The fastest path
to AI outcomes runs
through trusted data
Financial institutions built the data controls regulators demanded. Now the leading data teams are using that foundation to accelerate AI and deliver measurable business outcomes. Ataccama helps you make that shift.
Data expectations in financial services have shifted
The institutions pulling ahead aren't just managing data better.
They're deploying it faster. Here's what's driving the pressure.
Hard-won regulatory progress is at risk
without consistent data foundations
The quality, lineage, and governance controls built to meet regulatory expectations are the same foundations that enable AI. Erosion in one means exposure in both, and starting over isn't a realistic option for either.
AI is running into data problems in real time
AI agents are already accessing source systems directly, bypassing the warehouses where data used to get cleaned. Data quality is no longer a post-activity. It's a real-time requirement at the point of access.
Incumbent
tools are slowing
companies down
If the current platform takes 8–12 months to support the organization’s modernization journey, e.g. toward cloud-native data platforms such as Snowflake or Databricks, every AI initiative waits behind it. The integration burden, testing cycles, and change management overhead are the real adoption barriers.
The business wants results now, not in months
Monthly AI releases, CFO-certified value targets, business teams with their own AI mandates — the pace of expectation has fundamentally changed. Organizations that can move from data investment to measurable outcomes in weeks, not quarters, have a structural advantage. That speed only comes from a foundation that's ready to deploy, not still being assembled.
Growing capability without growing cost
Business expectations keep rising while data budgets compress. The only way to scale AI and analytics output without scaling headcount is a foundation that automates quality, reduces manual stewardship, and frees your team for higher-value work.
Your AI ambitions
are only as strong as
your data trust
AI ambitions consistently outpace data foundations. Models trained on inconsistent data underperform. Agents hitting ungoverned source systems produce unreliable outputs.
Ataccama connects quality, lineage, governance, and observability in a single, agentic data trust platform, natively integrated with Snowflake and Databricks, and built to work across the rest of your estate. Your governance foundation doesn't need to be rebuilt. It needs to be activated.
Stand up trusted data
for AI in weeks, not quarters
Govern data quality
at the source, not after the fact
Scale capability
without growing team size or cost
Unify governance
across cloud, on-prem, and legacy systems
Cut data quality rule
deployment from weeks to days
Built for the realities of financial services
Business benefits & ROI
With Ataccama, financial institutions see measurable gains:
with Customer 360
with Ataccama ONE
of mismanaged data
Results from financial institutions like yours
AI enablement and data trust
A US bank approaching $50B in assets replaced a failed data governance implementation with Ataccama, establishing automated quality checks, a governed catalog, and end-to-end lineage that auditors and business teams can rely on. The foundation now supports live AI initiatives across fraud detection, investor reporting, and their HSA business.
Customer 360
A global insurer unified 120 million records from 200 acquisitions in six months, establishing a single trusted customer view that now powers personalized servicing, AI-driven recommendations, and scalable onboarding across the business.
Operational modernization
Following a major merger, a US bank centralized 11,000 critical data elements across 16 sources, built on consistent definitions and quality controls rather than replicated legacy complexity. Now scaling to 77,000 rule validations to drive accountability across the organization.
Financial crime and AML
Lloyds Banking Group uses Ataccama to verify data for AML, sanctions, and post-trade processes across Retail and Commercial banking, reducing compliance risk, eliminating blind spots, and supporting audit readiness at scale.
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