Success StoryFrom Blind Spots to Full Visibility
Modernizing Data Privacy for a Regulated Enterprise


A leading U.S.-based insurance and financial services company operating in a highly regulated environment managed vast volumes of sensitive and personally identifiable data across policy, claims, underwriting, and customer operations. Facing increasing privacy and compliance requirements, the organization sought to automate the discovery, classification, and governance of sensitive data while establishing greater visibility and control across its enterprise data landscape.


Challenge

1

Limited visibility into sensitive and personally identifiable information (PII) across disparate systems.

2

Manual and time-intensive processes for data discovery and classification.

3

Inefficiencies in responding to Data Subject Requests within mandated timelines.

4

Increasing regulatory pressure to ensure compliance with evolving data privacy requirements.

5

Lack of centralized governance across on-premises and cloud data environments.

The Difference Exavalu Delivered

  • Implemented the OneTrust platform to establish a unified framework for data privacy, AI governance, and automation.
  • Enabled enterprise-wide data discovery and cataloging across applications, databases, data warehouses, data lakes, BI tools, and file systems.
  • Automated identification, classification, and governance of sensitive and personally identifiable information (PII).
  • Established end-to-end data lineage to improve transparency, traceability, and control over enterprise data usage.
  • Reduced manual governance efforts through metadata scanning and automation.
  • Strengthened compliance readiness by improving visibility, governance, and control across the data ecosystem.

Tech Stack


  • OneTrust Data Privacy & Governance Platform


Benefits

1

Enhanced regulatory compliance and alignment with privacy frameworks such as CCPA and NAIC.

2

Improved response speed and fulfillment of Data Subject Requests, meeting mandated timelines.

3

Strengthened data governance, visibility, and control across the enterprise data landscape.

4

Reduced manual effort and operational costs through automation.

5

Increased adoption and utilization of trusted enterprise data.

Key Highlights

1

85+ Applications

scanned across data warehouses, BI platforms, and file systems.

2

15% Reduction

in regulatory compliance-related incidents.

3

30% Improvement

in Data Subject Request response rates.

4

50% Increase

in data stewardship productivity.