Reducing Subsidies
 
 Frequently Asked Questions

Subsidies are minimized when firms pay premiums that fund the same percentage of expected future insurance costs. This is best measured by the ratio of losses to premiums, called the loss ratio. In a perfect system, everyone will have the same future loss ratio. The loss ratios have been adjusted so that the average loss ratio is 100% for ease of comparison.

We have studied the effect of the changes by comparing how different methods would have worked in the past. The results were first analyzed by looking at five different sizes of firm. The charts below provide two examples of these different size groupings to illustrate the effect of the new credibilities in comparison to the old. Within these size groupings, we analyzed the subsequent loss ratios of firms with different ranges of experience modification factors to see how well these experience factors would have worked.

Example 1: Mid Large Firms

For the Mid Large Firms (firms with approximately $262,000 - $688,000 in annual Accident Fund + Medical Aid Fund premiums before experience rating) the relative loss ratios are shown below for two groups of firms:

A bar graph showing the relative adequacy of premiums assessed for Mid Large Firms; relative loss ratios 2000 through 2004. The average relative loss group for this size group is adjusted to 100 percent. Using old factors, the twenty percent of the lowest mod firms had a relative loss ratio of 113.3 percent and the twenty percent of the highest mod firms had a relative loss ratio of 91.7 percent. Using new factors, the twenty percent of the lowest mod firms had a relative loss ratio of 98.4 percent and the twenty percent of the highest mod firms had a relative loss ratio of 99.7 percent.

Using the old factors, the firms with the low experience factors had more losses per dollar of premium than the firms with the highest factors. Using the new experience factors these two groups of firms have similar losses per dollar of premiums. This imbalance was corrected by reducing the credibilities for larger firms in the 2007 experience modification formula. This indicates that both groups are funding similar proportions of their losses, making the rating system fairer.

Example 2: Mid Small Firms

The second example looks at the relative loss ratios for the Mid Small Firms (firms with approximately $60,000 - $129,000 in Accident Fund + Medical Aid Fund premiums before experience rating) with the highest and lowest experience factors.

A bar graph showing the relative adequacy of premiums assessed for Mid Small Firms; relative loss ratios 2000 through 2004. The average relative loss group for this size group is adjusted to 100 percent. Using old factors, the twenty percent of the lowest mod firms had a relative loss ratio of 94.2 percent and the twenty percent of the highest mod firms had a relative loss ratio of 105.2 percent. Using new factors, the twenty percent of the lowest mod firms had a relative loss ratio of 96.3 percent and the twenty percent of the highest mod firms had a relative loss ratio of 102.7 percent.

Using the old factors, the firms with the lowest factors had lower losses per dollar of premium than the firms with the highest factors. This is the opposite of the situation seen with the Mid Large firms in Example 1 above. Using the new experience factors these two groups of firms fund a closer amount of losses per dollar of premium. This imbalance was corrected by increasing their credibilities in the 2007 experience modification formula.

Credibility weights in Washington vs. other states

The new credibility weights are closer to those used in other states in comparison to those used in 2006 and previous years, as can be seen in the chart below. The credibilities used in Oregon are similar to those used in most of the other states.

A chart showing the comparison of experience rating total credibilities between Oregon in 2004, California in 2005, Washington in 2006 and Washington in 2007. The expected loss at 2006 levels shows a decrease between the Washington in 2006 and Washington in 2007 up to approximately 3,000,000.

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