From Data Dependency to Ownership at Enterprise Scale

Client Overview

A leading global financial data provider sought to build and control its own enterprise-grade company database covering 14,100+ North American and UK-listed companies. The objective was to reduce reliance on third-party vendors, improve data accuracy, and create a scalable foundation for long-term growth across global financial markets.

Problem Statement

• Manual extraction from 640K+ regulatory reports, resulting in long turnaround times
• Inconsistent raw file formats across US, UK, and Canadian filings
• Heavy dependency on third-party data providers, limiting flexibility and increasing costs
• Error-prone manual validation processes impacting data quality and comparability

Solution Provided

• Automated PDF downloads and intelligent extraction from regulatory websites across 14,100+ companies
• Standardized and structured 420M+ financial and 46M+ non-financial data points
• Built a robust ETL pipeline with real-time validation to ensure accuracy and faster processing
• Theory of Constraint based project management identifying and resolving constraints in near real time resulting in Industry leading Turnaround time
• Implemented Statistical Quality Control and Statistical process control leading to 99.5% accuracy

Outcome

• Transitioned from data distributor to full data owner
• 3x cost savings achieved through automation and reduced reprocessing
• 99.5% data accuracy delivered through structured validation
• Improved comparability and reliability of insights to support investment strategy decisions
• Flexibility in product/solution design and implementation
• Scalable architecture enabling expansion across global financial markets

Key Takeaway

Data ownership is a strategic advantage. By investing in automation, validation frameworks, and scalable architecture, financial institutions can reduce vendor dependency, protect margins, offer flexibility and unlock long-term competitive control over their data ecosystem.

If your organization is dependent on fragmented data sources and manual workflows, it may be time to rethink your data operating model. Connect with Decimal Point Analytics to build a scalable, automation-led data infrastructure designed for enterprise growth.