Insurance Data Platform for Deep Financial Insights on Demand

A grand data mapping & stabilization project to facilitate analytics, financial and performance reporting






Customer location
Project duration:
  • 1.5 years (ongoing)

Insurance giant embarks on a holistic data structuring project

Our client is an award-winning insurance major operating in the US and European markets. The carrier chose Symfa to carry out a series of renovation projects as a part of their digital transformation initiative, to which this project belongs.

In order to facilitate analytics and reporting for their financial and operational lines, the client embarked on a huge data structuring endeavor. The project covers several insurance business lines (warranty servicing, P&C, M&C, ATE insurance, Accident & Health insurance). The vast amount of data used to come each month to the client’s European offices from authorized agents, all in disparate formats. The project goal was to streamline the data flow and provide the client’s talents with clean data for insightful reports.

Quick system overview and the business value it creates

This is a non-GUI system that processes data behind the scenes, invisible to the business users. It inputs data automatically at a fixed interval (currently once every hour). The interval is chosen based on the users' preference and server's capacities.

The solution for this project involves ETL-based files processing that consists of: a) data extraction from various file sources; b) data transformation according to a specific business model; c) data loading into a database and output files with templates.

General View of the Solution (3)

Symfa helps the client move the application to the cloud

After evaluating the benefits that the cloud offered for this project, the customer decided to move it partially to the cloud. To do so, the client hired the third-party vendor whom we assisted with the PoC and the cloud infrastructure setup.

DWHstructured data for further analysis and reporting.
extensive project documentation and data migration scripts with detailed comments.
POCdata mapping, presentations, and demo recordings.
regular syncs with the vendor's team to transfer knowledge and enable a smooth transition to the cloud.
cloudwith Azure ETL applications – Data Factory and Data Lake.
visual data generation logic and data storage, working in sync with Power BI for data visualization in the cloud.
teamdistributed on-prem and cloud talents
continuous work to provide clean and structured data for financial and performance reports.

The Challenges We Faced Along the Project

With terabytes of data in question and 5 business lines depending on the quality work of the solution, we expected a few challenges along the project road. Mainly, those related to the nature of data and the new insights perspectives that the business wanted to get.


Data intake mechanism

The system required a process that would correctly load extra large files (up to several TB) with data contained in various formats. A by-pass script was created for password-protected files.


Data logic discrepancies

Initially, the team planned to reuse the logic patterns adopted in the client's US offices. The proposed pattern didn't work out for the UK office (the end user of the system). After a series of consultations with the business, the Symfa team went with a proprietary solution design.


Data filling rules

Source files could have empty columns, would come in unsupported languages or simply had the wrong title that the system wouldn't recognize. The Symfa team worked closely with the business units on the data filling rules for the best output data quality and provides data filling consultations whenever the operations ask for new data perspectives.


New ETL pipelines

The project started with one ETL process, yet as the client started to see the real value of the solution, it grew massively. Now we process data in 5 environments representing 5 ETL processes: from dev environment to preproduction to cloud. All the data within those environments are properly synchronized.


  • Astera Centerprise
  • .NET
  • MS SQL Server

DevOps effort of the Symfa team

Project growth through motivated synergetic teamwork

During the first year, the team has implemented all the initial scope of work specified by the client. The Symfa team now is working to make the data intake and processing workflow fully autonomous. They have introduced additional data jobs (now totals 5) to enable a more human-independent system operation. More data jobs are underway to automate repetitive and time-consuming data processing jobs.

5 data jobs
2 -> 5business lines
3 -> 23team growth
100%autonomous team
EASYbusiness planning
DATAfor insightful reporting and reconciliation
PROJECTfull documentation package
DOCSinc. SAD, Data Migration Document, Proprietary onboarding framework

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