Large Scale Model Migration Delivers USD 10MM in Savings

Business Objective

Our client, a Fortune 100 company, is among the world’s largest provider of life insurance, P&C insurance, and annuities products serving 90+ million customers. The client wanted to embrace open source technology across the organization and reduce dependency on proprietary tools and technologies. As part of this endeavor, our client wanted to:

— Migrate Analytics models from a license-based analytics tool to open source technology
— Design an end-to-end open source integration strategy
— Design a continuous model monitoring and maintenance framework

  • 75% of the analytics use cases lacked documentation around business requirements, data, modeling approach, model evaluation, and business impact determination.
  • No set process for model development or templates existed for any deliverable and no testing standard applied either
  • Lack of stable governance as the existing models were not version controlled. There is no audit review process to validate model methodology and results

Solution Methodology

Implemented an end-to-end analytics lifecycle process for large scale model migration ensuring consistency throughout the organization.

  • Understood analytics use case objectives and its implications in the business process
  • Identified technical and business stakeholders and connected with them to align on objectives
  • Gained detailed understanding of the data sources and open source infrastructure set up and dependencies
  • Designed the governance structure for the model development life cycle. Designed and created standard templates for each stage to main consistency across process
  • Identified components and methods for process efficiency
  • Migrated models from traditional (SPSS, SAS) to open source platform (Python) with elaborate testing so that the existing business cycle (upward or downward) is not affected by the change
  • Created detailed documentation and recommendation for model enhancement and improvement.
Business Impact
  • USD 10MM estimated savings due to licensing cost, model improvements and process efficiency

  • ~300+ analytics models migrated to open source across 12 Lines of Business

  • Improved process efficiency with reduced turnaround time and streamlined analytics process by developing reusable components.

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