Healthcare Insurance



About the Client

The client is a health insurance company operating in different sectors, such as retail, group and specialty businesses, and healthcare services. The company has over 90,000 employees in different verticals and specializes in clinical care, pharmacy solutions, provider solutions, and health informatics.

Business Challenges

Manual inspections to catch fraudulent transactions were time-consuming and repetitive
The payout delays caused significant mismanagement due to the accumulation of a large number of claims
Increase in transaction transactions led to decreased customer satisfaction

Business Solution

Royal Cyber’s data science experts created a machine learning solution to help the client’s system identify vital features and attributes of fraudulent transactions and automate the claims handling process to save time and cost for the team.

Key Outcomes


Decrease in deployment dependencies


Increase in customer satisfaction


Reduction in human resources investment

Our Customers Enjoy Our Process

Working with an industry-leading client in the health insurance space was a productive and learning experience for me and my team. We initiated by understanding the client’s project and its pain points, how the fraudulent transactions and manual inspection processes affected their time and resources, and eventually created a custom ML solution that would help them detect fraud claims and automate claims handling and payments.

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