Advanced Analytics, paired with cloud migration, led
to faster and more accurate anomaly detection for a
top 10 U.S. healthcare company.
When this company faced challenges in its claims processing and fraud, waste, and abuse detection process, it partnered with CapTech to analyze the issue and engineer a cloud-based solution. This resulted in increased speed and flexibility in delivering new advanced analytic models to the business.
Challenge
Increasingly, insurance companies are leveraging data and analytics models to assist with fraud detection, but the road to adoption has not been without obstacles. Slow processing times and outdated models hinder the ability to fully utilize data.
A top 10 U.S. healthcare company’s anomaly detection team leveraged predictive models for a more methodical approach to identifying claims, but the technology behind these models was tied to on-premises systems. This typically resulted in slow processing and a delay in the timelines to deliver new models. The team had previously attempted a move to the cloud, but efforts stalled, leading to a distrust of cloud-based systems.
The company engaged CapTech for an in-depth analysis of the issue and recommendation for a solution.
Approach
The CapTech team recommended a cloud-based system
to improve efficiency in the delivery and execution of
advanced analytic solutions. This recommendation was
met with some hesitancy from the client’s leadership
team due to the previously attempted cloud migration.
To validate the benefits of a cloud-based system, the
CapTech team delivered a proof-of-concept, which
demonstrated a scalable, integrated environment with
centralized data access. This built confidence around
the move to the cloud and the value it would bring.
Once the client agreed to move forward with the cloud-
based approach, the CapTech team designed and
implemented a single, integrated platform through AWS
with an end-to-end unified integration strategy, utilizing
S3, Glue, Athena, SageMaker and Lambda. The client
did not have an existing cloud infrastructure, which
necessitated building a complete data pipeline and
cloud-native architecture. Through the cloud platform,
the CapTech team was also able to create architecture
that allows for containerized deployment of advanced
analytics solutions, leading to increased access to key data.
Results
The new cloud-based platform resulted in significantly
faster, more efficient, and more reliable model delivery
timelines, leading to a faster and more accurate anomaly
detection process.
The success of this project paved the way for the client to
leverage the cloud in other areas of its business. CapTech
developed a training plan and roadmap that enabled the
client’s existing IT team to develop the skills necessary to
manage and maintain the cloud platform. By the completion
of the project, the CapTech team had successfully
completed training for a team of the client’s employees.
