  Fraud has led to a huge addition of expenses in health insurance sector in
India. The work is aimed to provide methods applied to health insurance fraud
detection. The work presents two approaches - a markov model and an improved
markov model using gradient boosting method in health insurance claims. The
dataset 382,587 claims of which 38,082 claims are fraudulent. The markov based
model gave the accuracy of 94.07% with F1-score at 0.6683. However, the
improved markov model performed much better in comparison with the accuracy of
97.10% and F1-score of 0.8546. It was observed that the improved markov model
gave much lower false positives compared to markov model.
