RIA

Governance Cleanup

Data governance and RMA cleanup for an advisory platform

Problem

An RIA platform was experiencing data quality issues and inconsistent governance across multiple systems. Client data, portfolio information, and reporting metrics were scattered across different platforms, making it difficult to maintain accurate client records and generate reliable reports. Key challenges included:

  • Inconsistent data definitions and calculations across systems
  • Duplicate and conflicting client records
  • Limited data lineage and auditability
  • Manual reconciliation processes
  • Difficulty maintaining compliance with changing regulations

Constraints

  • SEC and state regulatory requirements for client data accuracy
  • Client confidentiality and data privacy requirements
  • Integration with existing portfolio management and CRM systems
  • Minimal disruption to ongoing advisory operations

Approach

We implemented a comprehensive data governance framework with the following components:

Data Standardization

Unified data definitions, schemas, and validation rules across all systems.

RMA Cleanup

Systematic cleanup of duplicate and conflicting client records with master data management.

Data Lineage

End-to-end data lineage tracking from source to consumption for compliance and impact analysis.

Quality Monitoring

Automated data quality checks and exception alerts to maintain data integrity.

Outcomes

  • Unified data governance framework across all systems
  • Improved data quality and consistency
  • Enhanced client reporting accuracy and reliability
  • Better compliance monitoring and auditability
  • Reduced manual reconciliation effort

Tech Stack

Microsoft Fabric Purview Power BI Azure Data Factory SQL Server