AI And ML Adaptive Learning Helps Fight Medical Fraud

Machine learning (ML) algorithms inherently practice adaptive learning. If this sounds intimidating, you can look at it like an email filter. You initiate the identification of spam emails, then, over time, your email is able to identify spam without your assistance using algorithms, making your life much simpler. While modern day ML is capable of so much more, this is just a basic example of how that intelligent evolution works.

How AI and ML Can Help You

Through machine learning and artificial intelligence, algorithms can be trained to seek out any signs of fraud, then assign a risk score based on the details it finds. Following that, these pieces of information can be weighted to impact the scoring, with analytics software running models against it for accuracy. Once the best model is recognized, it is implemented in production. Humans do not have this inherent ability, nor do businesses have the time or resources to achieve this without ML and AI.

With the Centaur platform, our algorithm model can adaptively learn the signs of fraud, what the likelihood is that fraud has occurred, and if it needs to be sent to a human for final review. Machine learning is extremely powerful in this regard due to its ability to constantly adapt to new information and re-run scoring models as many times as necessary to see if there is a better model that be implemented. Overtime, the scoring just gets better and more accurate, saving your business money and effort in the long run through less fraud and less man hours.