Overview

A US-based Class 1 freight railroad company was managing employee claims through a largely manual process. Complex labor agreements and lengthy approval cycles slowed reviews and made them harder to manage, increasing the risk of errors and fraudulent payments while affecting productivity and employee morale.

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A US-based Class 1 freight railroad company was managing employee claims through a largely manual process. Complex labor agreements and lengthy approval cycles slowed reviews and made them harder to manage, increasing the risk of errors and fraudulent payments while affecting productivity and employee morale.

To address these challenges, the company partnered with Tech Mahindra to modernize claims management with GenAI. Together, we digitized employment agreements, automated claims validation, and used historical claims data to support faster, more accurate decisions.

The streamlined workflow improved review consistency, reduced administrative effort, and created a faster, more scalable approach to claims management

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Industry Challenge

The client is one of North America’s leading freight transportation companies, operating a 32,500 mile-network. It manages employee claims against a complex set of employment agreements and review guidelines. As volumes grew, manual checks and cross-referencing became increasingly difficult to manage.

Nearly 25% of claims were paid automatically when review windows expired. This extended processing timelines, consumed operational capacity, and increased the risk of errors and financial leakage.

Our Approach and Solution

Employment Agreement Digitization

Digitized employment agreements to reduce manual validation effort and human error.

Automated Claims Validation

Implemented an intelligent business rule engine to validate employee claims against digitized rule mapping.

Claims Risks Insights

Analyzed historical claims data to flag invalid or high-risk claims.

Business and Community Impact

Our solution delivered measurable improvements in claims processing efficiency and financial risk, including:

  • Cut claims processing time by approximately 90%.
  • Annual invalid claims payouts were reduced by approximately 84%.
  • Eliminated auto-paid claims tied to expired review timelines
  • Built a scalable platform ready to support additional employee claims processes