A04 · TOPIC · open-financeGRA dossier · service level R0
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Topic dossier · Fintech Nexus

Open finance

Open finance lets customers direct their bank, payment, savings, insurance and pension data to other providers through secure interfaces, and in some regimes lets those providers initiate payments. It promises competition and better products. It also creates new dependencies on interfaces, new paths for data misuse and new questions about who is liable when something goes wrong. This page sets out how data sharing changes operational, privacy and conduct risk, how it is measured, and who sets the rules.

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Latest available

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

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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.

For open finance, in GRA's spatial-finance reading, the map opens on night lights and population density with night lights tonight from NASA GIBS, framed on East Africa; every other NASA layer, live feed and forecast waits in the layer list.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 · Blue Marble · © OpenStreetMap contributors · Natural Earth · GDACS · CIESIN/Columbia, NASA SEDAC HBASE · NASA/NOAA VIIRSSources 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
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery 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
  • © 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: GDACS (EC JRC / UN OCHA) Events are indicative, not official warnings.
  • Context: CIESIN/Columbia, NASA SEDAC HBASE. Center for International Earth Science Information Network (CIESIN), Columbia University, and NASA Socioeconomic Data and Applications Center (SEDAC): Global Human Built-up And Settlement Extent (HBASE) 2010; Seto, Guneralp and Hutyra 2012, Global Grid of Probabilities of Urban Expansion to 2030; Global Urban Heat Island (UHI) Data Set, 2013.
  • Observed (EO): NASA/NOAA VIIRS (Suomi NPP). 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 (35 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
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024

01In brief

The short answer.

Open finance is a regime in which customers can direct their bank, payment, savings, insurance and pension data to other providers through secure interfaces, and in some regimes let those providers initiate payments. It promises competition and better products, and it turns interfaces into infrastructure and consent into the control point.

02Console

Fintech risk and operations, in outline.

The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.

Fintech risk and operations

Open finance · Fintech F1 · Week 26

  • Active users
    754,8237Active
  • API uptime, %
    99.91Normal
  • Fraud per 10,000 transactions
    61Alert
  • Complaints open
    272Watch
Fraud spike on one channelGRA · Fintech Nexus

Fraud rate by channel

Credit model fairness

Women656Within
Rural383Review
Under 25418Review
Fintech risk and operations: the screen's structure, terms and states for Open finance.Placeholder names and illustrative values; a design, not a record or a live system.
03The question

Open finance: how the risk develops.

Data portability, privacy and access. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

Interfaces become infrastructure

Once third parties build services on bank interfaces, downtime or slow responses stop those services too. Availability and response-time standards turn an internal system into infrastructure that other firms and their customers rely on.

Mechanism

Consent is the control point

Customers grant access through consent journeys that set scope and duration. Poorly designed journeys produce consent that is broad, forgotten or misunderstood, and data keep flowing after the need has passed.

Mechanism

Credential sharing persists

Where dedicated interfaces are weak or absent, providers fall back on screen scraping with the customer's own login details. Shared credentials widen the attack surface and blur liability when funds or data are lost.

Mechanism

Liability gaps between parties

A failed or fraudulent payment initiated through a third party touches the customer, the account provider and the initiating firm. Where dispute and redress rules are unclear, losses fall on whoever is least able to contest them.

04Key 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
Open bankingOpen data sharing limited to payment accounts, as under the EU PSD2 regime.
Screen scrapingAccessing account data by logging in with a customer's credentials instead of a dedicated interface.
Third-party providerA licensed firm that accesses account data or initiates payments with the customer's consent.
05Indicators

What is measured, and how well.

Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.

IndicatorUnitCadenceSource typeLabel
Dedicated interface availabilitypercent of time availablequarterlyAccount provider performance reportingOFFICIAL
Interface response timemilliseconds at the median and the tailquarterlyAccount provider performance reportingOFFICIAL
Active consentscount by data scopemonthlyImplementation entity statisticsREPORTED
Payments initiated through third partiestransactions per monthmonthlyImplementation entity statisticsOFFICIAL
Authorised third-party providerscount by licence typemonthlyNational and EU registersOFFICIAL
Complaints and disputes on data sharingcases per quarterquarterlyOmbudsman and regulator recordsREPORTED
Personal data breaches involving financial datanotifications per yearannualData protection authority recordsREPORTED
06Canvas

From sources to decisions.

The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.

Pipeline canvas · Open finance as a run graphDesign, not a record
Open finance: from customer due diligence to suspicious activity reportCustomer due diligence sets a risk rating; transaction monitoring scenarios raise alerts; analysts triage and investigate; the MLRO decides whether to report to the financial intelligence unit; feedback tunes the scenarios. Design of the process, not a record of a run.

Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.

07Sources

Where the evidence comes from.

Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.

SourceWhat it givesLicence class
EBA register of payment and electronic money institutionsAuthorised account information and payment initiation providers across the EUPublic register, EBA terms
UK Open Banking performance and usage statisticsInterface availability, response times and call volumes by account providerPublic records, terms per publisher
Banco Central do Brasil Open Finance dataParticipants, consents and interface performance in Brazil's open finance systemPublic records, open data terms
Financial regulator registers (FCA Financial Services Register and peers)Permissions held by each data and payment providerPublic records, terms per regulator
Data protection authority annual reportsBreach notifications and enforcement involving financial dataPublic records, terms per authority
Financial ombudsman decisionsDisputes involving third-party access and payment initiationPublic records, terms per scheme
08Decisions

Who decides, and what the evidence serves.

Fintech Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Who decidesThe questionEvidence this page serves
Financial and competition regulatorsWhich data sets, products and firms an open finance regime covers, and on what timetableComparative regime notes, uptake and performance statistics, complaint trends
Implementation entities and standards bodiesWhat interface, security and consent standards participants must meetAvailability and response-time records, incident histories, consent design evidence
Data protection authoritiesWhether consent, purpose limitation and retention in data sharing meet the lawConsent journey reviews, breach notifications, data-minimisation designs
Boards of account providers and third-party firmsHow much to invest in interface resilience and in due diligence on the firms they connect toInterface performance, dependency maps, liability maps

Outputs this topic produces

  • Comparative notes on open banking and open finance regimes
  • Interface resilience guides for account providers and third parties
  • Consent and data-minimisation design notes
  • Liability maps across the data and payment chain
09Core questions

The questions experts ask.

  • Do customers understand and control what they consent to share?
  • Who is liable when shared data are misused or a breach occurs?
  • Does open finance improve competition and inclusion in practice?
  • How secure are the interfaces and the third parties that connect to them?
  • How do different jurisdictions' approaches compare?
10Mechanisms

Data, consent and interfaces.

Open finance relies on standardized application programming interfaces through which institutions share customer data, with the customer's consent, with authorized third parties. Approaches range from mandated regimes, where regulators require data sharing and set standards, to market-led arrangements. Some regimes extend to payment initiation, letting third parties move money on the customer's instruction.

Consent is the foundation, and its quality is a known weakness: long terms, repeated prompts and complex data flows can make consent a formality. Liability allocation between data holders and recipients is complex, particularly when data pass through several intermediaries. Security depends on the weakest connected party, so the vetting and monitoring of third parties matter.

Benefits depend on whether data sharing produces products that customers value, such as better credit assessment for people with thin credit files, or simply new channels for marketing. Evidence is still accumulating, and outcomes differ across markets.

Interoperability is a practical constraint. Where each institution implements interfaces differently, third parties face high integration costs and uneven reliability, which limits competition; common technical standards, conformance testing and clear dispute arrangements are therefore as important as the legal mandate.

11Methods and data

Methods and their limits.

Comparison

Regime comparison

Comparing legal frameworks, standards and adoption across jurisdictions.

Users

Consumer research

Studying understanding of consent and outcomes for users.

Security

Interface risk analysis

Assessing security models and incident patterns.

Limits: adoption data are often reported by industry bodies with incomplete coverage, and long-term effects on competition are hard to isolate.

12Methods

How it is studied, and what the methods cannot say.

  1. Digital identity and public digital systemsAssurance-level mapping · Remote proofing attack testing · Exclusion analysisApplied here
  2. Cybersecurity and cryptographyThreat-led penetration testing · Supply chain and dependency analysisApplied here
  3. Payment and financial market technologyDependency mapping of a payment chain · Liquidity stress simulationApplied here
  4. Artificial intelligence and machine learningCredit and fraud model evaluation · Drift and challenger monitoringApplied here
13Questions

Questions and answers.

What is the difference between open banking and open finance?
Open banking usually covers payment accounts and payment initiation. Open finance extends data sharing to savings, credit, investments, insurance and pensions, which raises the stakes for consent, security and liability.
Why is screen scraping a risk?
Because the provider holds the customer's login credentials and acts as the customer. A breach exposes full account access, and the account provider cannot tell legitimate access from fraud.
Who is liable when a third-party payment goes wrong?
It depends on the regime. Under PSD2 the account provider usually refunds the customer first and may then seek recovery from the initiating provider. Other regimes allocate liability differently.
Does Fintech Nexus authorise data-sharing providers?
No. Authorisation belongs to financial regulators and, where they exist, implementation entities. Fintech Nexus prepares shared understanding of the risks and design choices involved.
Does open finance mean my data is public?
No. Data are shared only with authorized third parties, with the customer's consent, under the applicable rules.
Does GRA take a position on open finance regimes?
No. It studies their design and effects; policy choices belong to legislators and regulators.
Is open finance the same as open banking?
Open banking usually covers payment accounts; open finance extends the model to other financial products.
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