Implementation of Data Platform for Advanced Analytics at a Financial Services Company

Implementation of Data Platform for Advanced Analytics at a Financial Services Company


Several financial services companies across the globe have been focusing on leveraging data to power their business, primarily by improving their operational matrices as well by enhancing quality of their customer service. Such financial services companies have an opportunity to leverage intuitive business intelligence, actionable advanced analytics deployed preferably on cloud to achieve these goals.

Customer Background Customer Background

  • Our client is a well-established specialized financial services company in the UK with a focus on contract compliance, account payables and financial risk in health areas.
  • Their reputation as a ‘market leader’ has been established through the quality of service delivery and the organizational strategy to leverage data for improving the service delivery and operational effectiveness.

Requirement Requirement

  • The client was looking for a solution which would help drive down capex costs and improve near real time view of the financial transactions to enable any course correction/s for in-flight financial negotiations.
  • Client data was residing on an on-premise server which was to be migrated to cloud.
  • As daily volume of transactions was high, client wanted to automate the transactional processes and get deeper insights by incorporating intuitive business intelligence and advanced analytics systems in place to enable actionable insights.

Scope Scope

  • The scope of the work included creation of a foundational cloud data service layer for data consumption by internal and external stake holders.
  • It was expected that the vendor should provide consultation and recommendations to the client for the cloud migration platform to be used for migration from the on-premise data.
  • The requirement was also to create a reusable framework to prepare financial data for reporting, dashboarding and analytical purposes.

Solution Solution

  • Aress assigned a team of database specialists and data analysts to work on re-designing the EDW for optimal performance in Azure cloud.
  • All the data received from custom business applications, data in form of media, unstructured files and logs was ingested into Azure Data Factory for processing.
  • Aress created a Data Lake in Azure Cloud to efficiently store the finance related data.
  • The data was migrated from existing data-warehouse to Azure SQL data ware-house.
  • To design the data visualization aspect of the solution, Aress implemented Microsoft Power BI which provided a real-time view of financial transactions.

Business Benefits Business Benefits

  • Post implementation of the solution and within months, the client experienced significant reduction in Capex areas.
  • The solution enabled better analysis of costs across key areas and client was able to design better pricing models for its customers.
  • Due to migration from on-premise to cloud, it helped the client in enhanced collaboration amongst stakeholders, allowed scalability and reduced overall IT and infrastructure costs for the client.