Vice President, Product Management
Forecasting shows impact of rate changes
Ohio Mutual Insurance Group explores price elasticity, broadens insurance lines with less risk via SAS®
What happens when you can forecast how a rate change will affect renewals at both the agent and policyholder level? Using SAS® Analytics, Ohio Mutual Insurance Group can explore price elasticity and broaden its insurance lines with less risk. The insurer says SAS gives it the kind of analytical firepower usually reserved for much larger companies – at a very affordable price.
Ohio Mutual writes nearly $190 million in annual premiums in homeowners, auto and farm lines through independent agents in seven states. Rate increases often trigger customers to shop around, and the company was looking for tools to better analyze how its business could be affected by proposed increases.
"We could calculate what a rate change would do to the overall book but for instance, we couldn't determine that 10 percent of the book would see at least a 6 percent rate change or 5 percent of the book would have a 10 percent rate change,'' says Dave Grove, Vice President of Product Management.
We can really do a lot with a little, which allows us to compete with companies that are significantly larger.
The company began using SAS® Business Intelligence for Midsize Business and SAS® Enterprise Guide® five years ago. With just one analyst, Ohio Mutual was quickly able to forecast rate changes all the way down to the policyholder level.
Understanding price elasticity, exploring new business lines
The insurer now has a much better sense of how premium increases will affect renewals, encouraging it to expand analytic efforts.
"We've just recently begun looking at the walkaway price for particular policies,'' Grove says, explaining that a 5 percent increase on one type of policy could trigger much more price shopping than a similar increase to another policy or individual policyholder.
With better insight into price sensitivity, executives can make better decisions on premium pricing. "SAS provides us with an additional layer of comfort knowing that the final rates we select will not be completely out of line,'' Grove says, adding that they can notify agents ahead of time on premium increases.
The company is also using SAS to help price new policies that offer customers more options. One such homeowners policy allows customers to select different deductibles depending on the type of damage (fire, weather, theft). Grove’s analyst ran its entire homeowners line using SAS to estimate the best rates to offer for the new product. The company has also explored data to look for discount options on business policies that make its commercial auto book even more competitive.
Doing a lot with a little
None of the modeling for the forecasts is time-consuming, Grove says. The monthly premium increase forecast was written over a week-long period and takes about three to four hours to run. All analysis work is done off a nightly backup of the company's data with no involvement from the IT department.
"IT loves not having to get involved,'' says Grove, adding that he is often surprised to hear conference speakers discuss the importance of doing what his company is doing, and then in the next breath talk about the four- to six-month-long effort it will take to get the information.
"I sit there thinking, 'We can do this in a week.' Having SAS gives us the capability to access the data, do this type of analysis and minimize the time it takes,'' Grove says. "We can really do a lot with a little, which allows us to compete with companies that are significantly larger."
Ohio Mutual initially did all its SAS work with one analyst, although it has since trained additional staff members. Given the minimal personnel needs, Grove says that he is surprised when other companies tell him they assume this type of work is expensive.
"There's this perception that you need a large staff of SAS experts and it costs a lot. That's not the case," Grove says. "We started with one individual, and the cost for SAS has been very affordable.''
Forecast premium increases, price new products effectively and explore price elasticity.
Tweak cost increases based on forecast, and notify agents well in advance of increases. Access to sophisticated analysis without IT support.