Building a Global Finance Data Platform for a Multinational Financial Institution

Background

Client
Large International Financial Institution with dozens of Global Affiliates

Engagement Type
Enterprise Finance Data Platform Architecture, Implementation, and Analytics Enablement

Business Need

The client required a centralized finance data platform to support consistent, corporate-level visibility into critical business metrics across dozens of international affiliates. The platform needed to enable reliable collection, validation, consolidation, and analysis of financial and operational data. While also preserving the ability for individual affiliates to independently analyze their own performance.

Key metrics included Assets Under Management (AUM), staffing, and profit and loss (P&L), spanning actuals, budgets, and forecasts. The solution needed to align with the client’s existing cloud strategy while supporting secure, scalable, and auditable financial reporting.

Challenge

The engagement presented several common, but complex, enterprise finance data challenges:

• Consolidating financial data across dozens of international affiliates with varying data maturity
• Ensuring consistent validation and standardization of critical business metrics
• Supporting both corporate-level consolidation and affiliate-level isolation of data
• Integrating multiple cloud platforms while aligning to the client’s preferred technology stack
• Enabling trusted, self-service reporting without compromising data security or governance

Solution

We designed and implemented a centralized finance data warehouse and reporting platform that serves as the authoritative source for corporate financial metrics.

The solution was intentionally architected as a hybrid cloud platform:

• AWS for data ingestion, processing, and warehousing
• Microsoft Fabric and Power BI for enterprise reporting, analytics, and governed self-service

This approach allowed the client to leverage best-fit technologies while maintaining architectural coherence and strong governance.

Technology Architecture

Data Ingestion, Processing, and Warehouse (AWS)
The core finance data platform was implemented on AWS using:

• AWS Transfer Family and S3 for secure data ingestion and storage
• SNS and Lambda for event-driven processing and validation
• Aurora/RDS as the centralized finance data warehouse
• Elastic Beanstalk to support scalable ETL workflows

This architecture enables automated, repeatable collection and consolidation of financial data from all affiliates.

Reporting and Business Intelligence (Microsoft Fabric & Power BI)
Enterprise reporting and analytics were implemented using Microsoft Fabric, including:

• Power BI for interactive reporting and visualization
• Fabric Lakehouse and Data Pipelines for analytics-ready data modeling
• Dataflow Gen2 for transformation and integration
• Semantic Models and Row-Level Security (RLS) to ensure appropriate data access

This design enables consolidated corporate reporting while allowing each affiliate to analyze its own data securely and independently.

Governance and Data Access

The platform was designed with governance and security as foundational principles:

• Standardized metric definitions across all affiliates
• Centralized validation logic to improve data accuracy and consistency
• Role-based access and row-level security to isolate affiliate data
• Clear separation between corporate-level analytics and affiliate-level reporting

This ensured trust in the data while supporting scalable self-service analytics.

Results

• A centralized finance data platform supporting 30+ international affiliates is live and operational
• Corporate leadership has consistent, consolidated visibility into AUM, staffing, and P&L
• Affiliates can independently analyze their own metrics without data leakage or duplication
• Automated ingestion and validation significantly reduced manual reporting effort
• The platform provides a scalable foundation for future financial analytics and forecasting initiatives