Roughly 2.3 million Americans are victims of medical identity theft per year and have to pay an average of $13,450 in out-of-pocket expenses–two-thirds of those patients reported paying over 13,500. Medical identity theft is estimated to cost the healthcare industry over $30 billion a year.
You will most likely realize a victim of identity theft relatively quickly, but in most cases the victim of medical identity theft is not discovered until they go in for medical treatments or for a life threatening emergency procedure. Medical identity theft can sit and grow for years without being known. Without A.I. systems in place this becomes a major issue.
Using NEMESIS, analysts can see claim details with trends and scores to identify whether this claim has a high probability of being a medical identitfy theft fraudulent case. Using the historical data of the medical insurance claims, analysts can easily build a predictive model to foresee the next move of the identity thefts.
This case requires the use of historical claim data, including geo-location information, time parameters, policy information, claim type, claim amount, insured person description etc.