Optimising commercial P&C deductibles

Commercial property and casualty (P&C) insurance underwriters use deductibles or self-insured retentions to incentivise their insureds to avoid submitting small or “nuisance” claims. Risk retentions also decrease the likelihood of a moral hazard developing, as insureds have “skin in the game”.

Commercial insureds like retentions because they can balance affordability of premiums against the affordability of a potential claim. Problems often arise, however, as insureds do not understand the math behind the insurance company’s premium calculations, or how to anticipate premium savings for changes in deductibles. As a result, insureds often buy too much insurance and do not take advantage of significant savings opportunities.

This problem is often compounded because insurance agents and brokers are incentivised to maximise insurance premiums and consciously, or subconsciously, push back on insureds’ desires to benefit from raising deductibles.

A professional risk manager’s job is to resist the sales tactics of insurance intermediaries and allow appropriate underwriting data to drive positive results in insurance negotiations. If an insured understands the components of an underwriter’s premium quote, it can be helpful in balancing risk and return.

Insurance premium is the money insurers collect to pay for potential future claims. Actuarial projections are used to predict an insured’s probable annual claim amounts or “loss pick”. Once an underwriter understands probable losses, it can calculate a premium by dividing the loss pick by a “target loss ratio”, or the amount of losses as a percentage of premiums needed to cover company expenses and desired underwriting profits. A simplified example may be useful at this point.

Insured: XYZ Corporation
Insurer: Columbus Insurance
Type of insurance: Business liability
Limit requested: $5 million
Deductible requested: $nil
Ground-up loss pick: $25,000
Target loss ratio: 50 percent
Premium: ($25,000/0.50) = $50,000

This initial quote is delivered to the insurance agent and then to the insured. At this point, many insureds simply pay the premium and move on. However, in this case, XYZ may have missed an opportunity. XYZ has a loss history shown in Table 1.

XYZ’s loss record is a perfect example of an insured that may be overpaying and buying too much insurance. After the large losses in 2014, management engaged a risk manager to help reduce the loss exposures of the company. Losses since then have been significantly lower than the previous five years. However, to an actuary and an underwriter, the loss pick is still expected to be $25,000 per year.
Now may be a great time to explore a higher deductible.

Many insureds do not take the next step, which is to determine what premium credit should be available for raising the deductible. To do this, insureds need to “stratify” their loss history, or break it down into layers based on probable deductible amounts.
Using the same 10-year loss run, stratified losses are shown in Table 2.

Table 2: Stratified losses over 10 years

This means that from the underwriter’s perspective, 80 percent of the expected losses would fall below a $10,000 deductible, and 60 percent below $1,000. The risk manager can now request a new quote, and armed with this new information, is better equipped to negotiate from a position of power.

The new quote is as follows.
Insured: XYZ Corporation
Insurer: Columbus Insurance
Type of insurance: Business liability
Limit requested: $5 million
Deductible requested: $10,000
Ground-up loss pick: $25,000
Losses insured: $5,000
Target loss ratio: 50 percent
Premium: ($5,000/0.50) = $10,000; or minimum premium of $3,000/million limit requested = $15,000

XYZ saved $35,000 on fixed cost premiums by taking a $10,000 deductible. These savings will be offset by incurred losses, but due to their new loss-control efforts, the five-year expected losses are only $2,500 per year. This would save them $32,500 per year net of expected losses. They will reduce their expected cost of risk by 65 percent.

There are caveats to this analysis. First, insurance companies and agents resist straight-line premium reductions of this kind. They will fight to keep their premium amounts up, regardless of the data. Second, note that the quote was subject to minimum premium; that is, even if XYZ had no losses, insurance would still cost at least the minimum premium (an amount to cover uncertainty and the insurer’s cost to issue the policy). Third, insurance quotes are derived from more than just loss history. If XYZ’s risk exposure is unusual or particularly hazardous, insurance premiums will be modified to reflect it.

From the perspective of captive owners and managers, imagine if this effort were conducted across the insured’s entire portfolio of insurance coverage. Savings could be used to fund additional risk management initiatives, further shore-up captive reserves, or increase premiums to the captive by including deductible buy-down coverage. Often, savings from this effort more than pay for the costs of setting up a captive and/or covering annual expenses.

Randall Davis is managing partner at Delphi Risk Management. He can be contacted at:  randalldavis@delphirisk.com