GCRI · Digital Public Infrastructure
Digital payments and services
Fast payment systems, mobile money and digital government transfers let people pay, receive wages and benefits, and access services quickly and cheaply. They can widen financial inclusion and speed emergency transfers, and they concentrate operational and fraud risk. This page sets out how digital payment systems and services work, how use and reliability are measured, and what evidence serves the central banks and agencies that run and regulate them.
Digital payments and services on the record.
Digital payments and services: how the risk develops.
Digital service interfaces and dependencies. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Instant payments change behaviour
Fast, low-cost retail payment systems let people and businesses pay instantly at any time, drawing payments away from cash.
Transfers reach people faster
Digital government-to-person payments reach recipients faster and with less leakage than cash, which matters in emergencies.
Fraud moves online
Instant, irrevocable payments attract scams and account takeover, shifting losses to consumers unless safeguards and reimbursement rules exist.
Outages stop commerce
When a central payment system or major provider fails, many transactions stop at once, affecting shops, wages and services.
Contagion on an interbank network.
A loss on external assets distresses banks in proportion to their leverage; DebtRank passes the distress along interbank exposures, round by round, until it settles. Teaching model with stated illustrative values, not a prediction.
Controls
- Fall in external assets
- 2.0%
- Leverage (assets over equity)
- 10 times
- Interbank share of assets
- 10%
- Recovery on interbank claims
- 40%
- Banks in the system
- 20
- Core banks
- 20% of banks
Readouts
- Equity lost to the initial shock
- 18.0%
- Equity lost after contagion
- 45.0%
- Added by contagion (DebtRank)
- 27.0 points
- Banks in default
- 0
Numbers, methods and sources
| Round | System equity lost (%) | Banks in default |
|---|---|---|
| 0 | 18.00 | 0 |
| 1 | 28.80 | 0 |
| 2 | 35.28 | 0 |
| 3 | 39.17 | 0 |
| 4 | 41.50 | 0 |
| 5 | 42.90 | 0 |
| 6 | 43.74 | 0 |
| 7 | 44.24 | 0 |
| 8 | 44.55 | 0 |
| 9 | 44.73 | 0 |
| 10 | 44.84 | 0 |
| 11 | 44.90 | 0 |
| 12 | 44.94 | 0 |
| 13 | 44.96 | 0 |
| 14 | 44.98 | 0 |
| 15 | 44.99 | 0 |
| 16 | 44.99 | 0 |
| 17 | 45.00 | 0 |
| 18 | 45.00 | 0 |
| 19 | 45.00 | 0 |
| 20 | 45.00 | 0 |
| 21 | 45.00 | 0 |
| 22 | 45.00 | 0 |
| 23 | 45.00 | 0 |
| 24 | 45.00 | 0 |
| 25 | 45.00 | 0 |
| 26 | 45.00 | 0 |
| 27 | 45.00 | 0 |
| 28 | 45.00 | 0 |
| 29 | 45.00 | 0 |
| 30 | 45.00 | 0 |
Methods
- DebtRank Battiston and others (2012), Scientific Reports 2:541
- Differential DebtRank Bardoscia and others (2015), PLOS ONE 10
- Contagion in financial networks Gai and Kapadia (2010), Proc. R. Soc. A 466
- Clearing in financial networks Eisenberg and Noe (2001), Management Science 47
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme's own evidence.
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Digital Public Infrastructure in Foundry
- Tested at Digital Public Infrastructure in Universe
- Codified in Open Infrastructure and Developers in Standards
- Published in Digital Public Infrastructure in Reports
- Taught in Faculty of Technology and Digital Systems in Academy
Digital payments move money for every domain's services.
Findings are designed for the Strategic Systems series. Payment infrastructure follows the CPMI-IOSCO Principles (2012) and ISO 20022 messaging; finance questions sit with The Global Risks Alliance (GRA).
- Payment outage records.
- Inclusion studies.
How digital payments and services is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Datasets and provenance
The data classes behind digital payments and services and what is recorded about each before it is used.
| Data class | Provenance recorded | Resolution stated | Licence checked |
|---|---|---|---|
| Satellite imagery, optical and radar | sensor, processing level, acquisition date | pixel size and revisit | per scene |
| Reanalysis and climate model output | model, experiment, member, version | grid and time step | per release |
| In-situ sensors and gauges | station, instrument, calibration record | point and sampling rate | per network |
| Population and asset exposure | method, vintage, input sources | cell size and unit | per release |
| Boundaries and reference geography | producer, edition, date | scale | per edition |
- Lineage
- W3C PROV record from source to figure
- Principles
- FAIR: findable, accessible, interoperable, reusable
- Gaps
- shown as missing, never filled silently
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.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Adults making or receiving digital payments | percent of adults | per survey | Global Findex | REPORTED |
| Fast payment system transactions | count per capita | annual | Central bank statistics | Published statistics |
| Government transfers paid digitally | percent of transfers | annual | Programme records | Published statistics |
| Authorised push payment fraud | value and count | annual | Industry and regulator reports | REPORTED |
| Payment system availability | percent of scheduled time | annual | Operator reports | Published statistics |
| Cost of remittances | percent of amount sent | quarterly | Remittance price data | OBSERVED |
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.
| Source | What it gives | Licence class |
|---|---|---|
| World Bank Global Findex Database | Use of accounts and digital payments | Open, CC BY 4.0 |
| BIS CPMI Red Book statistics and fast payments reports | Payment statistics and fast payment system practice | Public, BIS terms |
| World Bank Remittance Prices Worldwide | Cost of sending remittances | Open, CC BY 4.0 |
| Central bank payment system reports | Volumes, availability and incidents | Public records, terms per central bank |
| Regulator and industry fraud reports, such as UK Finance annual fraud reports | Payment fraud volumes and types | Public, terms per publisher |
Who decides, and what the evidence serves.
Digital Public Infrastructure prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Central banks and payment regulators | How to design and oversee fast payment systems and fraud safeguards | Fraud reviews; resilience assessments |
| Social protection agencies | How to pay benefits digitally without excluding people | Inclusion profiles; transfer evidence |
| Payment service providers | How to reduce fraud and outages | Fraud and availability evidence |
Outputs this topic produces
- Payment inclusion profiles by group
- Fraud and consumer protection reviews
- Payment system resilience assessments
- Evidence notes on digital transfers in emergencies
What experts ask.
Payments are the point at which DPI touches household budgets most directly. Government-to-person transfers, wage payments, merchant payments and remittances increasingly move through digital rails. When they work, they reduce delays, leakage and the cost of handling cash. When they fail, through outages, fraud or exclusion, the people affected may have no buffer.
- How interoperable are payment systems, so that users of different banks and mobile money providers can pay each other?
- How do digital payment services depend on identity, telecommunications, cloud hosting and settlement systems?
- Which users face fees, fraud or failures that discourage use, and what protections exist?
- What fallbacks exist when digital payment channels are unavailable?
Drivers and processes.
Digital payments link front-end services to identity, connectivity and settlement.
Front-end services
Apps, agents, cards and quick-response codes through which people pay. Agent networks matter where connectivity and literacy are limited.
Interoperable systems
Fast payment systems and switches that connect providers. Interoperability lowers costs but creates shared dependencies.
Fraud and consumer safeguards
Social engineering, account takeover and unauthorised transactions harm users, especially those new to digital finance.
Experience with large government transfer programmes has shown that the last mile matters as much as the rails. A transfer that reaches an account is of little use if the recipient cannot withdraw it nearby, does not know it has arrived or loses it to fraud. Studies of DPI payments therefore follow money all the way to its use, not only through the switch.
How the evidence is built, and its limits.
- 01
Transaction data
Aggregate volumes and values show adoption. Individual data are held by providers and require strict safeguards.
- 02
Outage analysis
Incident reports from operators and central banks show failure modes. Public reporting varies widely.
- 03
Household surveys
Show who uses digital payments, for what and what barriers they face.
- 04
Systems analysis
Dependency analysis of payment architecture, applying payment and financial market technology, with limits set by access to operator information.
How it is studied, and what the methods cannot say.
- 01Payment and financial market technologyFast payment system design · Fraud prevention for instant paymentsApplied here
- 02Cybersecurity and cryptographyThreat modelling DPI components · Protecting identity databasesApplied here
- 03Data engineering, interoperability and stewardshipSecure data exchange layers · Common data models · Consent-based sharingApplied here
- 04High-performance, cloud and edge computingCapacity planning for peaks · Multi-site and multi-provider hosting · Portability engineeringApplied here
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.
Questions and answers.
What is a fast payment system?
What is authorised push payment fraud?
Why do digital government payments matter?
Are digital payments always cheaper than cash?
Should cash be kept as a fallback?
Does the platform evaluate payment providers?
How do digital payments relate to identity?
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