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Experience Modification Factor

A multiplier comparing an employer's actual workers' compensation losses to expected losses for its industry and size, applied to manual premium at rating.

businessPublished 2026/06/10Last verified 2026/06/10

FAQs

What is a good experience modification factor?
Anything below 1.00 means the employer's losses ran better than expected for its industry and size, and it pays proportionally less than manual premium. Many construction project owners require a mod of 1.00 or lower to bid, and sophisticated buyers target the low 0.80s. Above roughly 1.25, some markets decline the risk outright.
How many years of losses go into the e-mod?
Typically three completed policy years, excluding the year that just expired. For a factor effective in 2026, the experience period would generally be the policies incepting in 2022, 2023, and 2024. Claims that remain open enter at their current reserve value, which is why reserve management directly moves the mod.
Can an employer lower its experience mod?
Yes, over time. Reducing claim frequency through safety programs has the largest effect, since primary losses are weighted most heavily. Closing open claims at or below reserve, using return-to-work programs to cut lost-time exposure, and correcting payroll or classification errors in the bureau's worksheet all help. Changes take effect as old years roll out of the experience period.

Related Terms

  • Experience Rating

    A pricing method that adjusts manual premium up or down based on an insured's own historical loss experience relative to expected losses for their class.

  • Experience Modifier

    A factor calculated from an insured's own loss history that adjusts workers compensation premium up or down from the manual rate — commonly called the e-mod.

  • Credibility Theory

    The actuarial framework setting how much weight an insured's own loss experience gets versus industry data when calculating experience-rated premiums.

  • Workers' Compensation

    Insurance covering employee injuries and illnesses arising from work.

Related Items

  • Gradient AI

    ML for underwriting risk and claims optimization

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The experience modification factor — commonly the e-mod, EMR, or experience mod — is a numeric multiplier applied to an employer's workers' compensation manual premium. It compares the employer's actual past losses to the losses expected for employers of similar size and industry classification. A factor of 1.00 is average for the class; below 1.00 earns a premium credit, above 1.00 imposes a debit.

How it works / Why it matters

The factor is calculated by a rating bureau — NCCI in most states, independent bureaus such as California's WCIRB in others — using a standardized experience-rating plan. The calculation typically draws on three completed policy years of payroll and loss data, excluding the most recently expired year because its claims are too immature to be credible. Losses enter the formula under a split-rating approach: each claim is divided into a primary portion (the first dollars, which measure frequency) and an excess portion (the remainder, which measures severity), with primary losses weighted far more heavily. The plan applies credibility weights derived from credibility-theory, so a small employer's volatile experience moves its mod less than the same experience would move a large employer's.

The design deliberately rewards frequency control over severity luck: five small claims hurt the mod more than one large claim of the same total cost, because claim frequency is the strongest predictor of future losses. This gives employers a direct financial incentive to invest in safety programs, return-to-work policies, and prompt claim reporting.

The e-mod also functions as a market credential. In construction and energy contracting, project owners routinely require bidders to hold a mod below 1.00, which makes the factor a gatekeeper for revenue, not just an input to workers-comp pricing.

In practice

Underwriters read the mod alongside its components: a 1.20 driven by frequency signals weak safety culture, while the same 1.20 driven by a single severe claim may be an anomaly. AI underwriting platforms such as Gradient AI incorporate mod history and the underlying claim detail into workers' compensation risk models, distinguishing employers whose experience is deteriorating from those whose mod overstates current risk. Agencies, in turn, use mod projection tools to show clients how an open claim will flow into next year's factor and what a reserve reduction would be worth in premium.