Artificial Intelligence

Reducing health insurance claims expenditure by 20% on average, by identifying fraudulent activity.

Upcoding

When a more expensive procedure is billing for, when a less expensive procedure is performed.

Ghost Billing

Billing for services not rendered.

Improper Bundling

Bundling or unbundling services in order to hide excess charges.

Medical Durable Equipment Not Rendered

Equipment that is charged to insurance but never distributed.

Drug Diversion

Prescription drugs obtained for distribution on the streets.

Doctor / Pharmacy Shopping

Visiting multiple providers for the same diagnosis within the same period of time. Typically done to obtain more prescription drugs.

Waste & Abuse

Overcharging for services rendered.

Identifying fraud based on behaviors.

Identifying fraud based on behaviors.

Our AI partner uses algorithms that are based on sophisticated and extremely detailed fraud profiles that have been created and vetted with experts inside the healthcare industry. Patterns that are found in the data overlay on top of behavior profiles to get the matches needed to prove out fraud.    

Detecting fraudulent behavior and wrapping it around mathematical principals found in the more familiar “simplistic” AI that we see today is what our partner has termed Psychometric AITM.    

Combining math with the behaviors derived from human neural networking and decision making processes  determines what is statistically improbable and what it is fraud.  

False positives are prevented by requiring evidence of fraudulent behavior to be abundantly evident through highly confident P-Values.

AI FAQs

  • Self-Insured Corporations
  • Health Care Systems
  • Pensions, Unions
  • Federal and State Governments
  • TPA’s
  • Airlines
  • Savings are rarely less than 20% on post adjudicated claims
  • Opportunity for self-insured companies to reduce claims expenditure from fraudulent activity
  • Prevent the abuse of taxpayer funded programs, to alleviate financial burdens of healthcare on the government and free up resources for more productive allocation
  • Combine and relate the variables which result in a stronger predictive value for chronic opioid use, thus enabling an opportunity to engage early with the employee who may need interdiction
  • Safer work environment

Benefits fraud can result from the actions of plan members, service providers or both in tandem. Some fraud is not intentional. An example of intentional fraud is Plan members start submitting claims for services never provided or for ineligible products, such as getting dress shoes and billing them as orthotics. Organized Crime Rings are systemic in the Health Care Benefit platforms, because it is easy to perpetrate schemes and abuse that is easily concealed in Big Data.

Your privacy and the privacy of your Plan Participants is very important to us. All data is encrypted, so we never have access to personal data.

Cost growth in medicine is driven by multiple problems.

 

Fraud is a major cause, as the costs are transferred to the general population through increases in insurance premiums, provider charges and taxes.

 

Waste and abuse is another major cause. Many medical providers game the system by charging the absolute maximum amount insurance will allow. This drives the insurance companies to increase premiums due to the increasing provider charges.