大数据在银行的七个应用实例

大数据文摘翻译，转载请保留

翻译：Chenlu，Lynda； 校对：闫瑾

 

Hadoop is present in nearly every vertical today that isleveraging big data in order to analyze information and gain competitiveadvantages. Many financial organizations firms are already using Hadoopsolutions successfully and the ones who are not have plans to do so. If theydon’t, they risk enormous market share loss. Followingare a few of the most intriguing and essential big data and Hadoopuse cases.

如今，Hadoop几乎存在于各个方面，其通过利用大数据来分析信息和增加竞争力。许多金融机构和公司已经开始使用Hadoop成功地解决问题，即便他们本没有计划这样做。因为如果他们不这样做，就会面临市场份额损失的巨大风险。以下是一些特别有趣和重要的大数据和Hadoop用例。

 

Fraud detection:Fraud, financial crimes and data breaches are some of the most costlychallenges in the industry. Hadoop analytics help financial organizationsdetect, prevent and eliminate internal and external fraud, as well as reducethe associated costs. Analyzing points of sale, authorizations andtransactions, and other data points help banks identify and mitigate fraud. Forexample, big data technology can alert the bank that a credit or debit card hasbeen lost or stolen by picking up on unusual behavior patterns. This then givesthe bank time to put a temporary hold on the card while contacting its accountowner.

诈骗侦测（Fraud detection）：诈骗是金融犯罪和数据泄露中成本最大的挑战之一。Hadoop分析可以帮助金融机构检测、预防和减小来自内部和外部的诈骗行为，同时降低相关成本。销售、授权、交易以及其他的数据分析点能够帮助银行识别和减少