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<\/a>Traditional operating model<\/strong><\/p>\nInsurance companies add value through their ability to quantify risk in the face of limited information, and to offer a price to eliminate policyholders\u2019 potential financial losses [2]. Leading insurance companies therefore employ large teams of skilled actuaries (forecasting professionals) who analyze imperfect, generalized data to project likely claims and therefore set premiums. The traditional model relies on a plentiful supply of individuals subject to varying degrees of risk: the premiums paid by low-risk customers (who don\u2019t later claim) cover the cost of the eventual claims of the high-risk customers and leave some profit for the insurer, once all receipts are aggregated into a \u2018risk pool\u2019.<\/p>\n
The challenge<\/strong><\/p>\n Improvements in data collection and data analysis will shrink traditional risk pools in the car insurance industry by up to $54bn, according to a recent report by Morgan Stanley and the Boston Consulting Group [3]. Devices such as smart-watches, in-home networked sensors and GPS trackers allow firms to remotely monitor people, homes and cars respectively. Applying data analytics tools, companies can draw granular insights from the data collected to better segregate according to risk, and to encourage risky customers to change their behavior [4]. In both instances claims should fall, and more detailed data allows insurers to more easily select and serve only the best low-risk customers.<\/p>\n The urgency to adapt the traditional insurance model to one using connected devices and data analytics is strong \u2013 those who do it best can offer the lowest premiums to low risk customers and make predictable profits. Those who can\u2019t are stuck with a deteriorating customer base of high-risk customers who can\u2019t get their insurance elsewhere [4].<\/p>\n Progressive<\/strong><\/p>\n Progressive, founded in 1937, has a track record of innovation, including drive-in claims and the first installment payment plans [5]. More recently, the company has sought to capitalize on connected devices and data analytics trends through Snapshot, its driver quality assessment program. Using\u00a0telematics (the long-distance communication of driving data) Progressive awards\u00a0discounts of up to 30% off the generic premium rate to Snapshot users who drive carefully. This prospect was enough to entice a large number of customers, who paid $2.6bn in premiums through Snapshot in 2014 [6], or around 15% of Progressive\u2019s total business.<\/p>\n However, more remains to be done if Progressive is to take full advantage of digital innovation in insurance. As Simon Douglas of AA Insurance observes: \u201cthe winners in the insurance market will be the ones that have got the data insights that others don\u2019t have\u201d [7]. Insurers are increasingly looking for such data insights in unconventional places. For example, a pilot scheme by Aviva, a British insurer, found that a customer\u2019s online behavior and spending habits were equally effective health risk indicators to medical examinations [1]. Progressive must be cognizant that as connected devices become cheaper and more widely available, barriers to entry fall and traditional benefits of scale are being eroded. The company must maintain an operating model that fosters the\u00a0collection and analysis of a wide range of data to gain insights beyond what smaller competitors can achieve. This could be done with a product innovation process involving a wide funnel of novel data inputs, which are then intelligently narrowed in stages to arrive at the most meaningful predictive risk indicators.<\/p>\n Privacy and trust<\/strong><\/p>\n Despite greater acceptance of personal data-sharing, especially by younger generations, privacy and trust remain an important consideration for policyholders; Allianz is spending $500m to build its own private cloud, to avoid entrusting its data to third parties [1]. Insurers like Progressive must ensure they use an operating model that has robust controls on the transfer and use of customer information, enabling differentiation on data privacy as well as price [8].<\/p>\n Driving change, for now<\/strong><\/p>\n Progressive\u2019s Snapshot program challenges the traditional insurance model of segmentation of customers into broad risk pools, instead gaining specific insights that enable lower pricing for its least risky customers. The program is revolutionary and reflective of a wider trend made possible by low cost connected devices and powerful data analytics. While taking steps to mitigate privacy concerns, Progressive must continue to creatively develop best-in-class data insights if it is to maintain its position in the market.<\/p>\n (800 words)<\/p>\n <\/p>\n Sources:<\/p>\n [1] \u201cRisk and reward\u201d Economist (March 2016), accessed 17 November 2016, available here<\/a><\/p>\n [2] \u201cInsurance\u201d The Concise Encyclopedia of Economics, accessed 16 November 2016, available here<\/a><\/p>\n [3] \u201cEvolution and revolution in a digital world\u201d Morgan Stanley, The Boston Consulting Group September 2014, accessed 16 November 2016, available here<\/a><\/p>\n [4] \u201cCar insurers find tracking devices are a tough sell\u201d Wall Street Journal, January 2016, accessed 17 November 2016, available here<\/a><\/p>\n [5] \u201cHistory\u201d Progressive homepage, accessed 17 November 2016, available here<\/a><\/p>\n [6] \u201cHow\u2019s my driving? The insurer knows\u201d The New York Times Blogs, June 2015, accessed 16 November 2016, available here<\/a><\/p>\n [7] \u201cInsurers mine customers\u2019 finance records to set premiums\u201d Financial Times, July 2014, accessed 17 November 2016, available here<\/a><\/p>\n<\/a><\/p>\n