Cloud-Based Data Platform for Efficient Claims Management

The Challenge

Launch worked with a Fortune 50 healthcare company that has significant technical debt due to the array of legacy systems that manage data, including systems inherited via acquisitions. Besides being complex, difficult to support, and inflexible, these systems result in insurance claims processes that require heavy manual effort and are error prone. Well over a thousand employees were required to manually perform benefits plan configuration processing of more than 30 million claims per year.

As the burden of dealing with an ever-increasing number of claims prevents their employees from providing timely and efficient service, healthcare companies of all sizes are struggling with negative sentiment from customers and providers.

Consistent data management is key to transforming the claims process into a faster, more efficient, more accurate engine that drives customer satisfaction, cost savings, and employee productivity.

Managing claims through outdated, fragmented legacy systems was creating several growing burdens for our client:

• Over 1,000 employees required to manually process 30M+ claims per year
• Multiple legacy systems inherited via acquisitions created data silos and inefficiencies
• High administrative costs (8% of healthcare spend vs. 1-3% in other developed countries)
• Frequent errors in benefits configuration, slowing service and eroding trust

The insurer needed a modern, intelligent platform that could process claims faster, more accurately, and at scale.

The Solution

Launch designed and delivered a cloud-native, intelligent claims platform that:

• Developed a modern, modular platform hosted in Azure with HIPAA-compliant architecture
• Leveraged NLP and ML to automate data matching and validation
• Built microservices for scalability, flexibility, and expedited deployment
• Streamlined benefits configuration and enabled faster system migrations
• Engaged stakeholders across business and IT to ensure alignment and adoption