Telematics: How Big Data Is Transforming the Auto Insurance Industry WHITE PAPER
SAS White Paper Table of Contents Introduction.... 1 Self-Reporting Policies: Precursors to Telematics... 1 Pay-As-You-Drive: A Telematics Solution... 2 Pay-How-You-Drive: Another Telematics Solution.... 2 Challenge Data, Data Everywhere... 3 SAS Recommends... 4 Challenge Finding a Needle in a Haystack.... 4 SAS Recommends.... 5 Challenge from Data to KPIs and Real-Time Pricing Models... 6 SAS Recommends... 7 How SAS Can Help.... 8 SAS Data Management.... 8 SAS Visual Analytics.... 8 SAS High-Performance Analytics Server... 8 Conclusion.... 9 For More Information... 9 Content for this white paper was provided by Stuart Rose. Rose is the Global Insurance Marketing Director at SAS. He is responsible for thought leadership and marketing content for applying analytics within the insurance industry. Rose began his career as an actuary, and now has more than 25 years of experience in the insurance industry. He has been responsible for the successful development and implementation of enterprise systems, working with insurance companies in the US, UK, Europe and South Africa. Rose is a regular contributor to insurance publications and to the Analytic Insurer blog (blogs.sas.com/content/insurance). He frequently speaks at insurance conferences and is co-author of the book Executive s Guide to Solvency II. He graduated from Sheffield University with a bachelor s degree in mathematical studies.
Telematics: How Big Data Is Transforming the Auto Insurance Industry Introduction True innovation is a rare thing, particularly in the insurance sector. But telematics could turn out to be a technology that will revolutionize the entire automobile insurance industry. Telematics refers to the use of wireless devices to transmit data in real time back to an organization. The data recorded in telematics devices can be used to develop more accurate pricing, improve the granularity of risk management techniques and reduce losses by enabling better claims assessments. In the auto insurance industry, the terms telematics and usage-based insurance (UBI) are often used interchangeably but they are actually two different concepts. Usagebased insurance is a broader concept that can be broken down into two categories: self-reporting policies and telematics-based policies. Adopting usage-based insurance sooner rather than later will not only attract better drivers, but will also allow carriers to build and maintain a database on numerous variables that influence loss costs. Moody s Investor Service Much has been written about the pros and cons of using telematics and many have made a business case for implementing usage-based insurance in the auto industry. This white paper will focus on the challenges insurers will face due to the explosion of data. It will also explain how analytics can help carriers analyze all of the information that will soon be available to them. Self-Reporting Policies: Precursors to Telematics Self-reporting policies calculate an auto insurance premium based on the total distance driven as reported by the insured. While these products are easy to implement, they suffer from many drawbacks. For example, these types of policies rely on the insured person being honest enough to report accurate odometer readings. Self-reporting policies don t require any major paradigm shift for auto insurance companies. The real evolution in the auto insurance industry is associated with telematics-based insurance. There are two main types of telematics-based insurance products: Pay-as-you-drive (PAYD). Pay-how-you-drive (PHYD). 1
SAS White Paper Pay-As-You-Drive: A Telematics Solution The simpler of the two telematics-based insurance products is the pay-as-you-drive (PAYD) plan. For this type of plan, a GPS device is installed in the car, which tracks the distance driven and automatically transmits the information to the insurer. One of the earliest PAYD products was launched by South African insurer Hollard Insurance. The product was targeted at low-mileage drivers, particular young drivers. It was designed to be similar to mobile phone plans that charge monthly fees. It charged the insured based on the number of kilometers driven, and included plans such as: Drive500, Drive1000, Drive1500 and an unlimited version, DriveMax. The disadvantage with PAYD plans is that they do not consider the driving habits of the insured, such as heavy braking. Pay-How-You-Drive: Another Telematics Solution Pay-how-you-drive (PHYD) plans are the most sophisticated of the usage-based insurance products that use GPS devices with integrated accelerometers to track a multitude of factors. In addition to mileage, these devices also capture date, time, location, speed, cornering, harsh braking and even frequent lane changing. Tracking all this information often provides a strong incentive for drivers to improve their driving styles. For example, State Farm s telematics product includes a driver feedback application that helps customers monitor their driving behavior by scoring the driver on three parameters acceleration, braking and cornering. US insurer Progressive Insurance launched the first telematics product in 1998. Since then, almost everything has changed with telematics technology. By 2012, Progressive reported that it wrote over $1 billion in premium revenue for UBI policies. By 2020, it is forecast that over 25 percent of the entire US auto insurance premium revenue will be generated via telematics, representing more than $30 billion. In Europe, the largest auto insurance market, there were more than a million telematics-based insurance customers by the end of 2011. The majority were concentrated in Italy, Spain, France and the UK. Indeed, Europe has become the most important market for telematics and is predicted to generate more than 50 billion euros (US$66.7 billion) in premiums by the end of the decade. Europe has become the most important market for telematics and is predicted to generate more than 50 billion euros (US$66.7 billion) in premiums by the end of the decade. As telematics becomes more and more prevalent in developed markets, its expansion into other insurance markets in Canada, Asia Pacific, South Africa and Latin America is inevitable. And as the cost of telematics devices continues to decrease, the greatest expansion of usage-based insurance is expected to be with PHYD products. 2
Telematics: How Big Data Is Transforming the Auto Insurance Industry Figure 1: Market size share of the telematics-enabled policies in Europe and the US. (Source: PTOLEMUS. Global Insurance Telematics Study, 2012.) Another factor influencing the growth of usage-based insurance, especially in Europe, is that gender is being eliminated as a rating factor. On March 1, 2011, the European Court of Justice 1 ruled that Taking the gender of the insured individual into account as a risk factor in insurance contracts constitutes discrimination. The gender directive could cause a general rise in insurance premiums, so the directive could result in more insured policyholders taking out telematics policies. Challenge Data, Data Everywhere From its earliest days, the insurance industry has been data-centric. In the past, insurance companies relied on historical data from policy administration solutions, claims management applications and billing systems. Today, the explosion of new data is turning the insurance business model on its head. The growth in telematics has had an especially large influence. Insurance is now a big data industry. Consider the amount of data automotive telematics devices are expected to generate. Every second, a telematics device will produce a data record. This data record will include information such as date, time, speed, longitude, latitude, acceleration or deceleration (G-force), cumulative mileage and fuel consumption. Depending on the frequency and length of the trips, these data records or data sets can represent approximately 5MB to 15MB of data annually, per customer. With a customer base of 100,000 vehicles, this represents more than 1 terabyte of data per year! Insurers are struggling to cope with the many different types of telematics devices and subsequently different data formats. Besides the explosion of data that telematics produces, insurers are struggling to cope with the many different types of telematics devices and subsequently different data formats. When Liberty Mutual launched its telematics program in 2009 for commercial fleets, it used data from at least five different telematics services providers. 1 European Court of Justice Press Release: http://curia.europa.eu/jcms/upload/docs/application/pdf/2011-03/cp110012en.pdf 3
SAS White Paper The types of devices insurers are using include: embedded navigation systems, such as General Motors OnStar; on-board diagnostics (OBD) devices like Progressive Snapshot; standard black boxes attached to commercial vehicles; and smartphones, like the iphone. There are advantages to using each of these devices, but there are also many challenges, such as cost and data quality issues arising from missing data. The complexity of who owns the data is another issue. Can the insured person transfer telematics data (i.e., a driving record) from one insurance company to another? If so, will the insurance industry consider an industrywide standard for telematics data? SAS Recommends To help insurance companies address the challenges posed by the large data volumes generated by telematics programs, it is essential for auto insurers to implement an enterprise data management strategy. This data management strategy should provide a unified environment of solutions, tools, methodologies and workflows for managing telematics data as a core asset. It should also be flexible and scalable to reduce the time and effort required to filter, aggregate and structure the exponential growth in telematics data. The data management strategy should consist of four key components: Data integration. Improve the flow of accurate telematics information across the organization. Data quality. Ensure information integrity and excellence by managing the data quality life cycle. Enterprise data access. Manage the access and use of data across the enterprise. Master data management. Create a single, accurate and unified view of all the telematics data. Challenge Finding a Needle in a Haystack What is riskier? An urban customer who drives only 5,000 miles per year, or a regional sales manager who travels over 20,000 miles per year, but mostly on interstate highways? Studies have shown that the number of crash-related claims increases based on mileage driven. Consequently, research by the UK Government Road Casualties in 2008 2 proved that accident risk per mile on a motorway is 80 percent less than on other roads. Without telematics, it would be nearly impossible to answer these questions. With all this new data that s available through telematics, how do insurers determine which variables are predictive or can forecast driving behavior, loss experience, etc.? 2 http://www.junction17.co.uk/information_links/documents/reported%20road%20casualties-2008.pdf 4
Telematics: How Big Data Is Transforming the Auto Insurance Industry There s also a question about how much data is required to have a statistically meaningful data set to analyze. Experts forecast that insurers will need to collect at least 10,000 customer-years of data to be able to correlate driving behavior with claims data so they can compare this information with data from standard drivers. SAS Recommends Telematics on its own will not revolutionize the auto insurance industry. Insurance companies will need to use analytics to mine the vast amount of data that the wireless devices will produce. By using data exploration and analytics, insurers will be able to rank and weigh hundreds of new variables generated by telematics to develop highly accurate telematics pricing models based on a driver s past and forecast driving behavior. For example, insurers could use a correlation matrix to quickly identify which variables are related and to determine the strength of the relationship. Correlation of Selected Measures By using data exploration and analytics, insurers will be able to rank and weigh hundreds of new variables generated by telematics to develop highly accurate telematics pricing models based on a driver s past and forecast driving behavior. Unit Capacity Unit Downtime Unit ID Unit Lifespan Unit Lifespan Limit Unit Reliability Unit Yield (actual) Unit Yield (rate) Unit Yield (target) Unit Age Unit Downtime Unit Lifespan Unit Reliability Unit Yield (rate) Unit Capacity Unit ID Unit Lifespan Limit Unit Yield (actual) Figure 2: Correlation matrix darker boxes indicate a stronger correlation; lighter boxes indicate a weaker correlation. Insurance companies cannot rely on traditional data mining technology to analyze all of this new data. Due to the sheer size of telematics data, insurers must consider a distributed, in-memory environment to display the results of data exploration and analysis in a way that is meaningful but not overwhelming. 5
SAS White Paper Challenge from Data to KPIs and Real-Time Pricing Models Auto insurance is mandatory in most developed countries. As a result, auto insurance is a very competitive market, and in many cases, a loss-making line of business. One reason for this unprofitability is that the pricing for auto insurance is often not aligned with individual risk. For example: An insured person who drives 20,000 miles will often pay the same premium as someone who drives less than 5,000 miles. A cautious young driver will pay the same high premium as a dangerous young driver. In Europe, a male driver will pay the same premium as a female driver, despite the fact that he is three times more likely to die in an auto accident. Many opponents to the introduction of telematics products have expressed concern regarding privacy and the ability of insurance companies to track their insured customers. By contrast, one could argue that telematics increases transparency. Through telematics, insured customers are more aware of how their premiums are calculated, and they ll know that their good driving skills and attitudes are recognized. Telematics equips insurers to present information on individual customers driving behavior, which gives customers incentive to drive more safely. This information can be presented through a driving performance dashboard and key performance indicators (KPIs). For example, UK insurer Young Marmalade sends email alerts to the driver when a risk indicator changes colors from amber to red. Even though usage-based insurance has been largely driven by personal lines markets to date, the companies that have implemented telematics in their commercial fleets have seen immediate decreases in claims volumes and fuel consumption. Through telematics, insured customers are more aware of how their premiums are calculated, and they ll know that their good driving skills and attitudes are recognized. Telematics equips insurers to present information on individual customers driving behavior, which gives customers incentive to drive more safely. 6
Telematics: How Big Data Is Transforming the Auto Insurance Industry Figure 3: A driving behavior dashboard. Telematics offers a multitude of possibilities in the way auto insurance could be priced. Telematics enables insurers to use real-time data for real-time pricing. The vision is that insurance could be paid on a monthly usage basis rather than a six-month or annual basis, similar to other utilities like electricity, gas or water. However, it would be a big risk to exploit too many variables in the pricing model. For example, when Norwich Union launched its initial PAYD product in 2006, its pricing structure was too complex and created financial uncertainty for customers. Its variable rate, ranging from one penny to 12 pence, depended not just on mileage but also on time of day and type of road driven. Another issue that affects many auto insurers is rate evasion, or premium leakage. Misrepresentation of information, whether deliberate or not, amounts to an estimated 10 percent on premium revenue. Telematics can help reduce this loss significantly because it allows information to be updated in real time. SAS Recommends The idea of using telematics data to generate personalized pricing and provide meaningful risk information appears simple. In reality, it is very complex to achieve this goal and it requires the use of high-performance analytics. The velocity of big data coming into an organization, especially that arising from telematics, can be very difficult to manage. The ability to quickly access and process varying velocities of data is critical. Insurance companies should consider a stream it, score it, store it approach. This approach enables analytics to be applied on the front end to filter out unimportant data, or noise. 7
SAS White Paper How SAS Can Help Telematics is still in its infancy, but its adoption rate is dramatically increasing. The winners, which may include new players like vehicle manufacturers, will be early adopters who capture the safest drivers and take advantage of competitive pricing while reducing claim losses. Fundamental to any telematics initiative is data collecting, storing and analyzing massive amounts of information. To help insurers with these projects, SAS recommends several solutions. SAS Data Management SAS Data Management provides the flexibility to meet your complete data management needs. It fulfills a wide range of data integration requirements for insurers telematics initiatives. With SAS, you can: Access all telematics data sources. Extract, cleanse, transform, conform, aggregate, load and manage data. Support batch-oriented and real-time master data management solutions. Create real-time, reusable data integration services that support collecting the data from telematics devices. SAS Visual Analytics The ability to explore huge volumes of data simultaneously by many users, combined with SAS software s very powerful high-performance analytics, gives insurance companies an unprecedented way to tap into telematics data. Through SAS Visual Analytics, insurers can surface unexpected insights, find answers to complex problems, and quickly identify new and better courses of action. The data is compelling. This capability has really redefined the way we think about pricing auto insurance. Carriers that don t use telematics to price auto coverage will eventually attract poor drivers who were turned down for coverage by the insurers that do. Andy Napoli President of the Consumer Markets Division at The Hartford The software combines an easy-to-use, dynamic interface with powerful in-memory technology to enable all types of users to visually explore telematics data. As a result, users can execute analytic correlations on billions of rows of data in just minutes or seconds to gain insights into what the data means. SAS High-Performance Analytics Server SAS High-Performance Analytics Server solves business problems that require sophisticated, high-end analytics and the ability to integrate telematics data sources. It removes the limitations of trying to analyze large volumes of data with traditional modeling tools, and eliminates restrictions imposed by existing computing infrastructures. By allowing complex analytical computations to run in a distributed, in-memory environment, SAS High-Performance Analytics Server enables you to prepare, explore and model multiple scenarios using data volumes never before possible to generate rapid, accurate insights. 8
Telematics: How Big Data Is Transforming the Auto Insurance Industry If you can reduce analytic processing from days or hours to minutes or seconds, you can ask more what-if questions. Telematics pricing models can quickly be adjusted and run again. The ability to combine unstructured and structured data, apply automated optimization techniques and run frequent model iterations faster than ever before provides incredibly increased predictive power. Conclusion The auto insurance industry is facing an unprecedented number of challenges brought on by heavy price competition and increased claims costs. Since the first pay-as-youdrive experiment by Progressive Insurance in 1998, almost everything has changed with telematics technology. Telematics has transformed into a fast-growing model that insurers across the globe are implementing. It has the potential to revolutionize the industry and give insurers a way to gain a competitive edge. Information technology and analytics are essential tools to helping insurers succeed with these efforts. For More Information To learn more about SAS solutions for the insurance industry, visit: sas.com/insurance 9
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