The Severe Implications of Payroll Misclassification & Premium Fraud

In 2011, the New York grand jury released a report showing that New York City’s construction industry cost the city and state approximately $500 million as a result of unpaid workers’ compensation premiums, in which businesses paid salaries off the books or purposely misclassified employees as independent contractors. This is just the tip of the iceberg. From 2008-2012, construction had misclassified their payroll totaling at $76.8 billion with 15 class codes representing 75% of the total problem.

Construction is the biggest culprit in premium fraud and misclassified payroll, but nearly half of all workers’ compensation policies have some level of misclassified exposure. So what does it mean if one out of every two policies written have inaccurate payroll numbers?

Keep in mind that not every policy reaches a threshold where the level of misclassification is critical enough to examine. Interestingly, we have found that large company insureds (e.g., large construction firms) tend to have less exposure to misclassification because they understand they will be physically audited more frequently. Smaller policies generally have a higher rate of misclassification.

That being said, it is impractical and incredibly unprofitable to physically audit every policy, especially smaller policies. Instead, many carriers tend to focus their audit policies on policies above certain premium levels. In doing so they a) still expend significant energy (and cost) auditing policies that turn out to be in compliance, and b) they miss the larger (but more fragmented) occurrence of misclassification which exists “below the waterline.”

The good news is that there are strategies to address the information gap that even the playing field from a data standpoint. Better yet, you can gain a competitive advantage by identifying misclassified payroll proactively. One benefit is being more exact in the types of policies to audit by going beyond traditional business rules that trigger an audit, such as industry, size of policy, etc. Having better information on class code exposure by policy is a big part of solving the misclassification issue.

For more information, check out this easy to follow guide with steps that are proven to help carriers get a better handle on this issue.


Kirstin Marr is the chief brand advocate for Valen Analytics, paving the way for prospective clients to lead the innovation initiatives required to compete in today’s marketplace. She has a passion for building companies that invent leading-edge technologies to improve customers’ lives and solve the inefficiencies that exist in many traditional marketplaces. Kirstin also has a long-standing commitment to philanthropy and community leadership. She was most recently Board President for Colorado MESA, a non-profit that serves underrepresented and economically disadvantaged students to graduate from college and successfully pursue careers in Science, Technology, Engineering and Mathematics (STEM). She also co-founded a non-profit to benefit the Teen Lounge at Children’s Hospital Colorado.