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Experience Rating Mod Calculator

Calculate workers' compensation experience modification factor based on actual vs expected losses.

About this calculator

This calculator follows the real structural shape of the NCCI workers' compensation experience rating formula: Experience Mod = (Primary Actual Losses + Excess Actual Losses × Excess Weight + Ballast) ÷ (Primary Expected Losses + Excess Expected Losses × Excess Weight + Ballast). The core idea is that a large single claim shouldn't swing an employer's rating as much as the same total in smaller, more frequent claims -- so losses are split into a 'primary' portion (frequency-driven, weighted fully) and an 'excess' portion (severity-driven, weighted down by Excess Weight), and a Ballast Value is added to both the numerator and denominator to stabilize the result. Actual Losses only affects the numerator, so raising it always raises Experience Mod; Expected Losses only affects the denominator, so raising it always lowers Experience Mod -- these two relationships hold regardless of how the other inputs are set.

This tool is a simplified illustration of the real formula's structure, not a reproduction of NCCI's actual published tables: the real primary/excess split is determined per individual claim against an official, state- and year-specific primary loss threshold (not a flat percentage of total losses applied here), and the real weighting value is itself derived from published credibility tables keyed to the size of Expected Losses, rather than set directly by the user. Treat Ballast Value and Primary Loss Weight here as adjustable illustrative levers for exploring how the formula behaves, not as figures to look up from a current rating worksheet.

Inputs

$
$
$

Results

Experience Mod

0.91

Premium Impact

-9%

Primary Actual Losses$240,000.00
Excess Actual Losses$560,000.00
Mod Deviation (%)-9%
How to Use This Calculator
  1. Enter Actual Losses (real incurred losses) and Expected Losses (based on payroll and class rates) for the experience period.
  2. Set Ballast Value, the stabilizing constant that dampens how much a single bad or good year swings the mod.
  3. Enter Primary Loss Weight — the share of losses classified as primary (frequency-driven, generally weighted more heavily) versus excess (severity-driven).
  4. Set Excess Loss Weight, the reduced weighting applied to the excess (severity) portion of losses in the mod formula.
  5. Review Experience Mod: 1.00 means actual losses matched expected exactly; above 1.00 raises premium, below 1.00 credits it.

How the result changes with Expected Losses

Expected LossesExperience ModPremium Impact
$500,000.001.1616%
$750,000.001.022%
$1,500,000.000.75-25%
$2,500,000.000.56-44%

What each input means

Actual Losses
Total actual incurred losses for the experience period
Expected Losses
Expected losses based on payroll and class rates
Ballast Value
Ballast (stabilizing) value to prevent extreme mod swings
Primary Loss Weight
Proportion of losses classified as primary (frequency-driven)
Excess Loss Weight
Weight given to excess (severity-driven) losses in the mod formula

How this is calculated

Worked example, using the default values

  1. Identify Input Parameters
    5 parameters
    Actual Losses = 800000, Expected Losses = 1000000, Ballast Value = 500000, Primary Loss Weight = 0.3, Excess Loss Weight = 0.1 = 5 input(s) provided
  2. Calculate Experience Mod
    Experience Mod
    0.91 = 0.91
  3. Calculate Premium Impact
    Premium Impact
    -9 = -9%
  4. Calculate Primary Actual Losses
    Primary Actual Losses
    240000 = $240,000
  5. Calculate Excess Actual Losses
    Excess Actual Losses
    560000 = $560,000

Engine last updated . Checked against 1 independently-derived test — how we verify calculators. Built by Paul Gunder, a software engineer, not a licensed financial, medical, or legal professional.

Frequently Asked Questions

Why does raising Actual Losses always raise Experience Mod?

Actual Losses feeds only the numerator of the mod formula (through Primary Actual Losses and Excess Actual Losses), while Expected Losses -- which sets the denominator -- doesn't change. Since the denominator stays fixed, a bigger numerator always produces a bigger ratio, so Experience Mod rises whenever Actual Losses rises, regardless of how Ballast Value or the weight inputs are set.

What does Ballast Value actually do?

Ballast Value is added to both the numerator and denominator of the mod formula. Because it's added equally to both sides, a larger ballast pulls the overall ratio toward 1.00 -- it dampens how far actual-versus-expected loss differences can push the final mod, which is the real formula's mechanism for preventing a single unusually good or bad year from producing an extreme rating swing.

Is the Primary Loss Weight the same as how real insurers split primary and excess losses?

Not exactly. This calculator applies Primary Loss Weight as a flat percentage split of total losses for simplicity. The real NCCI methodology instead splits losses per individual claim against an official primary loss threshold published for each state and policy year, so an actual experience mod worksheet won't match this tool's split exactly -- treat this as an illustration of the formula's shape, not a reproduction of the real per-claim methodology.

What does an Experience Mod above or below 1.00 mean for premium?

A mod of 1.00 means actual losses matched expected losses exactly, leaving standard premium unchanged. A mod above 1.00 means the insured's losses ran worse than expected and premium is surcharged; a mod below 1.00 means losses ran better than expected and premium is credited. Premium Impact translates that deviation into a percentage change.

Does this calculator use current NCCI credibility tables for the weighting value?

No. Real NCCI experience rating derives the weighting value (often called 'W') from published credibility tables that scale with the size of Expected Losses, rather than letting the user set it directly. This calculator instead exposes Excess Loss Weight as a direct adjustable input, which makes it useful for exploring the formula's structure but means it will not reproduce a specific state's current official weighting.

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