It's not just the technology that's changing, or even how we use it. Technology is driving societal changes, from where we live, to how we drive and beyond. Insurance Networking News asked Louie Bode, Solutions Architect for Great American Insurance Group, what changes insurers are anticipating, how they are responding and how they are coping with the acceleration of change.

INN: Your title is 'solutions architect,' not systems architect. What's the difference?

LB: My job is to help define solutions to problems, and they may not be technology related. They may be process, people or thought related. There's a lot more to finding a solution than writing a piece of code.

INN: Give me an example of the type of things you're working on or thinking about, then.

LB: We all understand the importance of data, but there's an interesting dichotomy: How do you get that data without burdening the agents or underwriters? What if you had the ability to take in other data, such as census data, weather data, maybe even data that doesn't obviously connect to what we do today, and be able to simulate patterns? Where and how we connect to all those external third-party data segments is going to be the wild west of what drives our rates and appetites.

Everyone is talking about big data, but in order to do big data, you have to have data. And I'm not sure we are there yet. The interesting thing about big data, big data's real promise, is that you can go several different directions with it. You can use it to understand what you already know, or you can go and figure out what you don't know.

At the same time we are seeing data being eroded. We are seeing insurers push out 'easy models,' so agents aren't put out by typing information into a tablet or screen. Insurers were hell-bent on making sure every bit of an application was filled out and all the underwriter's questions were answered. And now you get underwriters saying, 'why do I need those questions? I don't use them to determine a rate.'

That's where I really see systems having to get smart. They eventually will be able to find that right data for the niche, from government roles, property information, or some third-party vendor. That could really push us to get artificial intelligence in place to help us with big data, otherwise there's a gap created by a lack of key strokes.

I've been thinking about these things since 1998, and I have seen a change in the role of agents and in the philosophy of underwriting and the commoditization of insurance products, which forces us to do things just a little bit better.

INN: How is the philosophy of underwriting changing?

LB: It's really kind of ironic, but the role of underwriters is changing. They are kind of moving into a marketing/ strategy role.

Underwriters are still underwriting business, but now they are also out there trying to get premiums, and selling and trying to get the agents to write new products. Underwriters also don't have the ability to rate like they used to; they use rating algorithms. In commercial, they're filled using ISO rates, but underwriters rely on systems to come up with those rates. If you were to ask underwriters to come up with a rating algorithm for a garage or something, many underwriters would have a hard time because they are so dependent on their systems today.

INN: So technology is making risk models obsolete?

LB: You can study your data to understand the past, or to figure out where the future is going. These are commodity-type products and you've got to figure out trends before your competitors.

I sat in a meeting not long ago and it was a 25-minute love fest over telematics data. But in five or 10 years, that's going to be antiquated when the smartcars become available and liability issues turn from the driver to the automaker or the software that drove the car.

What happens if you rented a car or borrowed one that doesn't have that technology and you forgot to turn on a blinker and shifted lanes because you didn't hear a beep indicating a car was there? How is that going to change drivers and driver patterns? How is your data today going to help you understand how drivers drive five years from now?

Say you're studying how 19-year-old drivers have behaved over the past 10 years. Well, it used to be a cool thing for a 19-year old to cruise around with the radio on. That was what they did, and there was exposure to that.

Now a 19-year old gets their kicks from social media and online gaming. It's not cool to cruise in a Prius. Is that the same risk today?

The good news is that things are changing. The bad news is that things are changing. So how do we know what horse to bet on? The only solution is to keep your options open and study as much data as you can.

INN: What should insurers be doing to better manage change?

LB: Technology is going to be playing a bigger role, and our technology people need to be more aware and have more substantive insurance knowledge in order to help make these changes. It's not just a Ouija board and an underwriter.

We can use statistics to break risks down into buckets and rethink how we assimilate what's a good risk and what's a bad risk, and then throw a map over it. That's just an example, but there have got to be ways to make these things simpler and easier and have the systems think more.

Timing is everything. How long are those data points you're considering, or array of words that you are searching for, going to be meaningful for what you are trying to do?

Whoever figures out the right data at the right moment, even though it could be short lived, because they are going to have to come up with another process and different data two years from now, are the people who become the winners.

INN: We've got just another minute. What else is on your mind?

LB: Don't lose focus on why we are here. As insurers, we have the greatest jobs in the world: picking people up when they are down and indemnifying them back after horrific losses, and being able to put people and companies back on their feet. And we have to drive the technology that enables us to do more of that. That's why this is exciting.

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