Case Study - Artificial Intelligence

AI in Healthcare Fraud Detection

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Artifical intelligence

A major healthcare provider in the US faced a growing issue of fake claims impacting their finances and reputation. In urgent need of a solution to maintain trust and protect patients, they collaborated with Codelulu. Due to Codelulu’s smart approach, the healthcare provider could quickly identify and prevent fake claims, protecting their resources and maintaining the reliability of their services.

Our important client, a big healthcare provider in the US, had a big problem. They were dealing with a lot more fake claims, which not only cost them money but also put their good reputation at risk. Because healthcare is under scrutiny and people need to trust them, they need a clever solution to stop dishonest practices and protect their patients’ well-being.


The healthcare provider had a big issue with fake claims that were risking both their money and good reputation. To fix this issue, they knew they needed a powerful detection system that could seamlessly fit with how they currently operate. This system had to fight against fraud while also easing the heavy manual work their staff had to do.

Our client wanted a solution that not only caught the current fraud tricks but also learned and adapted to new ones. They needed to continue providing excellent care, maintain trust in the industry, and run their operations with integrity. All this while staying ahead of the constantly changing ways people try to cheat the system.


Codelulu made a plan to assist our partner’s team with their claim processing issues. We joined forces to understand their specific situation, searching for signs of fraud by studying patterns with our data-focused method. With Big Data analytics, we spotted subtle differences in how claims were described, all thanks to Natural Language Processing (NLP). After that, our team created and trained smart computer models, customized to fit the provider’s previous data. This led to a very dependable system that can accurately predict and catch fraud.

What makes our solution special is that it keeps getting better as it learns from new data. This means it can always stay on top of the latest tricks used by fraudsters. Our solution smoothly fits with the provider’s current technology, making the change easy and improving how well they work.

Technology used

  • Data Analytics Platforms: These are full systems made to manage and analyze really big amounts of data.
  • Machine Learning: These are clever models that learn, predict, and accurately identify fraudulent patterns.
  • NLP: This is used to understand and analyze the language in claim submissions to catch any signs of fraud.
  • Automated Data Processing: This is a way to efficiently handle large amounts of claim data by automating the processing tasks.


When we introduced our AI detection system to the healthcare provider, things took a positive turn. We saw a big 30% decrease in fake claims right off the bat, proving the system worked well from the start. As time went on, the impact got even better, and there’s now a lasting 11% drop in fraudulent activity.

Our commitment

Our AI system not only made the numbers better but also made patients and stakeholders trust the provider more. They now view the provider as reliable and ethical. The system can adjust to new fraud methods, and automated fraud detection saves time, making everything run more smoothly. This lets the provider’s team concentrate on their main goal: giving excellent healthcare.