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January 19, 2015

Big Data in Insurance: A Glimpse Into 2015

Summary:

There will be huge progress, including on machine learning and data visualization, but also new concerns on privacy and unpredictable types of losses.

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Bernard Marr is one of the big voices to pay attention to on the subject of big data. His recent piece “Big Data: The Predictions for 2015” is bold and thought-provoking. As a P&C actuary, I tend to look at everything through my insurance-colored glasses. So, of course, I immediately started thinking about the impact on insurance if Marr’s predictions come to pass this year.

As I share my thoughts below, be aware that the section headers are taken from his article; the rest of the content are my thoughts and interpretations of the impact to the insurance industry.

The value of the big data economy will reach $125 billion

That’s a really big number, Mr. Marr. I think I know how to answer my son the next time he comes to me looking for advice on a college major.

But what does this huge number mean for insurance? There’s a potential time bomb here for commercial lines because this $125 billion means we’re going to see new commerce (and new risks) that are not currently reflected in loss history – and therefore not reflected in rates.

Maybe premiums will go up as exposures increase with the new commerce – but that raises a new question: What’s the right exposure base for aggregating and analyzing big data? Is it revenue? Data observation count? Megaflops? We don’t know the answer to this yet. Unfortunately, it’s not until we start seeing losses that we’ll know for sure.

The Internet of Things will go mainstream

We already have some limited integration of “the Internet of Things” into our insurance world. Witness UBI (usage-based insurance), which can tie auto insurance premiums to not only miles driven, but also driving quality.

Google’s Nest thermostat keeps track of when you’re home and away, whether you’re heating or cooling, and communicates this information back to a data store. Could that data be used in more accurate pricing of homeowners insurance? If so, it would be like UBI for the house.

The Internet of Things can extend to healthcare and medical insurance, as well. We already have health plans offering a discount for attending the gym 12 times a month. We all have “a friend” who sometimes checks in at the gym to meet the quota and get the discount. With the proliferation of worn biometric devices (FitBit, Nike Fuel and so on), it would be trivial for the carrier to offer a UBI discount based on the quantity and quality of the workout. Of course, the insurer would need to get the policyholder’s permission to use that data, but, if the discount is big enough, we’ll buy it.

Machines will get better at making decisions

As I talk with carriers about predictive analytics, this concept is one of the most disruptive to underwriters and actuaries. There is a fundamental worry that the model is going to replace them.

Machines are getting better at making decisions, but within most of insurance, and certainly within commercial lines, the machines should be seen as an enabling technology that helps the underwriter to make better decisions, or the actuary to make more accurate rates. Expert systems can do well on risks that fit neatly into a standard underwriting box, but anything outside of that box is going to need some human intervention.

Textual analysis will become more widely used

A recurring theme I hear in talking to carriers is a desire to do claims analysis, fraud detection or claims triage using analysis of text in the claims adjusters’ files. There are early adopters in the industry doing this, and there have emerged several consultants and vendors offering bespoke solutions. I think that 2015 could be the year that we see some standardized, off-the-shelf solutions emerge that offer predictive analytics using textual analysis.

Data visualization tools will dominate the market

This is spot-on in insurance, too. Data visualization and exploration tools are emerging quickly in the insurance space. The lines between “reporting tool” and “data analysis tool” are blurring. Companies are realizing that they can combine key performance indicators (KPIs) and metrics from multiple data streams into single dashboard views. This leads to insights that were never before possible using single-dimension, standard reporting.

There is so much data present in so many dimensions that it no longer makes sense to look at a fixed set of static exhibits when managing insurance operations. Good performance metrics don’t necessarily lead to answers, but instead to better questions – and answering these new questions demands a dynamic data visualization environment.

Matt Mosher, senior vice president of rating services at A.M. Best, will be talking to this point in March at the Valen Analytics Summit and exploring how companies embracing analytics are finding ways to leverage their data-driven approach across the entire enterprise. This ultimately leads to significant benefits for these firms, both in portfolio profitability and in overall financial strength.

There will be a big scare over privacy

Here we are back in the realm of new risks again. P&C underwriters have long been aware of “cyber” risks and control these through specialized forms and policy exclusions.

With big data, however, comes new levels of risk. What happens, for example, when the insurance company knows something about the policyholder that the policyholder hasn’t revealed? (As a thought experiment, imagine what Google knows of your political affiliations or marital status, even though you’ve probably never formally given Google this information.) If the insurance company uses that information in underwriting or pricing, does this raise privacy issues?

Companies and organizations will struggle to find data talent

If this is a huge issue for big data, in general, then it’s a really, really big deal for insurance.

I can understand that college freshmen aren’t necessarily dreaming of a career as a “data analyst” when they graduate. So now put “insurance data analyst” up as a career choice, and we’re even lower on the list. If we’re going to attract the right data talent in the coming decade, the insurance industry has to do something to make this stuff look sexy, starting right now.

Big data will provide the key to the mysteries of the universe

Now, it seems, Mr. Marr has the upper hand. For the life of me, I can’t figure out how to spin prognostication about the Large Hadron Collider into an insurance angle. Well played.

Those of us in the insurance industry have long joked that this industry is one of the last to adopt new methods and technology. I feel we’ve continued the trend with big data and predictive analytics – at least, we certainly weren’t the first to the party. However, there was a tremendous amount of movement in 2013, and again in 2014. Insurance is ready for big data. And just in time, because I agree with Mr. Marr – 2015 is going to be a big year.

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About the Author

Bret Shroyer is the solutions architect at Valen Analytics, a provider of proprietary data, analytics and predictive modeling to help all insurance carriers manage and drive underwriting profitability. Bret identifies practical solutions for client success, identifying opportunities to bring tangible benefits from technical modeling.

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