By Margo Jenkins (AAA Life) & Rob Strange (Evadata)
​
The landscape of insurance fraud is rapidly evolving, and life insurance claims are no exception. With the accelerated development and accessibility of Artificial Intelligence (AI) and generative AI tools, claims examiners are facing sophisticated new threats. Understanding these emerging risks and adopting proactive AI-powered defenses are crucial to safeguarding your company’s financial health and maintaining trust with legitimate policyholders.

“Fraud prevention is easy”, said no person, ever.  An effective fraud prevention strategy is multi-faceted, requiring everyone in an organization to be on board – from the C-Suite to boots on the ground.  For an organization to manage fraud risks and the inherent financial or reputational losses, it needs to know what the risks are, where the risks are, who may exploit any weaknesses, and what the ultimate cost to the organization might be if fraud occurs.  The most effective and comprehensive way to identify such risks is via a fraud risk assessment.  This process seeks to proactively identify and address the organization’s vulnerabilities to internal and external fraud and determine how the organization will respond to these risks.

​Should CPT codes be used for billing or occupation analysis? The answer is both. 
 
In a recent lawsuit, an argument was raised that Current Procedural Terminology (CPT) codes were created and are used for billing purposes, so they should not be used in determining occupation for some reason.  One of the arguments made by an expert in the case was that charges were used, which is not a realistic measurement, as reimbursements and payments received are always less than the charge amount.  The counter argument is that charges are only one metric we use, and we recommend and use Relative Value Units (RVU) and units in all CPT analyzes.     
 
This blog will show why they can be used for both billing and the verification of a physician’s occupation.