A-P06 · TOPIC · data-integrity-and-availabilGRA dossier · service level R0
GRAFinancial Cyber and Operational ResilienceIn development
Topic dossier · Financial Cyber and Operational Resilience

Data integrity and availability

Finance runs on records: account balances, positions, policies and transactions. An attack or error that corrupts or destroys them is harder to recover from than an outage, because the firm must restore a correct state. This page sets out how data integrity and availability are threatened and protected, how recovery is measured, and who decides.

01In brief

The short answer.

Data integrity and recovery is the protection of financial records such as balances, positions and transactions against corruption or loss, and their restoration to a correct state. It depends on isolated backups, recovery points and reconciliation. Technology and data leaders, boards, supervisors and industry bodies hold the decisions.

02Spatial finance

Settlement dependencies, and what fails with a node.

How a failure at one financial centre can spread through settlement links. Design links, not real dependencies.

Sixteen financial centres, and how a failure at one spreads through settlement links.Design links, not the real dependencies of any infrastructure.
03Console

Important business services, in outline.

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

Important business services

Data integrity and availability · Bank B services · Self-assessment 3

One service outside toleranceGRA · Financial Cyber and Operational Resilience

Services vs impact tolerance

Make a payment32Cloud region lossWithin
Access cash1318Cyber attackWithin
Mortgage servicing6242Data centre lossWithin
Claims payment2550Third-party failureOutside

Dependency map

people · process · technology · third parties

Remediation

  1. R-1Second claims platform supplierExit plan tested138 d
  2. R-2Immutable backups for paymentsCyber recovery44 d
Important business services: the screen's structure, terms and states for Data integrity and availability.Placeholder names and illustrative values; a design, not a record or a live system.
04The question

Data integrity and availability: how the risk develops.

Confidentiality, integrity and continuity. 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

Corruption spreads to backups

Replication copies corrupted data to secondary sites. Without immutable, isolated backups, there may be no clean copy to restore.

Mechanism

Recovery points decide loss

The time between the last clean copy and the incident sets how much data must be reconstructed from other sources.

Mechanism

Reconciliation proves correctness

After recovery, balances and transactions must be reconciled with counterparties and infrastructures to confirm the restored state.

Mechanism

Errors propagate to others

Incorrect data sent to payment systems, clearing houses or customers spreads the problem beyond the firm.

05Key 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
Recovery point objectiveThe maximum acceptable amount of data loss, measured as time since the last good copy.
Immutable backupA backup that cannot be changed or deleted for a set period.
ReconciliationComparing records with counterparties or other sources to confirm they agree.
06Indicators

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
Critical data with immutable backupsshare of critical datasetsperiodicFirm recordsDECLARED
Recovery point objective for critical dataminutes or hourson reviewFirm standardsDECLARED
Restore tests from isolated backupscount and success rateannualTest recordsDECLARED
Time to reconcile after restorehoursper test or incidentTest recordsOBSERVED
Data corruption incidentscountannualIncident recordsREPORTED
Participation in data vaulting arrangementsyes or noon changeFirm and industry recordsDECLARED
07Canvas

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 · Data integrity and availability as a run graphDesign, not a record
Data integrity and availability: incident response across CSF 2.0 functionsAn adverse event is detected and triaged; response analyses, contains and communicates; recovery restores services from clean backups; improvement and governance close the loop with lessons and reporting. 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.

08Sources

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
Sheltered Harbor standard and participant informationUnited States industry standard for data vaulting and restorationFree to read, terms to check
CPMI-IOSCO cyber guidance on data integrityExpectations for recovering correct dataFree, BIS terms
NIST special publications on data integrityGuidance on detecting and recovering from data corruptionPublic domain
DORA requirements on backup and restorationEU backup and recovery expectationsFree, EU reuse terms
Post-incident reports involving data corruptionLessons from integrity incidentsPublic records, terms per publisher
09Decisions

Who decides, and what the evidence serves.

Financial Cyber and Operational Resilience 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
Chief technology and data officersHow to protect and recover critical dataBackup architecture and test results
BoardsWhat recovery points are acceptable for critical servicesImpact analysis and cost evidence
SupervisorsWhether data recovery capabilities meet expectationsTest evidence and incident reviews
Industry bodiesWhether to establish shared vaulting or restoration arrangementsStandards and participation

Outputs this topic produces

  • Guide to integrity recovery and reconciliation
  • Brief on immutable and isolated backups
  • Method note on recovery point objectives
  • Questions for boards on data recovery assurance
10Core questions

What data resilience asks.

  • If data were corrupted or encrypted, could the firm restore a trusted version, and how far back would it have to go?
  • How would the firm know that data had been subtly altered rather than destroyed?
  • Are backups isolated from the systems an attacker could reach?
  • How would counterparties and the market be assured that balances and positions are correct after an incident?
11Mechanisms

Why integrity and availability matter so much.

Confidentiality breaches dominate headlines, but integrity and availability failures can stop the financial system working. A bank that cannot trust its own ledger cannot safely open for business.

Confidentiality

Data exposure

Breaches harm customers and enable fraud, and carry legal and reputational consequences.

Integrity

Trusted records

If records cannot be trusted, transactions cannot be settled with confidence.

Availability

Access when needed

Encryption by ransomware or outages can make data unavailable just when it is needed.

12Methods and limits

How data resilience is built.

  1. 01

    Isolated and immutable backups

    Backups that attackers cannot alter or delete. Limits: restoring large systems takes time.

  2. 02

    Integrity verification

    Cryptographic checks and reconciliation to detect alteration, grounded in cybersecurity and cryptography. Limits: subtle manipulation can go undetected.

  3. 03

    Data recovery testing

    Testing that restoration works within tolerances. Limits: full-scale tests are disruptive.

  4. 04

    Sector data vaulting arrangements

    Industry initiatives to preserve critical account data for recovery. Limits: coverage and governance vary.

13Methods

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

  1. Software and safety-critical systems engineeringChange control for core systems · Integrity by design · Fault toleranceApplied here
  2. Reliability and resilience engineeringService and dependency mapping · Recovery strategy comparison · Learning reviewsApplied here
  3. Cybersecurity and cryptographyIdentity and privileged access · Detection and response capability · Threat-led testingApplied here
14Questions

Questions and answers.

Why is data corruption harder than an outage?
Because restoring service is not enough; the firm must restore records known to be correct and reconcile them with others, which can take much longer.
What is an immutable backup?
A backup that cannot be altered or deleted for a set period, protecting it from ransomware and malicious changes.
What is data vaulting?
Storing a protected copy of critical account data, separate from the firm's systems, so customer balances can be restored after a severe incident.
Are backups enough?
Only if they are isolated, tested and can be restored within tolerance. Attackers often target backups first.
Why is integrity harder than confidentiality?
Because subtle changes to data may not be noticed, and once trust in records is lost it is hard to restore.
Does the platform handle firms' data?
No. It publishes research using public and aggregated information.
How far back might a firm need to restore?
Far enough to reach a version it can trust. If an intrusion went undetected for some time, that point may be well before the incident was discovered, which is why retention and verification matter.
Financial Cyber and Operational Resilience

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