The insurance and reinsurance industries are in business to take bets on risks that can be identified, assessed, prioritized and planned for financially. Disasters like hurricanes, earthquakes, massive asbestos-like litigation and even terrorist attacks fit the bill. But what about so-called Black Swan events?
A Black Swan is a disaster or series of cascading disasters that no one saw coming—hence there was no way to identify, assess, prioritize and plan for the impact. The term apocryphally derives from the settlement of Australia by the British, who had seen white swans before but never a black one.
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The company is criticized for jacking up prices during periods of high demand but economists say that they are simply letting data on market conditions dictate pricing.
This past winter, Jerry Seinfeld’s wife Jessica earned her 15 minutes of fame, fuming over the $415 she reportedly paid to Uber to chauffeur her kids to a bar mitzvah, a price much higher than she had previously paid to get from here to there. Seinfeld famously posted a photograph of the receipt on Instagram, accompanied by the hashtags #neverforget and #neveragain. Leaving aside for the moment that the Seinfelds are faring fine financially, Jessica neglected to mention the upside of Uber’s surge pricing, as this practice is pejoratively called. Case in point — the $41 it cost me to ride Uber from my house to LAX last week, and the $72.16 it cost to taxi back. Uber’s prices jack up and down for basic supply-and-demand reasons. When demand for a ride is high and supply is low, as it is during a blizzard, prices rise. When the opposite holds true, they fall, although no one Instagrams their delight. Experts say this model heralds a new era made possible by access to data and more advanced analytics.
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The music industry has changed dramatically in the last couple decades, except for one domain — how television, film, video game and other producers of creative content license music tracks. Now, thanks to data analytics, APM Music believes that it has found a way to improve the system by enabling customers, who include major entertainment studios, to access musical tracks more easily from the Los Angeles-based company’s huge library.
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For any baseball team, making the World Series is a pretty dependable way to boost revenue. But when the Boston Red Sox seemed a long fly ball from this goal, the team still had something else going for it other than slugger David Ortiz: big data analytics.
The Sox have implemented several cloud-based technologies from providers such as Host Analytics, MicroStrategy and Microsoft Dynamics to slice and dice data on ticket sales, as well as revenue from merchandise, food and parking. The tools also help the company reduce expenses, by pinpointing how many ticket takers, ushers and security personnel it will need for a particular game or game series, based on past experience.The World Series champs access voluminous structured and unstructured game data on the weather, the opposing team, the day and time of the week and various pre-game promotions. Algorithms let then the team forecast how best to allocate resources based on expected fluctuations in demand.
Every company seeks the perfect measurement quantifying its performance against strategy. Historically, the corporate world has relied on an alphabet soup of acronyms—EPS, ROE, ROI, EBITDA and TSR, to cite a handful—for this guidance, employing these metrics to make key decisions on resource allocation, expense management and incentive compensation. In recent years, public companies have increasingly turned to an alternative method—Economic Value Added (EVA), prized as a more accurate measure of how companies perform for shareholders than many of its peers in the metrics game. Now private companies, as well, are finding favor with this metric.
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Property catastrophe reinsurance is causing a feeding frenzy for investors as they seem extremely willing to plunk their money into an alternative investment that does not correlate with their other portfolio bets.
The tens of billions of dollars flowing into the reinsurance industry are being funneled into securities including catastrophe bonds and other insurance-linked reinsurance investments. This bountiful capacity augments traditional sources in the venerable reinsurance industry, although even reinsurers are creating the collateralized securities and selling them to investors. For buyers—primary insurance companies the world over—the lines are blurred insofar as who is taking the reinsurance risk.
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Big data is big news these days, promising extraordinary insight into a company’s business performance against forecasted performance in as close to “real time” as possible. All that structured and unstructured data flowing in from internal and external sources can hasten decisions to quickly seize opportunities and avoid risks.
Within big data is a subset of data analytics called hot data — the vital information business leaders need before all other bits and bytes beckon. “We use the term to describe a decision that has to be made within a very tight window, such as today, tomorrow morning or at the very latest, the end of the week,” says Michael Lock, vice president and principal analyst for business analytics, at the research firm Aberdeen Group.
This window can even be smaller, such as a decision that has to be delivered within an hour or even right now. “As the speed of business becomes breakneck, the time to make decisions is moving closer and closer to ‘real time’ all the time,” Lock says. He cited the example of monitoring a new product for quality defects as it comes off the manufacturing line. “If there is a problem, you want to know it now,” he explains.
“Hot data is a hot topic,” agrees David Jonker, senior director, product marketing, big data, at technology vendor SAP. “People tend to fixate on big data and these giant data warehouses that strain from the storage overload, but from my perspective the key for a business is to be able to access the most important data as quickly as possible — the stuff so hot it will singe your fingers.”
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