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December 17, 2015

How to Assess Costs of Business Interruption

Summary:

The standard approach to calculations on business interruption overstates potential costs and leads to premiums that are too high.

Photo Courtesy of thinkpanama

As a professional loss accountant with more than 20 years of experience with business interruption (BI) valuation, I can understand why policyholders struggle with finding a repeatable, efficient system that produces an accurate measurement of their BI exposure. Over the years, some of my clients recognized the issues with the traditional BI values approach, and decided to make a change. Unfortunately, too many companies continue doing what they have always done, even when there is a better way available.

BI

Consider for a moment, just how important BI information is to your underwriter. The numbers you report give the underwriter the basis for writing coverage and calculating premium. Each renewal provides policyholders the opportunity to present their unique BI exposure. Unfortunately, this opportunity is often squandered because of a misunderstanding of business interruption values and the exposures they represent. The point of this article is to share a proven, alternative approach.

Understanding BI Values

First, there’s the ratable value. It is the “big number” that is calculated for the business as a whole, assuming a 12-month, total shutdown of all revenue-generating operations. This worst-case and often unrealistic scenario is the information requested by the insurance company, usually in the form of a one-page worksheet. Without additional information, the underwriter will use this information to set limits and charge premium.

The ratable value calculated is somewhat meaningless, except that it establishes the base assumption that is used as the BI value in all other scenarios, such as unincurred cost categories. The ratable value is seldom a reflection of your exposures. Better ways to assess your exposures are to examine your maximum foreseeable loss (MFL) and probable maximum loss (PML) scenarios.

What Is Maximum Foreseeable Loss?

The MFL, as the name indicates, is the worst-case scenario. This is not as extreme as the ratable value scenario, but pretty close. The assumptions used here include a complete breakdown of protection and loss mitigating factors while you are hit where it hurts at the worst possible time. An example would be the loss of a unique distribution center to a retailer during the holiday shopping season — say the distribution center that handles online orders goes up in smoke on Cyber Monday.

The factors used to measure the ratable value would be used in this scenario to determine the business interruption value. Certain assumptions may change depending on the duration of the loss scenario. For example, labor expense may be considered completely saved in the ratable value scenario because of the assumption that there is nothing left, but only partly saved in an MFL scenario.

What About the Probable Maximum Loss?

The PML is the same as the MFL, except that loss mitigation efforts and protections work properly. The PML also takes into account pure extra expenses used to retain customers. The PML can help with decision making on purchasing extra expense coverage.

What Happens in Underwriting?

Although I’m not an underwriter, I’ve typically seen insurance companies take an engineer’s approach to MFL and PML scenarios that vary only in duration. This singular perspective does not account for the rest of the pieces of the puzzle. The other pieces are the finer details that actually occur during a claim. In a real claim, topics like seasonality, make-up and outsourcing would surely come up, but you won’t see them on any BI worksheet.

The MFL and PML should be based on realistic loss scenarios and measured as if they were a claim. Simply applying the ratable value to loss-period assumptions produces misleading and inflated numbers. This is precisely why it is in your best interest to develop your own valuation method based on real scenarios.

Why Create Exposure Scenarios?

If BI values are based on assumptions, and you are using the worksheet, then the assumption is a 12-month loss scenario. Can you imagine a scenario in which your operations would only be affected for six months? The worksheet makes a blanket assumption of 12 months whether realistic or not. Coming up with various loss scenarios by location would flesh out a more realistic representation of the impact of each particular loss. The scenarios would also highlight high-risk locations along your supply chain, which could improve your business continuity planning.

An exposure analysis project is not only an accounting project; it’s an integrated business exercise offering multiple benefits to an organization. The goal is to identify and examine loss scenarios and the resulting ripple effects.

It isn’t necessary, nor is it practical, to anticipate every possible loss scenario. It’s better to prioritize by perceived risk and probability. Then, develop a good sampling of loss scenarios from which you can determine the impact to operations and the mitigating actions that would be taken. Depending on the exposure, involve the appropriate internal personnel, e.g., operations, sales, business continuity, IT and accounting. The external experts you may involve are your broker, legal counsel and, of course, a forensic accounting firm that specializes in insurance work. Additionally, your company’s business continuity plan (BCP) and incident response plan should be factored in. However your scenarios play out, the loss accountants can calculate the business interruption as though it were an actual claim.

As you can see, this approach would produce a more accurate BI value by location and overall. It’s the right way to look at business interruption, so make it a part of your approach with underwriters.

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About the Author

Christopher B. Hess is a partner in the Pittsburgh office of RWH Myers, specializing in the preparation and settlement of large and complex property and business interruption insurance claims for companies in the chemical, mining, manufacturing, communications, financial services, health care, hospitality and retail industries.

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