In order to understand how experience modification factors are developed, we first need to take a look at how Workers’ Compensation premium is calculated. Workers’ Compensation covers employees for injuries occurring on the job. The most logical premium basis for this exposure is payroll. Premium is charged through a standardized job classification system. When coverage is written, it is based on estimated payroll divided by $100. This estimate is applied against a rate determined by the Fund’s actuaries. Upon expiration of the Fund policy, the payroll is audited to finalize the premium based on the actual total payroll the employer paid out during the year. The premium is then adjusted accordingly.

Premium calculated by the process above is called “standard” or “manual” premium. This premium is subject to modification based on the individual member’s claim experience. Modifying the standard premium ensures each member pays its fair share for the risk involved based on each member’s loss history. The MML Fund (and WC industry) use an experience rating process to accomplish this task. A statistical model, including the most recent three-and-a-half years of payroll and claim data, is used to calculate each member’s individual experience modification factor.

Simply stated, the experience rating process uses past claim experience of an individual employer to predict future claims and modifies premium accordingly.

Since the purpose of using an experience modification factor or “mod” is to predict future claims, the experience rating process gives greater weight to the frequency of claims than to severity of claims. The fact than an accident happened is more significant than how much it cost. An accident could cost a few hundred dollars, a few thousand dollars, or hundreds of thousands of dollars, depending on the circumstances and type of injuries incurred.

The cost of each claim is split between a primary amount and an excess amount. This places greater weight on frequency (number of claims) than severity (dollar amount of the claims) in the experience rating formula. Primary losses have greater weight than the excess portions of the same claims. Generally speaking, ten $3,000 claims will result in a higher experience modification factor than one $30,000 claim. The statistical formula considers other factors too, such as the size of premium. Experience modification factors are recalculated annually.

What experience rating does

Experience rating:

• distributes the total Fund premium among members based on their individual claim history (this results in equity across the Fund membership);

• compares members’ expected claims with actual claims to produce a debit mod (if actual claims are greater than expected), or a credit mod (if actual claims are less than expected);

• splits claims between a primary (limited) amount and an excess amount, placing more weight on the primary amount and reducing the impact of large claims;

• over time, it results in each member paying its fair share of total Fund claims.

What experience rating does not do

Experience rating does not:

• increase or decrease the total premium of the Fund; (Note:  The average experience factor is as close as possible to 1.00.  The experience rating process is a refinement that distributes premium based on individual member experience.)

• force a member to bear the entire cost of a large claim; (Note:  The excess portion of a large claim is weighted to reduce its impact.  Although claims are applied to the experience rating plan for three-and-a-half years, the Fund may continue to pay claim benefits for many years on a severe claim.)

• punish a smaller member.  (Note:  The experience modification factor is intended to mitigate large fluctuations in premium based on its formulation.)

What can a member do to reduce their Workers’ Compensation cost?  Decrease claim activity through workplace safety.  This can be accomplished with the implementation of solid Loss Control or Risk Management programs.  The MML has staff dedicated to these processes and are willing to offer assistance as needed.