Banking Regulatory Reporting Agent

AI Agent for Regulatory Reporting

Prepare regulatory reporting packs from primary data, policy references, prior submissions, owner inputs, reviewer comments, and sign-off history while keeping provenance visible.

Explore VDF AI Agents
SourcePrimary data provenance attached
ReviewOwner and approver workflow coordinated
DraftNarratives and tables prepared
AuditSubmission trail preserved
Assembles
Reg reportsData lineageReviewer packsNarrativesEvidence mapsSign-off trails
The Reporting Problem

Regulatory reports are assembled by hand from systems nobody fully owns

Bank reporting teams reconcile numbers, narratives, source systems, commentary, and reviewer changes under time pressure. The hardest part is proving where each statement came from.

01

Primary data is fragmented

Risk, finance, treasury, operations, compliance, and business systems each own part of the report.

02

Narratives need evidence

Commentary and variance explanations must connect to real data, assumptions, and owner inputs.

03

Reviewer cycles are messy

Comments, changes, approvals, and late adjustments can scatter across emails and spreadsheets.

04

Audit wants lineage

A report is only defensible if the bank can show source, transformation, reviewer, and sign-off history.

The VDF AI Opportunity

Regulatory reporting with provenance built into the workflow

Gather

Source-Linked Report Assembly

Numbers and narratives point back to origin.

The agent gathers relevant tables, source extracts, prior filings, policy references, owner commentary, and supporting evidence into a report workspace.

  • Primary data references
  • Prior submission comparison
  • Owner input collection
  • Supporting evidence map
Source
Report Provenance

Lineage attached

DataOwnerPriorEvidence

Draft

Narrative and Variance Preparation

First drafts with assumptions visible.

It drafts report commentary, variance explanations, open questions, and reviewer prompts with each claim linked to source context.

  • Variance narratives
  • Open question list
  • Source-backed commentary
  • Reviewer prompts
Draft
Reporting Pack

Reviewer ready

NarrativeVarianceQuestionReview

Approve

Reviewer and Sign-Off Trail

The approval path stays intact.

The agent tracks owners, review status, requested changes, approvals, evidence gaps, and final sign-off for audit and supervisory review.

Sign
Approval Trail

Submission controlled

OwnerChangeApproveAudit
Where it pays back

Where the Regulatory Reporting Agent pays back

Periodic Regulatory Packs

Assemble repeat reports with prior-period comparisons and evidence maps.

DORA Evidence Packs

Collect resilience evidence, owners, incidents, controls, and review status.

Risk and Capital Reporting

Prepare source-linked commentary and variance explanations for risk teams.

Regulatory Change Impact

Map new requirements to report templates, owners, data sources, and controls.

Reviewer Coordination

Track comments, open questions, approvals, and sign-off readiness.

Audit Preparation

Produce lineage records that show how the report was assembled and approved.

ROI Snapshot

What changes after rollout

Less
Manual source chasing
Clear
Provenance for each section
Faster
Reviewer cycles
Complete
Sign-off and submission trail
FAQ

Questions about the Banking Regulatory Reporting Agent

What is a banking regulatory reporting agent?

A banking regulatory reporting agent assembles report packs from primary data, prior filings, policy references, owner inputs, reviewer comments, and sign-off records with provenance attached.

How is a banking regulatory reporting agent different from a generic chatbot?

A generic chatbot can draft a paragraph. The Regulatory Reporting Agent coordinates source-linked data, owner review, evidence maps, changes, approvals, and audit-ready sign-off trails.

Can it run on-premise with private company data?

Yes. It can run on-premise or in a sovereign cloud so regulatory data, risk information, management commentary, and submission evidence remain inside the bank.

What does it produce?

It produces report drafts, evidence maps, variance narratives, data lineage notes, owner request lists, reviewer packs, sign-off logs, and audit preparation files.

Where does it fit in a governed AI program?

It fits across finance, risk, compliance, treasury, operations, and regulatory affairs, often working with Compliance Monitoring, Treasury & Risk, and Reconciliation agents.

Assemble regulatory reports with evidence instead of last-minute archaeology

See the Regulatory Reporting Agent connect data, owners, reviewers, and sign-off in one governed workflow.