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GRA · Financial Crime and Fraud Risk

Spatial financeWhere capital meets hazard, exposure and transition

Published scenarios

Financial crime scenarios test how fraud and laundering exploit change: a disaster relief payment programme, an outage that pushes customers to new channels, a wave of impersonation scams. This page sets out scenario designs and the assumptions that matter. Values are design values.

01Workspace

The workspace for published scenarios.

Pipeline

Published scenarios · Workspace WS-17 · Example interface, not a record

One stage waitingGRA · Financial Crime and Fraud Risk

Stages

  1. Ingest4 sources
  2. Validateschema · licence
  3. Transformversioned
  4. ModelArtificial
  5. Testheld-out
  6. Releasewith limits

Artefacts

Transaction monitoring alertsv6.1OpenOBSERVED
KYC recordsv2.3To checkPublished statistics
Case managementv2.6OpenPublished statistics
Screening logsv2.6OpenOBSERVED

Compute quota

share used vs alert level

CPU hours71 used of 80 used limitStorage34 used of 90 used limitGPU hours22 used of 70 used limit
Pipeline.Illustrative interface; not live data.

Financial Crime and Fraud Risk · Pipeline. Pipeline: example names and illustrative values, not a record.

02Status

Releases appear as they are reviewed.

Analysis runs in Foundry; reviewed releases are listed here.

03Scenario set

Financial crime scenarios for planning.

ScenarioWhat it tests
Authorised push payment scam wave using synthetic voiceDetection of social engineering and customer warnings
Mule network after a disaster cash transfer programmeOnboarding controls under emergency relaxation
Sanctions evasion through trade documentsTrade finance document checks
Account takeover through compromised identity dataAuthentication and identity verification
04Process

How the process runs.

Process explorer · Process

Published scenarios: Layers to published map

7 steps4 stages1 gate

Process

Published scenarios: Layers to published map

Layers enter with their rights, are aligned, analysed and checked for uncertainty, then released after public-safe review; a map is a governed spatial claim.

  1. 01 Data

    1. 01Source layers with their rightsDataset · NXS-GRX (canonical data, provenance and risk)Spatial views of The Global Risks Index (NXS-GRX) products sit under the boundary licence gate. Rights classification sets how a layer may be used.
  2. 02 Harmonise

    1. 02Coordinate reference and boundary versionRecord · NXS-EOP (earth observation and digital twins)The area of interest preserves its coordinate reference system, polygon validity and observation support. Boundary versions are kept.
    2. 03Harmonise units, variables and timeStepUnit metadata, conversion records and transformation logs are required. Alignment is an evidence event, not hidden preprocessing.
  3. 03 Analyse and check

    1. 04Analyse with a recorded processing recipeModel · GIS teamA processing recipe records parameters, calibration, inputs and output lineage. The analysis methods are named in each product's own record.
    2. 05Spatial uncertainty checkGateSpatial uncertainty is recorded and affects downstream use. A high-uncertainty polygon may suit internal review, not public-safe release.
  4. 04 Publish

    1. 06Spatial metadata bundleRecordThe bundle records boundary type, jurisdiction, geometry version, projection, resolution, source, time window, uncertainty and access class.
    2. 07Public-safe release of the mapDecisionThe output record names the redactions, uncertainty and public-safe reviewer. A map is a governed spatial claim, never merely a picture.

Spatio-temporal intelligence · Data protocols: semantic, jurisdictional and temporal intelligence · NXS-EOPDesigned programme process, not a record of operation. No cycle has run and every programme is at service level R0. A gate is a programme decision, never a public-authority approval, certification or deployment authorisation. The pages cited are design doctrine.

05Network method

Fraud as a network.

Fraud and laundering are network problems: accounts, devices and counterparties linked by flows. Graph methods find communities and unusual paths. Methods at GCRI network science; identity evidence at the Global Centre for Risk and Innovation (GCRI) identity and authentication.

06Sources

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.

07Questions

Questions and answers.

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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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