Milliman has announced a new innovation in the InsurTech space – a driving “risk score” created with tech start-up Zendrive that is up to six times more powerful than the leading predictive models.
Milliman teamed up with Zendrive, a smartphone-powered driving analytics company, to study how distracted driving and other driving behaviors can lead to auto collisions. Using Zendrive data, Milliman verified the behaviors that were strong indicators of collision frequency and created a risk score to compare the “worst” drivers relative to the “best.” Their findings revealed that the worst 10% of drivers were over 13 times more likely to be involved in a crash than the best 10% of drivers. The results were based on one of – if not the – largest telematics data set in the U.S. As of today, Zendrive has captured over 40 billion miles of driving behavior via smartphone sensors.
Smartphones can measure driving behaviors that traditional, first-generation telematics can’t, such as who is driving the vehicle and phone usage contributing to distracted driving. These new-age predictors contributed to a risk score that is over six times more accurate than the current industry leader models, which use traditional hardware-based telematics devices. There’s an opportunity here for auto insurers, especially commercial auto fleet insurers, to be early-adopters of this technology, and improve their ability to measure and rate risk.
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Applying for a mortgage loan is a process that requires a lot of information to make an informed decision. Even in this digital age the process of obtaining a mortgage remains complex. Can artificial intelligence (AI) technology that makes recommendations based on research from consumer organizations and federal agencies help? Milliman consultant Madeline Johnson looks at the question in her article “Couch surfing for mortgage loans.”
Today actuaries and insurers are able to apply predictive analytics in novel ways because of advanced technologies, larger data sets, and increased computing power. A recent Risk & Insurance article featuring Milliman’s Peggy Brinkman and Phil Borba explores four key areas where advances in predictive analytics are changing the way insurers conduct business: claims, driving safety, property risk, and competitive rating.
Technology is changing the way businesses evaluate risks, transforming customer interactions, and overhauling the purchase process. As traditional insurers strive to overcome legacy systems and practices, how are they successfully keeping pace with new InsurTech entrants? In the Milliman Impact article “Setting the pace: InsurTech transformation,” Neil Cantle, Russell Osman, and Pat Renzi offer their perspectives on the challenges that traditional insurers must navigate.
Milliman has announced the launch of its latest InsurTech offering, an innovative casualty benchmarking tool that provides a new industry standard and a better, more efficient way of assessing variability in unpaid claim estimates. Milliman’s Claim Variability Guidelines™, debuting at the Casualty Loss Reserve Seminar in Philadelphia, are new industry benchmarks to help evaluate the quality of stochastic unpaid claim distributions used for enterprise risk management (ERM) and dynamic financial analysis (DFA), including correlations for aggregate distributions. The Guidelines also stochastically support deterministic ranges used for reserving.
Milliman’s Claim Variability Guidelines are like version 2.0 of the standard benchmarks that are currently used industry-wide—they’re a modernized, robust, and efficient set of tools that can help insurers better understand their unpaid claim reserves. Being able to gauge the quality of unpaid claim variability estimates is a key metric in any risk management strategy, and allows insurers to more accurately price their products.
Key features of the tool include automatically adapting results based on company size, as well as the flexibility to adjust for different development patterns, currencies, and variance assumptions. For more information, Mark will be presenting on benchmarking unpaid claim estimates, as well as integrating reserve variability into ERM, at the Casualty Loss Reserve Seminar this week in Philadelphia; or click here.
InsurTech seeks to improve upon traditional insurance processes by making use of technology like artificial intelligence (AI), mobile applications, and cloud computing. In this article, Milliman’s Tom Ryan takes a look at the InsurTech environment within the property and casualty (P&C) industry. The following excerpt highlights the dynamics stirring up interest in the industry.
The current interest in InsurTech is driven by a perfect alignment of four key elements, the “big Ts”—technology, talent, treasure, and a tempting target.
• Technology: Many of the ideas behind InsurTech startups are not new. It’s just that they were not feasible previously because of shortcomings in technology—even for the technology available as recently as four to five years ago. The improvements in faster, cheaper, smarter computing power, greater storage capability, and large blocks of external but “usable” big data have allowed many seasoned ideas to come to fruition.
• Talent: Many of the entrepreneurs behind today’s InsurTech initiatives migrated to insurance from other industries where they successfully implemented technological innovation. As these other industries get more crowded and mature, innovators are bringing their playbooks to more wide open spaces—the insurance industry. Visit the websites or read the backstories of many InsurTech startups and you will likely find references to prior successes in FinTech or at least a Stanford or MIT pedigree.
• Treasure: At the end of 2016, policyholder surplus in the U.S. property and casualty (P&C) industry stood near record highs of $700 billion. According to the Insurance Information Institute, the industry now has $1 of surplus for every 77 cents of net written premium, close to the strongest claim-paying status in its history. While this is good news from an insurer solvency perspective, the abundance of surplus relative to premium is driving a sustained soft market with low return on equity. Many insurers are responding to these conditions by merging with or acquiring competitors, buying stock back, or raising distributed dividends. It has proved difficult to put any excess capital to work directly in company operations. This had led several insurers to invest in internal technology and digital innovation initiatives as well as starting their own corporate venture capital funds to invest in InsurTech startups. More and more of the investors in InsurTech ventures are the investment arms of legacy insurers and reinsurers. Because of the lack of attractive standard alternatives, these investments may be the best options.
• Tempting target: The insurance industry is huge, with over a trillion dollars of net premiums written annually—over $500 billion in the P&C industry alone. Couple the size of the industry with a reputation for risk aversion and conservatism, and you have a tempting target for innovators, disruptors, and entrepreneurs.