Bad valuations cost underwriters $7 billion a year on business interruption insurance -- but third-party data can end the problem.
It is estimated that commercial property writers lose out on more than $7 billion annually in business interruption insurance, a line that could deliver increased and sustainable earnings upside annually but has often struggled to do so. This loss represents not only undervalued policies, but also income lost because of premium calculations that are not commensurate with risk.
As with other property business, the No. 1 culprit is the decades-old difficulty that insurance companies’ face establishing adequate coverage limits for property lines -- and business interruption insurance (BII) often has worse results than insurance on buildings and contents.
For the past 10 years especially, the property insurance industry worldwide has been buzzing with concerns about coverage adequacy for BII. The problem affects both business owners policies (BOPs) and the larger package policies (CPP/SMPs).
Caroline Woolley, senior vice president at Marsh’s Business Interruption Center, wrote a comprehensive report in 2015 summarizing the challenges the industry faces making BII coverage profitable. Woolley lays out five major obstacles that agents, companies and brokers face when underwriting this coverage line. Woolley says the No. 1 problem is simply “getting the values right” when policies are first written and again at time of renewal.
The valuation concern stems from the fact that there has been no standardized, simple-to- learn-and-use insurance-to-value (ITV) system for BII coverages similar to what is done today for buildings and contents.
No. 1: Getting the values right
According to a survey conducted by the Chartered Institute of Loss Adjusters in 2012 ((and quoting from PMWBG)), 40% of declarations were deemed too low by about 45%. More recently, PMWBG research shows as much as 58% of BII coverages are undervalued by 48%
, suggesting the problem is getting worse at a time when demand for property insurance is in decline and competition is fierce.
Inadequate coverage disenfranchises consumers, and improper valuation undermines providers. In a very competitive marketplace, where too much supply is chasing dwindling demand, carriers losing on the valuation front lose reputation, financial advantage and long-term revenue.
From the inception of BII coverage in the 1930s, calculating risk-specific BII limits has not been easy. The BII coverage addresses shortfalls in the margins corporations face when loss occurs, so underwriters, brokers and agents should understand key variables in the insured's financials. Unfortunately, not enough industry professionals are proficient in this area, leading to costly exposure errors, pricing mistakes and the age-old dilemma of undervaluation.
As important is the fact that, unlike with other lines, there has been very little third-party data to aid insurers with BII calculations.
When losses occur, it’s too late in the game to correct undervaluation problems. The impact, especially in today’s economy, where wildfires, storms and other disasters routinely happen, has caused companies like Marsh to look again at the coverage line, suggesting the need for industry-standard ITV calculation tools.
Now, modern web-enabled technology offers both substantive raw data on businesses that actuaries will want to work with to improve pricing models, at the same time carriers will use the program’s web-based ITV system to calculate detailed BII coverage reports for the majority of businesses found anywhere in the U.S. Virtually any enterprise can be valued, with complex insurance specific data sets searched automatically on behalf of the user to both pre-fill input and create BII reports.
First Step to Success
Vast amounts of insight about corporations and their supply chains can be aggregated on to estimate BII limits in seconds, accessible anywhere from the Internet.
In the case of the BOP sector, actuaries and pricing managers have instant access to large amounts of aggregated data for the various sizes and types of business insured, to develop more representative and localized pricing models. Users can also adjust models automatically for the business opportunity rather than offer one-size-fits-all pricing. Additionally, because core data changes annually, savvy users can also upgrade model variables.