Entity

Disaster Recovery Plan

The documented recovery procedures for each critical system — containing recovery time objectives, recovery point objectives, failover procedures, test results, and the dependencies that determine recovery sequence.

Last updated: February 2026Data current as of: February 2026

Why This Object Matters for AI

AI cannot automate DR testing without structured recovery plans; without it, disaster recovery is a manual exercise that reveals gaps only during actual disasters.

Technology & Data Management Capacity Profile

Typical CMC levels for technology & data management in Financial Services organizations.

Formality
L2
Capture
L2
Structure
L2
Accessibility
L2
Maintenance
L2
Integration
L2

CMC Dimension Scenarios

What each CMC level looks like specifically for Disaster Recovery Plan. Baseline level is highlighted.

L0

Database Schema Version F0: Schema changes deployed manually to trading databases; rollback procedures undocumented.

Can do nothing for financial services databases.

Version control schemas for trading and payment databases.

L1

Database Schema Version F1: Schema scripts in shared folder; no version linkage to trading application releases.

Can list schema files for financial services databases.

Link to applications for trading and payment databases.

L2Current Baseline

Database Schema Version F2: Schema versions tracked with basic metadata; payment DB changes require manual approval.

Can track versions for financial services databases.

Add change workflow for trading and payment databases.

L3

Database Schema Version F3: Schema registry with automated validation; BCBS 239 data lineage traced through schema history.

Can validate compliance for financial services databases.

Implement registry for trading and payment databases.

L4

Database Schema Version F4: Validated schema ontology with impact analysis; trading platform changes predict downstream effects.

Can predict impacts for financial services databases.

Deploy ML impact analysis for trading and payment databases.

L5

Database Schema Version F5: AI-optimized schema evolution; performance and compliance automatically balanced.

Can autonomously optimize database schemas.

Ceiling of the CMC framework for this dimension.

Capabilities That Depend on Disaster Recovery Plan

Other Objects in Technology & Data Management

Related business objects in the same function area.

IT Asset Inventory

Entity

The comprehensive registry of all IT assets — servers, workstations, network devices, cloud instances, and software with specifications, patch levels, owners, and the relationships that form the configuration management database.

Security Threat Intelligence

Entity

The curated collection of threat indicators and attack patterns — containing IOCs, CVEs, threat actor profiles, and the risk contextualization that helps security teams prioritize responses.

IT Service Ticket

Entity

The transactional record for each IT incident or service request — containing issue description, affected system, priority, resolution steps, and the time-to-resolution metrics that drive service level performance.

Data Quality Score

Entity

The measured assessment of data quality for critical data domains — containing completeness, accuracy, timeliness, and consistency metrics with thresholds that trigger remediation when quality degrades.

Data Catalog Entry

Entity

The metadata record for each data asset — containing data definitions, lineage, ownership, classification, usage statistics, and the access controls that govern who can see and use each dataset.

Software License Record

Entity

The managed inventory of software entitlements — containing license types, quantities, deployment counts, renewal dates, and the compliance position showing over- or under-deployment.

Code Repository

Entity

The version-controlled collection of source code and configurations — containing code files, commit history, branch structure, pull request reviews, and the quality metrics that track code health.

Privacy Data Inventory

Entity

The catalog of personal and sensitive data across systems — containing data categories, storage locations, retention periods, processing purposes, and the data subject rights fulfillment status.

Patch Deployment Decision

Decision

The recurring judgment point where IT operations evaluates which patches to deploy — weighing vulnerability severity, exploit availability, system criticality, and change window constraints to prioritize patching efforts.

What Can Your Organization Deploy?

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