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TellParrot for Financial Services

Know your customer once — govern your data and AI everywhere

Core banking, cards, loans, wealth — every product line grows its own customer file. TellParrot resolves them into one governed record and puts your AI models on a register your risk team can defend.

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The problems we solve for financial services teams

KYC done four times for one customer

The problem

The same person is onboarded separately by every product system. Duplicate KYC effort frustrates customers, and fragmented records hide the exposure a risk team actually needs to see.

How TellParrot solves it

Match rules resolve identities across systems using exact identifiers plus fuzzy name and contact matching, with a required-field gate so look-alikes never merge without corroboration. Stewards review borderline clusters with full field-by-field evidence.

→ A single customer view with a governed, human-approved merge trail.

Model risk teams can't see the models

The problem

Credit scoring, fraud detection and marketing models ship from different teams. The inventory lives in slide decks; impact assessments happen after deployment, if at all.

How TellParrot solves it

The AI governance register captures models, their risks, impact assessments, incidents and public disclosures — with contestability workflows and a weighted data-compliance score per model based on the data domains it consumes.

→ A living model inventory that satisfies internal risk and external scrutiny.

Lineage requests take a quarter to answer

The problem

When a regulator or auditor asks how a reported figure was produced, tracing it back through warehouse transformations and manual extracts is a project in itself.

How TellParrot solves it

Column lineage, field-level provenance and a tamper-evident audit chain document how data moved and changed. Every governed export carries a receipt of what left, when, and what the destination acknowledged.

→ Provenance answers in minutes, backed by cryptographic audit evidence.

Privacy obligations outpace manual process

The problem

Access and deletion requests arrive faster than teams can search systems. Retention rules exist on paper but not in the data layer.

How TellParrot solves it

DSAR workflows search governed records across sources; retention policies attach to data domains; deletions and their approvals are recorded on the audit chain.

→ Privacy operations that scale with request volume, with proof of completion.

How TellParrot builds your single customer view

Product systems keep running; TellParrot resolves the customer across all of them and puts your models on a register risk can defend.

Source systems
Core banking
Cards
Lending
Wealth
Marketing CRM
ingest & match
TellParrot
platform
One governed platform
Ingest & map
Match & merge
Govern & catalog
AI governance
governed exports
Consumers
Risk & compliance
Relationship teams
Regulators
Model owners
One customer, resolved with a human-approved merge trail — and every model traceable to the data it runs on.

Capabilities doing the work

Identity resolution with approval workflowAI model register & impact assessmentsTamper-evident audit chainDSAR & retentionColumn lineageData-quality scoring

Every borderline match reviewed, never silently merged

Stewards see per-field evidence and a survivorship preview before approving — the actual matching review screen in TellParrot.

app.tellparrot.com/fs/matching/cluster-2087
Golden Records
Matching
Survivorship
AI Governance
Audit Log

Match review · Cluster 2087

Score 0.94Needs reviewKYC linked

2 candidate records · required-field gate: identifier match ✓

0.94
Match score
2
Records in cluster
4
Fields agree
FieldRecord ARecord BSimilarity
Full nameJonathan P. MercerJon Mercer0.91
Date of birth1984-06-021984-06-021.00
Tax identifier•••••4471•••••44711.00
Emailj.mercer@…jmercer@…0.88
Approve mergeRejectPreview survivorship

Frequently asked questions

How does TellParrot support model risk management?

Every AI model gets a register entry linking its purpose, risks, impact assessments, incidents and disclosures to the data domains it consumes. Assessments follow recognised frameworks, and each model carries a data-compliance score derived from the governance state of its inputs.

Can merges be controlled and reviewed?

Yes. Matching produces clusters, not silent merges. Stewards preview survivorship outcomes and approve or reject each cluster — individually or in bulk — and every decision is audited.

Where does our data live?

TellParrot runs on Azure with region-pinned deployments, including Australian data residency, and offers dedicated database isolation per tenant.

Related industries

InsuranceGovernment & Public SectorSaaS & Software Companies

TellParrot by industry

UtilitiesFinancial ServicesInsurancePublic SectorHealthcareEducationRetailManufacturingMiningLogisticsMembership & NFPDistributionSaaS & ISV