Platform · Trust Intelligence

Trust Intelligence.scalearrivingTrust Intelligence & Decision Support

Every score on this platform is derived, never set. Trust Intelligence is where that shows: report posture, exam readiness, and a trust score that opens up into the assertions and sealed decisions beneath it. It is arriving, and nothing about it will ever be settable by hand.

The product, at a glance

What Trust Intelligence is made of.

6 capabilities, and the part of the mechanism this product carries. Every box opens right here, with its full story one tap deeper.

tap any box, or any circle in the mechanism, and it answers right hereprove what happened

What changes

What changes when this is running.

This product is arriving, so these read as commitments, stated the way we will be held to them.

The board number will hold under questioning, because the trust score will decompose into the assertions and decisions beneath it.

Nobody will be able to dress up posture, because every score will be derived from evidence, never settable by hand.

The exam file will stand ready year round, because readiness will be computed continuously, not assembled when the letter arrives.

who lives hereExecutivesChief data officeanswers toBCBS 239

The product

Measure trust. Explain trust. Improve trust. Continuously.

Data quality, lineage, governance, controls, privacy and regulatory context, unified into one trust score. So you can prioritise what matters, act with confidence, and prove it to anyone who asks.

Trust and Scale

Business outcomes

Higher data trust

Faster issue resolution

Lower risk of incidents

Regulatory readiness

Better decisions, with confidence

Operational efficiency

Stronger customer and partner trust

At a glance

A real-time data trust score with deep explainability, connecting technical health, governance and regulatory context to business outcomes.

Measure

Continuously assess data trust across assets, domains, pipelines and reports.

Explain

Understand why an asset is trusted or not, with root cause and evidence.

Prioritise

Risk scoring and impact analysis, so effort goes where it matters.

Improve

Recommendations, workflows and guardrails that raise trust over time.

Prove

Immutable evidence, attestations and audit trails for regulators and auditors.

Trigger events

When an institution reaches for this.

A board or audit committee asks for one number, and nobody can produce itTrust is argued from anecdotes because nothing measures itRemediation budget is spent on whatever was loudest that quarterAn examiner asks how you know your controls are effectiveAI adoption stalls because nobody will vouch for the data underneath it

What it does

Seven stages from raw signal to a score somebody will stand behind, and back again.

01 · Collect and observeIngest signals from data, pipelines, systems, rules, controls and usage.

Quality results and rules
Lineage and provenance
Controls and attestations
Usage and adoption

Hover, click or use the arrow keys to walk the lifecycle.

The trust scorecard

One score, with its arithmetic published. Eight dimensions, each weighted, each explainable down to the issue and the root cause behind it. A composite score whose weights are hidden is a score nobody can argue with, and a score nobody can argue with is a score nobody trusts.

of 100 · High trust

Trust by business process

MeaningData qualityLineageGovernanceOverallRetail bankingTreasuryFinanceRiskOperations

Hover a dimension to see what it measures, or a cell to read the process behind it.

Trust over the last 6 periods

Overall trust
Data quality
Governance and control
Operational health

Hover the trend to read all series at one period. A headline score can hold steady while what is under it falls, which is why three lines are drawn and not one.

Lowest trust assets

Customer deposit balanceRetail banking · 48 · Data quality and controls
Intraday liquidity positionTreasury · 52 · Lineage gap and freshness
FX rate used in profit and lossFinance · 55 · Source reliability
Loan exposure at defaultCredit risk · 58 · Completeness

What would move it

01Fix failed rule ACC-01 and reprocess the dataHigh · Medium
02Initiate the control test and document the evidenceHigh · Medium
03Add the missing lineage from source to reportMedium · Medium
04Update the evidence pack for BCBS 239Medium · Low
05Optimise the pipeline to meet its SLALow · Medium

Overall trust by domain

Finance86
Risk86
Retail banking84
Treasury81
Operations79

High trust · 75 to 100Medium trust · 50 to 74Low trust · 0 to 49

How the score is composed

Data quality 22%Lineage and provenance 18%Governance and control 14%Meaning and context 12%Privacy and access 10%Regulatory alignment 10%Operational health 8%Usage and value 6%

An illustrative scorecard for ABC Bank, the site's standing fictional institution. The shape and the weights are real; the values in your estate are your own.

Why the score is what it is

The centre of the product. Every dimension carries its score, its key drivers, the issues dragging it down and the business impact of those issues. A trust score you cannot interrogate is a number somebody has to take on faith.

ExplainabilityScoreKey driversTop issue and root causeImpactStatus

Data qualitywarn

score 72 · key drivers Completeness, accuracy · top issue and root cause Missing values in source feed; rule failure ACC-01 · impact High

Two dimensions are pulling the score down and both are actionable: a failed completeness rule in a source feed, and a control test that has gone overdue. Neither is a mystery, which is the entire point.

What the score means for the business

Trust scored against the things the institution actually does, rather than against tables. This is the cut an executive reads, because it is the one where a falling number has a consequence with a name.

Business impactTrust scoreTrendStatus

Available deposit balancefail

trust score 72 · trend Falling

Available deposit balance is the only one falling, and it is the input to the liquidity work above it. A trust score is worth having precisely when it surfaces that ordering.

Key capabilities

Meaning and context

Business definition and CDE alignment
Semantic consistency
Owner and steward clarity

Data quality

Accuracy
Completeness
Consistency
Timeliness
Validity
Uniqueness

Lineage and provenance

Source reliability
Transformation transparency
End-to-end lineage coverage
Change impact

Governance and control

Policy and standards adherence
Control effectiveness
Issue management
Attestations

Privacy and access

Classification confidence
Access compliance
Data minimisation
Consent and purpose

Regulatory alignment

Obligation mapping
Control coverage
Evidence completeness
Impact of regulatory change

Operational health

Pipeline reliability
Freshness and volume
SLA performance
Incident trends

Usage and value

Adoption and usage
Downstream impact
User feedback
Business value realisation

What the models contribute

AI-powered, and every one of them a recommendation rather than a decision.

Score every dimension from signals the other products already emit

Attribute a fall to its root cause rather than its symptom

Rank issues by business impact, not by severity alone

Recommend the action, with effort and impact estimated

Detect the asset about to drop a band

Assemble the evidence behind every number

Manual and AI-assisted

The same work, split. Everything on the left is something a person does; everything on the right is something the platform proposes, with evidence, for a person to accept. Nothing crosses the line on its own.

Manual

A person does this.

Set the dimensions and their weighting
Set the bands that count as strong, moderate and weak
Decide which recommendations to fund
Own the remediation and close it
Attest to the scorecard a board sees

AI-assisted

The platform proposes. A person accepts.

Normalise and correlate signals into one model
Compute scores across dimensions, assets and domains
Attribute a fall to its root cause
Forecast degradation and rank its drivers
Rank actions by predicted impact and effort
Assemble the evidence behind every number

Top improvement opportunities

Ranked by impact

Improve data quality for customer deposit balance
Complete control testing for critical data rules
Close lineage gaps in regulatory reports
Strengthen evidence for regulatory obligations
Improve pipeline SLA performance

Common use cases

Where institutions start

Executive trust scorecard and reporting
Identifying high-risk data and process areas
Regulatory readiness and control monitoring
Data quality and lineage risk analysis
AI and model data trust assessment
Third-party and vendor data risk oversight
Trust impact of change and new initiatives
Prioritising remediation investment
Board and audit committee dashboards

End-to-end workflow

01Signal ingestion
02Normalisation
03Correlation
04Scoring
05Prediction
06Recommendation
07Remediation
08Re-measurement
09Evidence and attestation

What gets measured

Against your own baseline.

Overall trust scoreTrusted data assetsCritical data assets monitoredSteward attestation completionAverage time to detect an issueAverage time to resolveSteward satisfactionEvidence completeness

Who it is for

Executive leadership: CFO, CRO, CDOData governance councilsData owners and stewardsRisk, compliance and audit teamsData engineers and architectsBusiness analysts and decision makersAI and model owners and developers

Integrations

OntaVera CatalogOntaVera GovernanceOntaVera LineageOntaVera QualityOntaVera PrivacyOntaVera RegulatoryOntaVera Data ProductsOntaVera AI GovernanceOntaVera Reference DataServiceNow, JiraTableau, Power BI, LookerEmail, Teams, Slack

Built on the OntaVera platform

Shared by every product in the suite.

Financial ontology and knowledge graph

Metadata fabric and connectors

AI and semantic engine

Data quality engine

Lineage engine

Policy, rules and approvals

APIs and evidence: REST, GraphQL

Why OntaVera

Unified, context-rich trust scores with full explainability
Real-time signals from quality, controls, lineage, observability and usage
Root cause, recommendations and prioritisation, computed
Embedded governance, attestations and immutable evidence
Out-of-the-box regulatory mappings and evidence packs
Enterprise scale, open, extensible and cloud-ready

Trust is the foundation of every decision.Measurable.Explainable.Actionable.

Try it yourself

What Trust Intelligence will do, shown live.

One number per report or domain, computed from evidence. Knock an input out and the score falls on its own; restore it and it recovers the same way.

setting the stage…

Inside Trust Intelligence6 sub-modules

This capability is arriving. One number per report or domain, computed from coverage, freshness, quality runs, certification, and control conclusions, and the point of it is what happens when you click it: the score opens into every input beneath it.

What you get

A derived trust score with its weights and inputs on display.

No control anywhere to set it by hand, for anyone, at any level.

Every movement explains itself: what changed, when, and on what evidence.

How it works

Derive

The score computes from the record: coverage, freshness, runs, certification, controls.

Decompose

Click any component and you land on the assertions and sealed decisions behind it.

Questions buyers ask

Stronger together

One shared record, so products compound.

Every product you add makes this one smarter, because they read and write the same governed record. Start where it hurts most; nothing you adopt later starts from zero.

Trust Intelligence + Regulatory

Add evidence and the score a board signs will decompose into the same sealed record an examiner reads.

Trust Intelligence + Quality

Add quality and the trust score will move with live check results instead of periodic self-assessment.

Getting started

Start small, and prove it on your own systems.

Most banks start with one priority report and five source systems, live in 90 days, then bring in more of the platform behind exit gates they approve. Trust Intelligence is part of that first conversation.

Keep exploring

← Reference Dataarriving Catalog →available now The engines underneatharchitecture How decisions workframework

The next step

Start with proof, not a promise.

There are three ways in, and each one earns the next. You approve the exit criteria before we spend any more of your time or budget.

A 60-minute working session

Bring one report that is expensive to prove. We walk the mechanism against it. Nothing is required from your side.

A two-week guided sandbox

Your team works hands-on against a synthetic sample bank. It requires zero access to your systems and zero procurement.

A six-week proof on your systems

We use read-only metadata across five systems and one priority report, scored against criteria both sides sign first. The decision it produces is yours.

Book a working session See the adoption path