Bill Skapof, chief underwriting officer and head of global corporate and commercial in North America for Generali, considers underwriting as much art as it is science.
Skapof has more than 30 years of global insurance experience developing product, distribution and sales strategies in support of global commercial market segments. He was a senior vice president at Zurich Insurance, and was with AIG before that.
He spoke with Insurance Journal about underwriting, predictive analytics, big data and more.
This has been edited for clarity and brevity.
Insurance Journal: You have stated in the past that there’s a scientific aspect to understanding risks, but there’s also an art to it. Can you tell us how that works?
Skapof: There’s a balance, and what’s important is that risk is becoming more complex, becoming more global. Programs are becoming much more involved. As insurance companies evolve, they’re becoming more scientific, more use of data analytics, more investment in predictive analytics. There’s becoming a balance.
People are trying to maintain a balance between using data, which is a tool, and balancing that with experience and the abilities of the underwriter, who have developed years of experience working with individual companies, which becomes more of the science, getting to know the color, getting to understand an individual company’s needs, and balancing that with analytics, which really is market based.
The companies that are able to find that balance and offer their solutions based on a bit of both provide the best programs.
IJ: You mentioned predictive analytics. It seems like we’re seeing a transition towards predictive analytics. How will this affect the industry going forward? How will it affect the risk managers, brokers, underwriters?
Skapof: We’re all being driven by huge investments that our companies are making in predictive analytics. It’s providing us with a lot of data and being able to manage that data effectively. What do we need to assess the exposure? What do we need to do to price the exposure?
It’s very good in certain fields, where there’s a lot of predictability, but when you’re dealing in international business with large or large middle market companies, where they may be a little bit more unique, it’s hard to have the predictive analytics, the statistical basis that you need to zero in on the exposure.
There, it’s important for us to have people who have been there, done that, who have years of experience writing international risk in various countries, understanding exposures, understanding what’s happening in the markets relative to the growing need for different types of insurance, and being there to understand when to use the tool and how to amend the tool so that they can provide a program that’s balanced for both the customer and the insurance company.
IJ: Can you talk about big data as it pertains to multinational insurance and other insurance categories?
Skapof: The whole idea of big data is we’re all about big data today. Everything is captured in a machine, and we can slice and dice that data a billion ways. Many companies have employed numbers of data scientists to manage the data, build models, and use the data to predict what the outcomes are going to be across any spectrum.
That has given us a huge amount of lift in terms of how we can predict outcomes, but there’s also a means to an end. That may work when you’re talking about personal lines insurance. If you’re talking about small businesses, where there’s frequency, where there’s a lot of homogeneity, where one risk looks like another, you can do predictive analytics.
Certainly, the bigger the database, the more accurate, the more statistically relevant the answers that come out of the models are.
When you’re dealing with huge, multinational companies, when you’re dealing with companies that are entering new markets, but they’re making big investments, you don’t always have the data to support that. That’s where just good, old fashioned underwriting capability comes in to be able to assess a risk, to understand what the exposures are, the climates are, what the color is.
Where is it located? How are they operating? Will they operate close to the way they operate in other countries? Is the facility new? What’s it made from? What are some of the exposures? How exposed are they to outside intervention, like cyber, etc.?
I’m not sure you can build all of that into a model. Certainly, over time, we’ll get there, but I’m not sure you can ever take a Fortune 1000 company and put it into a model, and every time predict exactly what’s going to happen.
It certainly gives you a good inference, but we have to use this as a tool and not base our whole business on that. We need to take that and then use it to come to a solution that is comfortable for both of us.
IJ: One of the tools we always talk about is the digital tools, digital technology. How has underwriting changed in this new digital age that we’re in?
Skapof: We certainly don’t give quotes on the back of napkins anymore. I would say that there isn’t an underwriter that’s doing insurance business today that doesn’t have three screens on his desk and using models, and data analytics, and systems, and proprietary information to come to whatever the solution is that they’re looking to provide to the client.
It’s become a very complex business, and it requires a lot of time, effort, and experience. We should value that. It’s difficult to encapsulate that all in a program. As I’ve said throughout this interview, it’s a balance between the person using the machine and the machine.
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