Objective

A UK based bank wanted to embark on an enterprise-wide data strategy and transformation programme, to centralize it's D&A capabilities including master data management, data catalogue, analytical tools and platforms.

Challenges
 

• Siloed approach to data governance and tool usage across the bank
• Data quality maturity inconsistencies
  
  

Approach
 

• Created a centralized repository of high-quality data
  
• Automated an end-to-end solution from data sourcing to visualization
  
• Incorporated ML models to analyze data patterns, report outliers and resolve entities with string matching algorithms
  

Impact
 

• Enabled Program Managers to use trusted data for investment insights with increased frequency of reporting
  
• Reduced processing efforts by 90% from over 15 market data sources
  

Questions

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