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AI‑Ready Data Infrastructure for Financial Services

Data observability that meets the demands of banking, capital markets, and wealth management. Aligned with DORA and SOX. Zero data extraction required.

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The Financial Services Data Challenge

Banks, capital markets firms, and wealth managers face tough data challenges today. AI needs clean, accurate data. Regulators are pushing harder on three fronts:

  • DORA

    Calls for full ICT risk management

  • SOX

    Requires auditable controls over financial data

  • Model risk guidance

    Demands validation, documentation, and explainability

Yet many data observability tools skip compliance duties or pull sensitive financial data outside the security perimeter.

Most enterprise financial services organizations run two observability tools and still have gaps. Chris Alfaras, CIO, on the architecture shift Snowflake customers can’t ignore.

Read Chris’s Take

Regulatory and Compliance Pressures
Facing FSI Data Teams

  • DORA Is Here. Are You Ready?

    DORA is in force across the EU and reaching every firm that touches European financial data. It demands ICT risk management, incident reporting, and third-party oversight. Strong data observability supports each pillar. ¹

    DORA enforcement is live, and the pressure is mounting. See where your firm stands.

    Get Your Enterprise Playbook

  • SOX Auditors Want Proof, Not Promises.

    SOX Section 404 puts internal controls over financial reporting on the CFO’s desk and the auditor’s checklist. Clear data lineage helps firms show those controls hold up under scrutiny. ²

  • Your Models Are Only as Good as Your Data

    SR 26-2 calls for model validation and ongoing monitoring across the model lifecycle. AI, credit, and pricing models all need reliable, well-documented inputs. Bad data in means regulator scrutiny out. ³

    88% of AI projects fail. The data inputs are usually why.

    What’s Stalling AI Projects?

  • Where Your Data Lives Is a Board‑Level Question

    GDPR, US state privacy laws, and cross-border rules shape where data can go. Native architecture keeps data inside the Snowflake account, where governance and residency stay in your control. ⁴

Where Risk Intelligence Meets Data Quality

Compliance That Doesn’t Slow You Down

DataRadar™ gives financial services teams the visibility regulators look for, all inside your Snowflake account. No data extraction. No third-party risk. ⁴

  • Audit trails mapped to SOX Section 404

  • End‑to‑end data lineage from source to financial report

  • Anomaly detection that catches problems before the CFO does

  • ICT risk monitoring and incident logging built for DORA

  • Model input quality scoring aligned to SR 26‑2

  • Your data never leaves your Snowflake account. Period.

The compliance story starts with architecture. Most observability tools force your data outside your perimeter to do their job.

See the Architecture

Finally, Risk Teams Get Their Data

Stop treating data quality and risk as separate conversations. ³

  • Real‑time data quality dashboards your risk committee will open

  • Threshold alerts routed to risk workflows, not inboxes

  • Historical trend analysis examiners can follow

  • Model performance tied to the data feeding it

  • Audit‑ready reports without the fire drill

Where Financial Institutions Face the Greatest Risk

  1. REGULATORY COMPLIANCE

    The Compliance Cliff Is Closer Than You Think

    DORA is live. The EU AI Act high-risk provisions hit in August. SR 26-2 just superseded SR 11-7. FSI data leaders are running out of runway.

    Read the Breakdown

  2. DATA QUALITY

    The $12.9M Problem Hiding in Your Data

    Poor data quality costs the average enterprise $12.9M a year. In Financial Services, that number lands on the CFO’s desk.

    See the Numbers

  3. FRAUD AND OPERATIONS

    When Your Data Stops Talking, Fraudsters Listen

    Silent feed failures are the blind spot real-time fraud detection can’t survive. Here’s how to catch them before the criminals do.

    Close the Blind Spots

  4. MODEL RISK

    Why 88% of AI Projects Never Reach Production

    The data inputs are usually the reason. For FSI firms running credit, pricing, and trading models, that’s a regulator-scrutiny problem.

    See Why AI Stalls

  5. ARCHITECTURE AND COST

    Why Your Data Should Never Leave Home

    Every observability tool that extracts your data adds cost, security risk, and a third-party breach surface. The architecture matters more than the features.

    See the Architecture

  6. AI GOVERNANCE

    When AI Takes Action, Bad Data Becomes a Crisis

    Agentic AI in FSI means autonomous trades, autonomous approvals, and autonomous customer decisions. Bad data inputs are no longer an inconvenience.

    Read the Imperative

Frequently Asked Questions

Does DataRadar™ require my data to leave Snowflake?

No. DataRadar™ is a Native App, which means it runs inside your Snowflake account. Your data never moves, never gets copied to a vendor cloud, and never crosses your security perimeter.

How does DataRadar™ support DORA readiness?

DataRadar™ gives you ICT risk monitoring, anomaly detection, and full audit logging that align with DORA. The native architecture cuts third‑party risk because your data never leaves Snowflake.

How does native architecture help with data residency?

DataRadar™ runs inside Snowflake as a native app. Your data stays put, which makes life easier under GDPR, US state privacy laws, and cross‑border rules.

Does DataRadar™ integrate with our GRC platform?

DataRadar offers APIs and webhook integrations that connect to common Government, Risk, and Compliance (GRC) platforms. Quality issues can trigger risk events, and quality scores can feed your enterprise risk dashboards.

How does DataRadar™ support model risk management?

DataRadar tracks the quality of data feeding your AI, credit, and pricing models, including accuracy, completeness, consistency, and distribution stability. Quality scores plug into model validation workflows, which supports SR 26‑2 readiness.

Trust Your Data. Power Your AI.

While competitors scramble for DORA compliance, Trust Your Data. Power Your AI. offers you the best practices across The DataRadar Observability Framework™. These insights are utilized by market leaders before regulatory scrutiny.

  • $12.9M

    avg. annual cost of poor data¹

  • 70%

    will adopt by 2027²

  • Only 40%

    of AI prototypes succeed¹

Get Your data AI‑ready Book your demo Download your 30‑day trial

References

¹ DORA European Union. (2022). Regulation (EU) 2022/2554 of the European Parliament and of the Council of 14 December 2022 on digital operational resilience for the financial sector (Digital Operational Resilience Act). Official Journal of the European Union, L 333, 1-79. https://eur-lex.europa.eu/eli/reg/2022/2554/oj/eng

² SOX Section 404 United States Congress. (2002). Sarbanes-Oxley Act of 2002, Pub. L. No. 107-204, § 404, 116 Stat. 745. https://www.govinfo.gov/content/pkg/COMPS-1883/pdf/COMPS-1883.pdf

³ Model Risk Management Board of Governors of the Federal Reserve System. (2026). SR 26-2: Revised guidance on model risk management. https://www.federalreserve.gov/supervisionreg/srletters/SR2602.htm

⁴ DataRadar, Inc. (2026). DataRadar: Trust your data. Control your costs. Power your AI. https://www.dataradar.io