, framed on Mexico.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Natural EarthSources 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). 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). NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.

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, last day: 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

04Checklist

Seven questions.

  1. 01

    Purpose

    What problem does the programme address, and for whom?

  2. 02

    Evidence

    What hazard, exposure and vulnerability evidence supports it, with what uncertainty?

  3. 03

    Ownership

    Who owns the programme and answers for it?

  4. 04

    Governance

    How are decisions taken, recorded and challenged?

  5. 05

    Data

    Which data is used, on what terms, and how is it protected?

  6. 06

    Risks

    What could go wrong, and how is it managed?

  7. 07

    Monitoring

    How will results be measured and reported?

05Checklist

Controls that research can inform.

  • Risk assessment: products, channels, geographies and customer types, updated after major events.
  • Transaction monitoring: scenario coverage, tuning and alert quality.
  • Payment transparency: originator and beneficiary data completeness for the revised Recommendation 16.
  • Sanctions screening: list coverage and name-matching quality across jurisdictions.
  • Scam response: reimbursement and warning processes where rules require them.
06Data rights

Why GRA never handles case data.

Suspicious activity reports and customer data are confidential by law. Sector research uses public typology reports, aggregate statistics and synthetic data only. Topic depth at financial crime data rights.

07Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

TermDefinition
Due diligenceThe independent investigation a lender or investor carries out before committing finance.
Risk ownerThe person or entity with the accountability and authority to manage a risk.
Data lineageA record of where data came from and how it was transformed before use.
Theory of changeA stated chain of causes from a programme's activities to its intended outcomes, used to plan evaluation.
08Sources

Where this page's references lead.

The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.

09Questions

Questions and answers.

Is the checklist a standard?
No. It is a working aid. Institutions apply their own standards and rules.
Related

Around Financial Crime and Fraud Risk.

Financial Crime and Fraud Risk

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