Denodo Technologies > Case Studies > Large American Financial Holding Company Supports Regulatory Compliance with an Agile, Modern Data Architecture

Large American Financial Holding Company Supports Regulatory Compliance with an Agile, Modern Data Architecture

Company Size

1,000+

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

Data Science Services
System Integration

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

The Data Services Layer supported by data virtualization helped inject pragmatism to the company’s data integration strategy—it enabled faster time-to-market and incremental information delivery.
DSL helped the company realize value from its data—it successfully enabled access of all data through a common provisioning point instead of through the legacy point-to-point integration.
Data virtualization was able to minimize data replication and proliferation by eliminating data redundancy and unnecessary copies of data.
Data virtualization enabled effective data governance. It enforced policies, standards and procedures, defined and published authoritative sources of data, efficient data lineage and metadata management, and monitoring of data quality before consumption.