Large American Financial Holding Company Supports Regulatory Compliance with an Agile, Modern Data Architecture
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Denodo Platform
Tech Stack
- Data Virtualization
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Digital Expertise
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
Use Cases
- Regulatory Compliance Monitoring
Services
- System Integration
- Data Science Services
About The Customer
The customer is a large financial holding company based in the United States. The company crossed the $50 billion threshold in assets with the latest acquisition of a retail bank, making it a systemically important financial institution. This subjected the company to stringent regulatory oversight. The company primarily helps finance capital assets such as photocopiers, railcars, and aircraft. Last year, the company entered the retail banking business with the acquisition of a large regional bank. The acquisition propelled the company to become a Systemically Important Financial Institutions (SIFI) or 'too big to fail' bank. The company must now operate with strict controls around their data to support a whole series of regulatory oversight and controls that they need to be put in place.
The Challenge
The financial services company, after crossing the $50 billion threshold in assets due to the acquisition of a retail bank, became a systemically important financial institution. This subjected them to stringent regulatory oversight. To meet compliance requirements, the company needed a controlled data environment to enable intercompany data transfers with a complete understanding of lineage from source to destination. In the legacy architecture, consumers were pulling data from the upstream systems directly instead of going through the common data access layer. As a result, information that was modified along the way may not tie across to the various silos. The company also needed a smart data governance initiative to avoid the garbage-in-garbage-out problem.
The Solution
The company implemented a Data Services Layer (DSL) with the help of Denodo's data virtualization platform. The DSL integrated the data, metered usage, monitored in-flight data movement, and orchestrated data APIs. It was not a data repository, but a framework to leverage data that was persisted, mastered, and managed elsewhere. Data virtualization, which was core to the DSL, exposed the data in the sources, where it was maintained and mastered, and presented it to downstream consumers through a unified interface. The DSL used data virtualization not just to expose data from its original upstream sources via a common canonical model, but also used it to inject business rules to do data quality monitoring along the way. All downstream consumers accessed data through common definitions and authoritative upstream sources.
Operational Impact
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