经济学人22:非常非常私人的理财问题

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　　财经；保险数据；非常非常私人的理财问题；

　　Marketing¹ information offers insurers another way to analyse risk；

　　营销信息为保险公司提供了一种分析风险的新方式；

　　A Swiss life-settlements firm called Rigi Capital Partners (RCP) recently considered buying the life-insurance policy of an elderly woman apparently² suffering from dementia. RCP would take over payment of the policy premiums³ and receive the full death benefit when she passed away. Her medical records revealed that she had forgotten even her son's birthday. But Robin⁵ Willi, RCP's owner, searched Facebook to find out more about her. Her profile suggested she had a vibrant⁶ social life, not dementia. Reckoning that she was much healthier than she wanted to appear, Mr Willi did not offer to buy her policy.

　　一家名为 Rigi Capital Partners（RCP）的瑞士寿险公司最近在讨论是否买下一位年长女性的寿险保单，其人很明显正受到痴呆的困扰。当她去世后，RCP将拿到保险条款的支付，并且将全部的死亡赔偿金收入囊中。医疗记录显示她甚至已不记得自己儿子的生日了。但是RCP的控股人Robin Willi却造访了她的Facebook以对他了解更多。从她的个人主页上看出，该女士的社交生活非常丰富多彩，完全不像痴呆症患者。Willi先生认为她的健康状况要比外界认为的更好，于是决定不去购买她的保单。

　　Medical records can be deceptive⁷, incomplete or expensive to analyse. Mr Willi thinks that publicly available data will be increasingly useful in helping⁸ insurers distinguish the aerobics⁹ enthusiasts¹⁰ from the couch potatoes. His firm is small enough to be able to search for data manually. For bigger insurers, software is now being developed by technology firms such as Allfinanz and TCP LifeSystems to sift¹¹ through all the marketing data that might help them identify tomorrow's cancer patients or accident victims.

　　对医疗记录进行分析时，不仅价格可能很高，分析结果也可能是误导性的或者不完全的。但Willi先生认为，保险公司要从沙发电视迷中选出有氧运动爱好者时，公众可接触到的信息将会发挥日益重要的作用。他的公司规模较小，完全可以手动搜索数据。对于更大型的公司来说，Allfinanz与TCP LifeSystems等科技公司正在开发全新的软件，帮助他们检索全部的营销信息从而找到明天的癌症病人或者事故受害人。

　　Such information can be bought from marketing firms that aggregate¹² data about individuals from records of things like prescription-drug and other retail¹³ sales, product warranties¹⁴, consumer surveys, magazine subscriptions¹⁵ and, in some cases, credit-card spending. At least two big American life insurers already waive¹⁶ medical exams for some prospective¹⁷ customers partly because marketing data suggest that they have healthy lifestyles, says Tim Hill of Milliman, a consultancy that advises insurers on data-mining software systems.

　　一些营销公司会收集处方类药物或其他零售信息，产品保修，消费者调查，杂志订阅，有时甚至包括信用卡支付等的个人数据。营销信息可从这些公司购得。Milliman是一家在数据发掘软件领域向保险公司提供建议的咨询公司，该公司员工Tim Hill指出，至少两家美国大型寿保公司已经放弃了对一些潜在消费者的药物测试，一部分原因是营销数据显示出他们有健康的生活方式。

　　The software picks up clues that are unavailable in medical records. Recklessness in one part of someone's life is a pretty good signal of risk appetite in others, for example. A prospective policyholder with numerous speeding tickets is more likely than a safer driver to end up with a sports injury. The software also detects obscure correlations¹⁸. People who frequent ATMs so they can make cash payments tend to live longer than those who prefer writing cheques or paying with credit cards, it turns out. People with long commutes¹⁹ tend to die younger. Why this should be is not clear: some speculate that ATM users tend to be more spontaneous types, who like to have cash in their pocket and whose lifestyle may be more active; others hypothesise that sedentary commutes mean less time to do something healthy in the evening.

　　软件会处理那些医药记录不能提供的线索。若评估个人健康问题时对某一部分粗心大意，那么在其他方面可能就要承担极大的风险。与谨慎开车的投保人相比，一位有大量超速罚单的潜在投保人很可能死于运动创伤。这款软件同样可以检测潜在的联系。人们发现经常去ATM取钱并用现金支付的人往往会比写支票或使用信用卡支付的人活的更长，事实也是如此。那些通勤时间较长的人也倾向于“英年早逝”。为什么会是这样人们还不清楚，不过一些人推测理由是因为ATM用户一般都为主动型的用户，他们口袋中有现金，他们在生活中更主动；其他人认为较频繁的往来路程意味着他能做健康活动的时间更少。

　　The technology is not perfect. For some predictions it cannot beat a blood test. But manual underwriting with medical tests can cost hundreds of dollars and, according to one estimate, drags on for an average of 42 days in America and Europe. That gives potential customers ample time to talk to a competitor or walk away. Automated²⁰ underwriting can cost a tenth as much and be done once a human reviews the software's recommendation.

　　这项技术也并不完美。有时，预测结果的准确性甚至不如血液测试。但是手工利用医学测验来核对保单可耗费数百美元，而据估计在美国和欧洲这个过程更可拖沓长达42日之久。这就给潜在的消费者足够的时间去与竞争者谈业务或者干脆不办了。自动测试较之只需十分之一的成本，并且工作人员审阅软件报告后，整个过程就完成了。

　　Insurers' interest in data mining will only grow, says Kevin Pledge, the boss of Insight Decision Solutions, an underwriting-technology consultancy based near Toronto. He has investors²¹ interested in a project to develop software to comb Facebook and Twitter for promising²² sales leads: a woman proud of her pregnancy²³ might want to buy life insurance, for example. Insurance firms will also analyse grocery purchases for clues about policyholders, he predicts. But that raises some sticky questions about privacy. Mr Pledge himself has begun to forgo⁴ his supermarket loyalty-card discount on junk food and pay for his burgers in cash. Promising as data mining is, much will depend on how regulators, and consumers, react.

　　在多伦多附近的保险科技咨询公司Insight Decision Solutions的经理 Kevin Pledge说数据挖掘技术只会导致保险公司利润的增长。他接触过有兴趣投资那些能整合Facebook与twitter信息，提高销售额的软件开发项目的投资人：比如一名对自己的怀孕非常骄傲的女性可能乐于购买寿险。他预测到将来保险公司也课从杂货购买的记录中寻求、分析潜在投保人的线索。但是一些关于隐私的棘手问题的问题也付出了水面。Pledge先生本人已经弃用了超市的垃圾食品打折忠诚卡、开始用现金购买垃圾食品了。数据挖掘的未来到底有多光明，在很大程度上取决于监管者，消费者将如何反应了。

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