Digitizing benefits administration process

Case study

Digitizing benefits administration process

Setting up employee benefits administration for customers is often a daunting effort across organizations. Due to its complex processes, benefits administrators have to face a number of challenges, which include:

  • Collecting a multitude of employee data along with the details of their dependants
  • Managing the relevant benefit plans entitled for each employee, where the benefit plans are location-dependant and vary for every level of employees in a diverse workforce
  • Documenting and uploading the list of employee data files prepared for every client organizations to a Benefit Administration System (Ben Admin Systems)

Manually processing these tasks might lead to data errors, mismatch in policies, lack of insights and, ultimately, a delayed turnaround. This can hit the operational efficacy of an organization.

What if benefit administrators have an online tool to sort the maze of complex steps involved in a benefit administration set up? What if that tool can skip the manual tedious process and achieve higher efficiency?

As more and more organizations adopt Ben Admin Systems to manage employee benefits, the need for an online tool that can streamline the process for benefit administrators becomes essential.

Our client is among the top 10 insurance brokerage firms in the United States and is one of the most powerful and influential leaders in the industry. They have been providing insurance products and services to corporations, trade associations, governmental institutions and individuals for more than 50 years.


Our client was manually reconciling and transforming payroll data received from their client organization and the employee/dependent census data received from various carriers for different lines of business. The manually transformed data was organized into two major files acceptable by Ben Admin Systems, one file containing enrollment details (opted plan types, effective plan date, benefit amount, coverage level and so on) and the other file has demographic information (name, age, relationship, DOB and so on).

Our client’s benefits administrators had to prepare these files for each of their client organizations. The manual steps posed challenges and complexity in handling benefit administration. Our client needed a scalable web-based solution with the below-mentioned features:

  • Capability to resolve data conflicts, because of data discrepancy observed in the employee/ dependent information fetched from different carrier’s census files 
  • Interface to generate files containing dependents’/ employees’ demographic details and benefit enrollment file containing details on opted benefit plans as per the applicable format of the selected Ben Admin Systems (Bswift, PlanSource, Employee Navigator, and so on)


  • Varied setup rules and file formats for each Ben Admin Systems
  • No standardization in census file formats received from different carriers
  • High turnaround time consuming around 3 to 5 days
  • Semi-structured nature of the data received
  • High threat to data security 


Imaginea proposed to build a web application that can generate the final output files to be uploaded to set up the employee/ dependent demographic and benefit details in Ben Admin Systems. The key functionalities of the solution are:

  • Import Files: An interface to upload employee data files received from the client’s payroll system and census files received from multiple carriers
  • Template Management: A functionality to provide the ability to configure or set up rules for relevant data extraction from varied census file formats 
  • Conflict Resolution: An interface to resolve conflicts due to data discrepancy observed in the dependent data fetched from different carriers
  • Ben Admin Systems – Carrier Mapping: An interface to map carrier-specific benefit plan codes with the predefined benefit plan codes of Ben Admin Systems and creating rules to define employee coverage level
  • Rules engine: A customized rule engine developed based on the respective Ben Admin Systems (like Bswift, Plan Source, Employee Navigator) to transform data and generate the desired final output files 
  • Reports Dashboard: An interface to generate and download dependent demographic file, orphaned employee/ dependent report, new hires report, non-active employee report and benefit enrollment file

Tech stack

How Our Solution Helped

85% reduction in turnaround time to set up a Ben Admin System, from reconciling and transforming employees’/ dependents’ data, organizing demographic and benefit details and, finally, uploading files in respective formats

Overall Approach

The application is designed to provide seamless performance to the operations team. We aimed to build a web application that maps employees with their dependents across various census files, automatically identifies records with any discrepancy in the data and finally processes and transforms the data to generate the Ben Admin Systems’ uploadable files. The details of the key components built are:

  • Data mapping and transformation rule engine: We built a rule engine, using which columns of data sources (census files, employee listing file and so on) are mapped after parsing, and transformed as per the rules configured in the system. Any conflict while comparing the data is flagged and rendered on the portal for resolution.
  • Data Security: Data security was ensured using encryption and network isolation.

The application’s architecture is designed to ensure the scalability and adaptability of the system with changing business needs. Key features implemented to achieve it are given below:

  • Ability to scale on demand for volume concentration on specific calendar months using Azure App service
  • Change in existing formats or new format configuration with a click of a button using Azure Cosmos DB, Azure Blob storage
  • Open architecture to ensure support for new Ben Admin Systems without any impact on existing application


  • Increase in operational efficiency
  • Improvement in process handling and data reliability
  • More than 90% reduction in chances of manual error

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