Case study

Data Management Solution for a European Loan Management Business

An end-to-end analytical platform provides BI reporting and advanced analytics to improve business efficiency of a financial services company

Cloud & DevOpsData & AnalyticsFinancial Services & InsurancePlatform Development

Project snapshot

Recognizing the importance of efficient data management in today’s financial sector, our client was focused on using relevant digital technologies while expanding their market presence and enhancing the customer experience across multiple countries. With a steadfast commitment to improving their core business operations within loan management, the company aimed to redesign its data analytics processes to drive more streamlined decision-making and reduce operating costs.

Business challenge

Our client provides a complete range of debt management services, accompanying customers at each stage of their journey, from invoice administration to debt collection and purchasing. Streamlining data analytics processes had the potential of bringing added value to the client’s services, allowing the company to make data-driven decisions and reduce financial risks.

A transnational business with a strong presence in several European economies, our client felt the need to standardize their approach to managing large volumes of information received from different sources.

At the same time, the company had no unified data warehouse capable of processing incoming data and simplifying business processes. They needed a complete review of their data management strategy, allowing them to establish a presence in new markets while maintaining the same high quality of loan counseling services.

Data Management Solution for a European Loan Management Business

Solution delivered

Intellias delivered an end-to-end analytical platform that includes the required infrastructure, data warehouse, business intelligence, reporting (including self-service options), and advanced analytics capabilities.

The team helped the client develop a new data management architecture capable of consuming, processing, and analyzing large volumes of data. This complex solution included deep analysis of the client’s requirements and the design and implementation of new data warehousing infrastructure.

We chose Microsoft Azure SQL Database for an enterprise data warehouse and Microsoft Azure Data Factory as the platform for data processing.

For analyzing data and generating actionable insights, the Intellias team designed and implemented a business intelligence framework with Microsoft Power BI under the hood. The use of Microsoft tools ensured seamless integration of components and allowed for building a coherent BI/DWH framework.

The implemented business intelligence process involves advanced data analytics and visualization via interactive dashboards and operational reporting. The framework provides a 360-degree view of customer information, analyzing both historical and operational data collected from the call center and the CRM system. Machine learning technologies add predictive capabilities by enabling automated customer segmentation.

Tap into your data potential to gain a competitive edge

Business outcomes

Intellias fully redesigned the client’s approach to data management, building a new infrastructure that takes data processing efficiency to a new level. Leveraging the power of data warehousing and business intelligence technologies, we created advanced data analytics experiences giving our client full control over their entire information base:

  • Streamlined business processes by implementing a unified data management strategy
  • Facilitated business expansion into new regional markets by applying a standardized approach to data management in all company branches
  • Supported data-driven decision-making with advanced analytics
  • Significantly reduced manual labor and operating costs due to automated BI reporting
  • More accurately targeted customers based on automated segmentation and predictive analytics


decrease in average manual actions per case due to an automated data collection process via refined customer segmentation


cost efficiency through custom data infrastructure for the BI platform

1 TB

data warehouse capacity

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