Tag Archives: verisk analytics

Usage-Based Pricing: Reality or Fantasy?

In the world of usage-based insurance (UBI), Progressive is an exception: Its massive amount of driving data – 110 terabytes covering some two million vehicles, 1.5 billion separate trips and more than 10 billion miles driven – allows it to quickly test new rating factors and to do so with a great degree of accuracy.

“We continue to test new ideas all the time,” says David Pratt, Progressive’s general manager of usage-based insurance. “Our research team will come up with a theory for what would predict safe driving. With our big data set, we can test those quickly.”

Few other UBI providers are as fortunate. Octo Telematics, which launched its first UBI product in 2002, also has tons of data: 194 billion kilometers of driving performance from two million drivers globally. But most other companies are making educated guesses based on more limited data combined with more traditional ratings factors.

As Nino Tarantino, CEO of Octo Telematics North America, says, “Today, there is no data standard and no clear understanding of which data and how much is required.”

For example, Octo works with seven insurers in the U.S. and Canada, and each one asks for a different data set to be collected – everything from hard braking and acceleration to how many trips a driver takes and how long the trips are, as well as when and where they occur.

Actuarial guidelines often cite 100,000 earned car years as the threshold for credibility for a model, says Dwight Hakim, vice president of telematics, Verisk Insurance Solutions, a provider of underwriting data and tools for UBI. An earned car year is equivalent to one car insured for one year.

In traditional motor vehicle insurance, the number of earned car years is used to show state regulators that an insurer’s pricing decision is based on plenty of evidence. This helps reassure regulators, and helps agents selling the insurance.

“Credibility is particularly important when insurers are constructing a rate plan that might increase premiums,” Hakim says. “Regulators need to see a model with high credibility if that model might result in rate increases. Assuming the insurer has a good financial position overall, modest rate decreases are easier to justify.”

While using earned car years – or the equivalent in telematics driving data – may be critical when an insurer asks regulators to approve a price increase, it may not be strictly necessary to see how different UBI rating characteristics perform, Hakim says.

Trial first, price later

That is what many insurers in need of beginning to test or launch UBI programs are betting on, to avoid the need for a large data set.

For starters, insurers can assume that good drivers self-select for UBI programs. “Chances are [that] the people who try it are more likely to be safe drivers,” says Thomas Hallauer, research and marketing director for telematics consultancy Ptolemus Consulting Group. “So you know you can offer some kind of discount anyway. You also know they will probably stick longer to your contract.”

Another strategy, Hallauer says, is for UBI insurers to collect an initial data set through trials, and to then revise their ratings as more data comes in. Coming up on one full year of offering UBI in the U.S., American Family Insurance used just this approach.

“We feel like we got enough to launch, but as we see the data we know we need to refine it,” says Pete Frey, personal lines UBI program and product manager, American Family Insurance.

Combining telematics data with traditional rating factors, such as age and location of residence, is yet another strategy. The Hartford is one of many U.S. insurance companies to do just that, saying it makes for finer segmentation for its consumers.

“Almost all programs in the U.S. augment telematics data with other carrier-specific rating factors,” Hakim says. “Assessing the degree of overlap among rating factors to avoid double-counting takes a significant amount of work, but carriers are implementing telematics because they know doing so will help them stay competitive and win market share.”

But the benefit of adding more data must equal the cost, Progressive’s Pratt warns. While he agrees that UBI rating will continue to evolve and become more sophisticated, “if it costs a lot to get the information, it’s maybe not worth it,” he says.

Consumer acceptance is another sticking point. “Everything we use has to be something the customer thinks is fine,” Pratt says. “We have to be able to explain to people why it makes sense, why it’s actually fair that we do it that way.”

Pooled data

Finally, insurers can get larger data sets from third-party telematics data providers, such as Verisk Insurance Solutions, Towers Watson and Octo Telematics.

Verisk offers what it calls “Driving Behavior Database for Modelers,” which makes available to statistical modeling applications: data from telematics devices; exposure, premium and loss information on insured drivers; and third-party data, including weather conditions, road type and traffic flow.

Towers Watson has a pooled data offering that collects telematics data and claims, policy, vehicle and driver information. And it uses this pooled data to score drivers and to provide those scores to insurers. Also available from Towers Watson are models that take into consideration third-party information like maps and weather, road type, population density, weather and angle of the sun.

Octo’s Insight Centre collects global, real-time data from its installed base of Clearbox telematics devices, which customers can then interrogate to inform their UBI offerings.

However, there are caveats when it comes to using pooled data.

Hakim, for example, warns that while amassing large quantities of data is critical, not all data is equally valuable. Its utility depends on its accuracy and completeness; how frequently it’s sampled; and the source – whether OBD2 outputs, GPS or accelerometers in cell phones.

“Knowing how each device works and the manner in which the different technologies interact is key,” he says. “The complexities of reading the car’s diagnostic information, appending accelerometer data and then transmitting [it] wirelessly require a deep bench of experience.”

American Family Insurance’s Frey makes a similar point. The availability of aggregated, third-party data is not the issue, he says. While there are plenty of companies offering data to insurers, “carriers are just trying to figure out how to use it,” he says. “The data is almost overwhelming.”

The profit question

One of the big, unanswered questions about usage-based insurance is whether insurance carriers will ultimately be more profitable than – or even as profitable as – providers of traditional motor vehicle insurance.

“It’s an accepted thing that putting in a UBI program for starters is a cost,” according to Frey, of American Family Insurance. “It is about a longer-term strategy. Ideally, companies hope to achieve more growth.”

Among those costs that must be taken into account are the cost of telematics hardware – if an insurer is going the route of using its own devices – and the cost of the back-end infrastructure. Adding UBI on top of an already-existing infrastructure, as major insurers must do, is extremely costly, according to Hallauer, at Ptolemus. In this respect, UBI upstarts that rely on scalable cloud solutions have an advantage, Hallauer adds.

Still, the hope is UBI will ultimately pay off.

Enabling more sophisticated pricing is one benefit. “You want to make sure you have the right rates for the right drivers,” Frey says. “One of the biggest goals is trying to create fair rates eventually.”

And insurance discounts are only part of the equation, Hallauer adds. “The pricing decision is not a discount decision; it’s how do you change the offering to make it enticing?” he says.

According to Hallauer, discount-based UBI incentives will eventually evolve into a more service-oriented approach that may range from life-saving services, such as calling an ambulance after a crash, to more prosaic ones, such as allowing drivers to get a driving score.

Ultimately, he says, UBI can make the customer feel comfortable in having a stronger link with the insurer.

Value beyond discounts

Frey says American Family Insurance is looking in this direction. While it hasn’t pinpointed what services it might offer, it’s considering safety services, making drivers aware of their driving habits and stolen vehicle recovery.

Octo’s Nino Tarantino notes that the value-added services approach is more common in Europe, where some insurance companies offer personal safety and security services, instead of discounts.

The environment is different in North America, he says, because of Progressive. The early mover’s decision to base its UBI offering on a good-driver discount established the tone for consumer expectations and shaped the market.

According to Pratt, at Progressive, the company tries to set its prices so the profit margin is the same for people who sign up for Snapshot, its UBI product, as it is for people who opt for traditional insurance.

Progressive’s theory is that UBI customers will stay with the company longer – and so far that’s been the case. Therefore, the lifetime revenue per customer should be higher, even though the margin is the same as for traditional insurance customers.

Progressive may also save some money through helping people drive better. The company noticed that the driving of UBI customers improved when, a couple of years ago, it added the option of turning on audio feedback in the device so that, for example, it beeps when someone brakes hard.

“We see this training effect within the first few weeks people have the device plugged in,” Pratt says. “They learn to avoid hard braking, and we have evidence it helps people avoid accidents. That could be a big change in the industry, trying to actually reduce your risk.”

But the big win is likely in the life of the customer relationship. Pratt adds. “We are not trying to make ourselves more profitable with this. We are trying to attract and keep good customers for a long time.”

In fact, Tarantino thinks that most usage-based insurance programs cannot succeed if they’re based only on discounts because of all the additional costs associated with them. He says Octo’s experience with 2.4 million insured drivers in Europe shows that “when the benefits of pricing and determining risk are combined with the benefits of the understanding the moment of loss for the insurance company – when there is a crash, that is – it will be successful.”

There is never enough data

So is there any such thing as enough data?

Pratt doesn’t think so. Progressive’s Snapshot considers mileage, time of day and hard braking. The company recently began a pilot using GPS-enabled devices to examine whether highway versus city street driving can contribute to predicting future losses.

Progressive has found that the measurement of how someone drives is indeed a better predictor of risk than driving record, age, gender or any of the traditional rating factors. Still, “the models can still get a lot better,” Pratt says.

Say Progressive wants to find out if people who are low-mileage drivers are safer drivers. The company can segment out those drivers from its customer base and see which ultimately did have accidents and which didn’t. It could go further and segment the low-mileage drivers by age to determine whether low mileage is a good predictor for all age groups.

Even with 10 billion miles driven, there may not always be enough drivers in the database to provide a meaningful segment to test a theory, Pratt says.

 

This article has been produced in the lead-up to the Insurance Telematics USA conference and exhibition, which will take place in Chicago on Sept. 3-4. This conference will tackle the steps needed to take UBI programs to the mass market. Find out more here.

Analytics at the Next Level: Transformation Is in Sight

Although insurance companies are embracing analytics in many forms to a much higher degree than other businesses, adoption by the insurance industry is still only in its adolescent stage. Deployment is broad but inconsistent. The use of analytics may be about to mature considerably, though, based on a recent series of mergers and acquisitions.

Currently, while a majority of large carriers use predictive modeling in one of more lines of business, and mostly in personal lines auto, a smaller percentage use it in their commercial auto and property units. Insurers recognize predictive analytics as a critical tool for improving top-line growth and profitability while managing risk and improving operational efficiency. Insurers believe predictive analytics can create competitive advantage and increase market share.

Fueling even greater excitement – and soon to be driving transformational innovation – is the recent surge of M&A activity by both new and nontraditional players, which have combined risk management and sophisticated analytics expertise with robust and diverse industry database services. The list of recent deals includes:

  • CoreLogic’s 2014 purchase of catastrophe modeling firm Eqecat, following its 2013 acquisition of property data provider Marshall & Swift/Boeckh; a significant minority interest in Symbility, provider of cloud-based and smartphone/tablet-enabled property claims technology for the property and casualty insurance industry; and the credit and flood services units of DataQuick.
  • Statutory and public data provider SNL Insurance’s 2014 purchase of business intelligence and analytics firm iPartners, which serves P&C and life companies.
  • Verisk Analytics’ 2014 acquisition of EagleView Technology, a digital aerial property imaging and measurement solution.
  • LexisNexis Risk Solutions’ 2013 acquisition of Mapflow, a geographic risk assessment technology company with solutions that complement the data, advanced analytics, supercomputing platform and linking capabilities offered by LexisNexis.

Other 2013/2014 transactions that have broad implications for the insurance analytics and information technology ecosystem include:

  • Guidewire Software, a provider of core management system software and related products for property and casualty insurers, acquired Millbrook, a provider of data management and business intelligence and analytic solutions for P&C insurers.
  • IHS, a global leader in critical information and analytics, acquired automotive information database provider R.L. Polk, which owns the vehicle history report provider Carfax. 
  • FICO, a leading provider of analytics and decision management technology, acquired Infoglide Software, a provider of entity resolution and social network analysis solutions used primarily to improve fraud detection, security and compliance.
  • CCC Information Services, a database, software, analytics and solutions provider to the auto insurance claims and collision repair markets, acquired Auto Injury Solutions, a provider of auto injury medical review solutions. This transaction follows CCC’s acquisition of Injury Sciences, which provides insurance carriers with scientifically based analytic tools to help identify fraudulent and exaggerated injury claims associated with automobile accidents.
  • Mitchell International, a provider of technology, connectivity and information solutions to the P&C claims and collision repair industries, plans to acquire Fairpay Solutions, which provides workers’ compensation, liability and auto-cost-containment and payment-integrity services. Fairpay will expand Mitchell’s solution suite of bill review and out-of-network negotiation services and complements its acquisition of National Health Quest in 2012.

Based on these acquisitions and the other trends driving the use of analytics, it will be increasingly possible to:

  • Integrate cloud services, M2M, data mining and analytics to create the ultimate insurance enterprise platform.
  • Identify profitable customers, measure satisfaction and loyalty and drive cross/up-sell programs.
  • Capitalize on emerging technologies to improve pool optimization, create dynamic pricing models and reduce loss and claims payout.
  • Encourage “management by analytics” to overcome departmental or product-specific views of customers, update legacy systems and reduce operating spending over the enterprise.
  • Explore external data sources to better understand customer risk, pricing, attrition and opportunities for exploring emerging markets.                       

As the industry is beginning to understand, the breadth of proven analytics applications and the seemingly unlimited potential to identify even more, coupled with related M&A market activity that will drive transformational innovation, indicates that the growing interest in analytics will be well-rewarded. Those that are paying the most attention will become market leaders.

Stephen will be Chairing Analytics for Insurance USA, Chicago, March 19-20, 2014.

Is M&A in Data and Analytics Setting a Path for Innovation?

The trend of acquisitions of software and data providers is continuing, but with a twist that may lay the foundation for innovation in the insurance industry. 

CoreLogic closed out 2013 with a bang by announcing its acquisition of Eqecat, a catastrophe modeling firm, on Dec. 20, adding to an already impressive list of acquisitions in the past year. CoreLogic added three real estate companies from TPG Capital Decision Insight Information Group–Marshall & Swift/Boeckh, DataQuick Information Systems and DataQuick Lender Solutions (credit and flood-services units)–further extending into the insurance data and analytics space.  

On Jan. 13, 2014, SNL Insurance, which provides a range of statutory data for insurers that links with public data, announced the acquisition of iPartners LLC, a SaaS business intelligence and analytics solution for both the property and casualty and life and annuity insurance industries. SNL says the acquisition will provide its clients a robust BI and reporting tool for operational needs.  

And Verisk Analytics, a supplier of data to insurers and banks, announced on Jan. 14 the acquisition of EagleView Technology, a provider of property images for nearly 90% of all U.S. structures. The images, based on digital aerial image capture, are analyzed to provide information to estimate property size and proximity to risks to assist in underwriting and claims assessments.

While the initial reaction might be to think of these as just another series of acquisitions, these actually point to the great possibility for change in how we access and use data in the insurance industry, a real mash-up of ideas and technology. As an industry, we are intensely dependent on data. But the data we use is fragmented across multiple organizations, accessed and paid for based on 10- to 20-year-old business/pricing models, requires significant integration and is often ineffectively used because of a lack of analytic capabilities. But these acquisitions have the potential to change this landscape.

These acquisitions and others are positioning the industry to be ready to move beyond long-held traditional offerings into “pay-by-use models” for both software (SaaS) and data (DaaS). Each offers the deepening analytics capabilities and expertise that can be used to analyze and create data from all the source data acquired, offering new data points for insurance business processes. Together, these create the opportunity to completely change the business model for data providers. This will enable the provision of new pricing, ease of access and new data based on analysis for many insurers, particularly mid-sized to small insurers, that may not have the expertise, resources or technology to do this by themselves.  

As new models emerge, the implications and the opportunities will be substantial. There could be a new wave of innovation for insurance products, business processes, markets, competition and business models. The playing field could be leveled for access to traditional and new data and information for insurers of all sizes and even for new entrants to the industry.

Who will take the first step forward in creating and offering a new model? How quickly will the innovator bring value and potential to the industry? If the traditional providers don’t, then companies outside our industry who see the strategic importance of data, cloud and new models will. Does Google come to mind?