AWS Based Data Ingestion solution for a Leading Financial Group in North America

Introduction

One of the top US Life & Annuity Insurer was looking to “Optimize the Actuarial model by better aligning work complexities, with the best and most efficient solutions that leverage latest technologies. This modernization would enhance the capability of the in-house actuarial talent to address and support high complexity high volume business needs of the Actuary team.”

Data Pipeline Modernization project consolidated actuarial data for each product line from on premise sources into a cloud based data environment. The consolidation of data included extraction of the source data, tokenization of sensitive data, curation of the data and ingestion into Data Lake. The Actuarial team is the consumer of downstream data. The project was conducted by product line, with Term Life being the first product, followed by Universal Life and Individual Disability Insurance. We designed and implemented Actuarial Data Lake solution using Amazon Web Services (“AWS”) technology and related tools as well as designed data pipeline framework including Orchestration, Automation and Data Governance (lineage, metadata dictionary, and glossary). To transform the Actuarial organization, the customer was looking for a strong strategic partners who could help re-imagine the future while continuing to deliver incremental improvements to the current state by driving efficiency and efficacy with a keen eye on quality and control.

EXL carefully crafted a solution and prepared a roadmap for the client, that leveraged a time-tested framework, beginning with the first wave that served as a strong proof point and continued scaling and accelerating impact through subsequent waves. There after, each wave followed a deliberate and consistent approach of “Discover & Design – Stabilize – Optimize” to continue moving up the efficiency and efficacy curves through the journey to the north star.

Our Solution

Data Pipeline Modernization project consolidated actuarial data for each product line from on premise sources into a cloud based data environment. The consolidation of data included extraction of the source data, tokenization of sensitive data, curation of the data and ingestion into Data Lake. The Actuarial team is the consumer of downstream data. The project was conducted by product line, with Term Life being the first product, followed by Universal Life and Individual Disability Insurance.

We designed and implemented Actuarial Data Lake solution using Amazon Web Services (“AWS”) technology and related tools as well as designed data pipeline framework including Orchestration, Automation and Data Governance (lineage, metadata dictionary, and glossary).

Solution Architecture

Solution

Testing

Testing is an important component of an effective solution development to ensure its reliability, identify and remediate defects/bugs, and to build the stakeholder confidence to consume the solution for driving desired business outcomes. EXL conducted Unit Testing , Integration Testing and Quality Assurance testing for the solution.

  • Unit Testing: Unit testing was done by the developers and incorporated as part of the CI/CD process. Pytest, a python based testing framework, was used to write and execute test codes. The comparison of the expected output with the actual output was done to ensure the credibility of the solution unit.
  • Integration Testing: Integration testing included process executions, process dependency checks and error handling.
  • Quality Assurance Testing: Quality Assurance testing will include validating some of the data after each process execution. For the MVP, the data check included:
    • Total Number of Policies by Year/Month
    • Total Claim amounts by Year/Month
    • Total Premium amounts by Year/Month

Project Management

EXL’s team consisted of Cloud Architect, Data Engineers, Business Analyst and worked alongside the client counterparts to design, build, and deploy the solution. EXL operated in an Agile way of working and delivered the end-to-end tested solution in sprints. EXL used Jira as the project management tool. Agile best practices such as daily stand-ups, sprint planning sessions , PI planning sessions and retro sessions helped in delivering the project on continuous releases and incorporating customer feedback with every iteration.

Business Value

Built Modern Cloud Data Pipelines

  • Consolidate and Streamline Data Sourcing across 7 different Admin Systems
  • Rapid and Iterative development approach with MVP’s delivered on an average timeline of 3 months

Rapidly Developed a Lightweight Accounting Rules Engine

  • Development of Accounting Rules Engine to Transform Model output into financial reporting
  • Iterative development process with MVP in 5 months
  • Saved the Accounting department hundreds of hours of manual work annually until customer Approximate cost savings of $500K (fraction of ongoing subscription to Cloud ERP/ARE).