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  • Time to Re-evaluate Downtimes for Failures of Tailings Dams

    By Gavin Rowatt | May 09, 2017 | English

    Estimating business interruption losses is never straightforward. But accurately forecasting the financial consequences of a large tailings dam failure can be a real challenge, as recent events have shown. Tailings dams store waste products of mining...

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  • 3 Ways to Change How We Talk About Disability Insurance

    By Steve Woods | May 05, 2017 | English

    May is Disability Insurance Awareness Month (DIAM) in the U.S., which means it’s a good time of year to bring consumers’ attention to an often misunderstood and overlooked product. In the spirit of this campaign, I would like to share a few thoughts on...

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  • Cyber Change Comes at You Fast - Are Insurers Ready?

    By Molly Corbett | May 02, 2017 | English

    Have you seen any exposure emerge and evolve as quickly as Cyber has? We follow many emerging issues in the marketplace, but Cyber has them beat in both speed and ferocity of change. Just take a look at the latest statistics: In 2015 Malware accounted...

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  • 预测分析全球调研结果 – 在寿险及健康险行业的应用仍有发展空间

    By Guizhou Hu | Apr 27, 2017 | Chinese

    “大数据”对寿险及健康险公司意义几何?全球的保险公司在预测分析上关注什么?他们如何采用预测分析?他们对于未来有何预期?我们通过在全球开展的预测分析调研得到了这些问题的答案,并于本月与调查参与公司分享了调研结果。 此次调研收集了23个国家/地区共136家保险公司的反馈,这些国家/地区按照地理位置被划分为八个区域:澳大利亚/新西兰、欧洲、拉丁美洲、中东/塞浦路斯、南非、台湾、英国/爱尔兰、美国。 我们在此次调研中将预测分析定义为:“超越传统精算经验分析,利用数据进行建模或预测未来结果的严谨统计学技术”。预测分析在保险业不同职能部门有着广泛的应用潜力:从市场营销和客户接触,到定价和经由核保与理赔流程实现的风险管理。在这些职能部门采用预测分析需要思考模式的转移、管理层的承诺以及资源和人才。 虽然预测分析已经在保险业以外的许多公司得到广泛应用,如谷歌的无人驾驶汽车和在线推荐引擎,但是预测分析在寿险及健康险行业的应用仍然被视为一种创新。 我们的调研结果显示: ...

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