
How Losses Get Evened Out to Make Ex. Mods More Accurate
Not all losses are the same.
Small, frequent losses need to be handled or "weighted" differently than oneoff severe losses that happen only occasionally. So, rating bureaus use "weighting values" and "ballast values" to arrive at exmods that more accurately predict your company's losses.
Below is the actual formula for calculating an experience modification factor:
Actual Primary Losses 
+ Ballast Value 
+ Weighting Value X Actual Excess Losses 
+ (1–Weighting Value) X Expected Excess Losses 
Expected Primary Losses 
+ Ballast Value 
+ Weighting Value X Expected Excess Losses 
+ (1–Weighting Value) X Expected Excess Losses 
What do these terms mean?
 "Primary losses" are the first $5,000 of any loss; "excess losses" are all loss amounts over $5,000. Losses up to $5,000 are included in full. Losses in excess of $5,000 are included on a discounted basis. In practical terms, this means that smaller losses have a bigger relative impact on your exmod than larger ones do.
 The "ballast value" and "weighting value" attempt to correct for the size of the risk. In statistics, the larger the pool sampled, the more accurate the sample is. Calculating exmods works in the same way — the larger the payroll base, the more accurately you will be able to predict your losses.
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In this issue:
This Just In...
Many States Offer Temporary Work Comp Classification Reductions During Pandemic
How the Pandemic Is Changing Workers Comp Forever
How Insurers Calculate Comp Rates
How Losses Get Evened Out to Make Ex. Mods More Accurate


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