Client Overview
A leading financier and investment manager faced significant operational challenges as their business grew facing several operational bottlenecks. The company relied on a small data team tasked with overseeing a loan management system migration, supporting a multitude of financial models, and generating accurate, timely reports for stakeholders.
Business Challenges
The firm encountered several critical challenges that were impacting their operational efficiency:
- Limited Data Resources: A small, overwhelmed data team struggling to manage increasing data demands
- System Migration: Transitioning to a new loan management system added complexity to data integration and reporting processes
- Complex Financial Models: Managing and maintaining numerous financial models led to inconsistencies and inefficiencies in reporting
- Time-Consuming Reporting: Time-intensive manual processes for monthly reporting and forecasting
- Lack of standardisation in metric calculations and KPI tracking
Our Solution
To address these challenges, we delivered an end-to-end data transformation that streamlined their entire data infrastructure:
Enterprise Data Model
We designed and implemented a robust enterprise data model that unified their financial data structure, creating a single source of truth for all operations. This model accommodated various financial products while maintaining flexibility for future growth.
Automated Data Operations
Our solution introduced multiple automation layers:
- Automated data ingestion processes from the loan management system, streamlining the integration of financial data
- Streamlined data extraction mechanisms to efficiently pull required information from Microsoft Fabric to Microsoft Excel
- Implementation of a modern data warehouse architecture using Microsoft Fabric
BI Dashboards
We designed and deployed interactive dashboards using Power BI to provide near real-time insights and improve decision-making capabilities.
Technical Implementation
We leveraged Microsoft's latest technology stack to deliver:
- Custom data engineering solutions for complex financial calculations
- Advanced data modeling to support various analytical requirements
- Interactive Power BI dashboards for near real-time insights
- Excel automation for traditional reporting needs
- Power Automate workflows for process automation
Business Impact
The transformation delivered significant measurable improvements:
Operational Efficiency
- Reduced end-of-month reporting preparation time from 3 days to 1 day
- Significantly accelerated loan pipeline forecasting processes
- Eliminated manual data entry and reconciliation tasks
Data Quality and Consistency
- Established standardised metrics and KPIs across the organisation
- Created a single source of truth for all financial reporting
- Improved data accuracy through automated validation checks
Strategic Benefits
- Enhanced decision-making capabilities through near real-time data access
- Improved risk assessment through comprehensive data analysis
- Scalable infrastructure ready for future growth
Technology Stack
- Microsoft Fabric
- Power BI
- Power Automate
- Azure Data Services
- Synapse notebook / PySpark
- Custom Python/SQL solutions
Conclusion
Through our targeted data transformation initiative, we helped the client achieve a modern, efficient, and scalable data infrastructure. The solution not only addressed their immediate operational challenges but also positioned them for future growth with a robust data foundation.
The success of this project demonstrates the power of combining technical expertise with domain knowledge to deliver practical, high-impact solutions in the financial services sector. The automated workflows and standardised processes now serve as the backbone of their data operations, enabling faster, more accurate decision-making across the organisation.