Insurers have long contemplated exiting the homeowners line ofbusiness because it's historically unprofitable. Recently,Allstate's CEO, Tom Wilson, said the carrier considered vacating thehomeowners market after the 2005 hurricane season. However,consumers have demonstrated their desire to bundle insurancecoverage, and Allstate ultimately realized that not offering bothauto and home was too big of a competitive disadvantage. Recentstudies show that homeowners is growing in both policies andpremium, yet the industry has only experienced four years withcombined ratios below 100 since 1990.

The trends we've seen develop in auto—like online consumershopping and increasingly sophisticated uses of data andanalytics—are starting to take hold in homeowners, and now insurershave to tangle with complex market dynamics while simultaneouslytrying to boost underwriting profitability. As online shoppinggains momentum, pricing competition will heat up, acquisition costswill increase, and retention rates will take a hit. If you don'thave the resources of a Top 20 insurer, this may represent afundamental shift in how you run your business.

All things considered, 2014 is a pivotal year in terms of howthe homeowners industry will turn around historically poor results.There is significant innovation occurring now to propelunderwriting and pricing strategies forward while things arerelatively stable. You don't want to fall behind when severeweather wreaks havoc on loss ratios…again.

How do I lower my loss ratio?

When we talk to insurers, they tell us their primary concern isreducing their loss ratio. A quick look at what's been donepreviously leads us to some exciting innovations happening rightnow in managing non-catastrophic loss.

One of the most successful strategies to date has been toseparate catastrophic (CAT) and non-catastrophic (non-CAT) losses,and develop specific CAT management strategies:

• To compensate for increased exposure, actuaries build in acatastrophe load into the rates by geographic region.
• Calculating probable maximum loss (PML) provides a worst-casescenario analysis that protects against inadequate reserves in theevent of a catastrophe like Hurricane Andrew, after which severalinsurers went out of business.

Early Non-CAT Strategies: Business Rules and ByPeril

Insurers have leveraged business rules based on location (e.g.,ZIP code) and property characteristics (e.g., age of roof) toreview those homes that trigger an “exception rule.” Many insurersfollow a rule to inspect properties at new business, while othersfocus on homes with high peril exposure. Much like CATmanagement strategies, insurers take specific pricing andunderwriting actions to minimize losses in fire-prone areas, as oneexample.

The industry falling short in generating underwriting profits,combined with the fact that 60 percent of losses are non-CAT, showsthat the strategies being used today are inadequate.

The Future of Homeowners Underwriting

To see the innovation happening now, look at the Florida market.It is well studied, carefully modeled, and subject to competitivepressures with dozens of carriers vying for the business.

There is a residual market for Florida property called FloridaCitizens. Citizens offers “takeout” opportunities to privateinsurers and provides detailed exposure and loss history statisticson individual policies. Insurers select a “wish list” of policiesthey'd like to assume onto private paper with granularcontrol.

After considering the expected hurricane loss, insurersprimarily look at the non-CAT cause of loss. It turns out that over50% of the homeowners losses in Florida are notcatastrophe related. This is a new paradigm where the primarydriver of profitability is reducing non-CAT loss at the policylevel.

2014 Brings New Categorization: Mitigatable vs.Non-Mitigatable

In order to drive down loss ratios and deliver consistentprofits, the industry needs to go deeper and answer:

• What caused the loss?
• Could something have been done about it?

What does “mitigatable” mean?

It's an important definition best explained through a simpleexample. Suppose an insurer has two identical homes on their bookof business, and both of them burn to the ground. One burnedbecause a candle was left burning overnight, and the other becauseof a faulty electrical box that wasn't up to code. Traditionallythese would be coded as non-CAT fire losses. However, one of theselosses could have been prevented by the insurer. Had aninspector visited both of these homes one day prior to the lossoccurring, they could have discovered the faulty electrical box.Alternatively, there would have been no way to find the burningcandle. The non-CAT loss that occurred because of the electricalbox should be coded as mitigatable, or within the control of thecarrier to reduce or prevent. On the other hand, the loss from thecandle would be coded as non-mitigatable, because the insurercannot reduce or prevent the cause of loss.

Why is it important to categorize losses this way? In additionto being able to predict loss ratio, it's now possible to predictthe percentage of the non-CAT loss ratio that is mitigatable. Anunderwriter can distinguish which homes to write based on theirability to reduce or prevent loss. Competitors without thisknowledge are susceptible to adverse selection by writing homeswhere the loss ratio cannot be influenced by the insurer.

This more sophisticated approach is successful according to aWillis Re study of the Florida Citizens data, that revealedsignificant variability in the predicted non-CAT loss ratio. Insome parts of the state, the mitigatable losses were actually moresignificant in terms of profitability than the catastrophic risk,because the catastrophes are so well reinsured.

The Florida example illustrates the unique opportunity availableto actively shape a future portfolio and a shift in mindset thatanalysis should be prospective—not retrospective. As marketconditions prompt insurers to stay competitive and profitable, theconcept of mitigatable and non-mitigatable classifications can helpaccurately assess risk, drive down loss ratio and produceprofits.

Dax Craig is the co-founder, president and CEO of Valen Analytics. Based in Denver, Valenis a provider of proprietary data, analytics and predictivemodeling to help insurance carriers manage and drive underwritingprofitability. E-mail him at [email protected].