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出售用户信息的“另类交易”

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2020年06月12日

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出售用户信息的“另类交易”

大数据的快速增长正被寻求关键投资优势的资产管理者视为一项越来越有吸引力的信息来源,而数据提供商可以出售一切信息——从社交媒体聊天记录、用电邮发送的收据。然而出售前,很多这样的“另类数据”未能充分抹去个人资料。

测试中可能遇到的词汇和知识:

adequately足够地;适当地['ædikwitli]

scrub用力擦洗;使净化[skrʌb]

anonymise使匿名[ə'nɒnɪmaɪz]

consultancy咨询公司[kən'sʌlt(ə)nsɪ]

misuse滥用;误用[mɪs'juːz]

zealous热情的,积极的['zeləs]

hedge fund对冲基金 对冲基金(又称避险基金或套利基金,是指由金融期货、金融期权等金融衍生工具与金融组织结合后,以盈利为目的的金融基金。)

Big data sellers fail to hide personal information,say funds(530 words)

By Robin Wigglesworth,US markets editor

The“alternative data”industry,which sells information such as app downloads and credit card purchases to investment groups,is failing to adequately erase personal details before sharing the material,according to several hedge funds.

The rapidly growing world of big data is seen as an increasingly attractive source of information for asset managers seeking a vital investment edge,with data providers selling everything from social media chatter and emailed receipts to federal lobbying data and even satellite images from space. But several hedge funds say some vendors are selling information that still contains sensitive personal information that could be used to identify individuals.

“The vendors claim to strip out all the personal information,but we occasionally find phone numbers,zip codes and so on,”said Matthew Granade,chief market intelligence officer at Steven Cohen’s Point72.“It’s a big enough deal that we have a couple of full-time tech people wash the data ourselves.”

The head of another major hedge fund said that even when personal information had been scrubbed from a data set,it was far too easy to restore.“We were shocked at how easy it was to de-anonymise the data,”he said.“It took one of my analysts 30 minutes to discover someone who was probably having an affair.”

Sophisticated algorithmic approaches such as“machine learning”allow money managers to sift through enormous data sets for profitable patterns. Tabb Group,a consultancy,estimates that in the US alone,spending on big data will double in the next five years to $400m,while CB Insights,a data provider,has counted at least 30 start-ups in the field.

But the torrent of information being offered for sale,and the sensitivity of some of it,has raised concerns. Robert Schoshinski,assistant director in the Federal Trade Commission’s division of privacy and identity protection,said the issue was“on the FTC’s radar”.

Mr Schoshinski would not be drawn on whether there were any open investigations into misuse of personal data,citing FTC policy,but said:“It raises a number of privacy issues,given the amount of data available and how you can cross-reference it.”The Securities and Exchange Commission declined to comment.

Hedge funds stress that most vendors do a good job,and Tammer Kamel,chief executive of Quandl,a well-reputed alternative data vendor,said his company was“super zealous”about scrubbing any personal information out of its aggregated data.“No one wants to be on the wrong side of this,”he said.

Another hedge fund manager pointed out that if there were any legal issues,the litigation axe would be more likely to fall on them than the data vendors.“We are incredibly careful about licensing and privacy issues because when things go wrong legally,the plaintiffs go after the people with the money,”he said.

But there is no overarching US privacy law to protect consumers,with standards set individually by different states,industries and even companies,according to Albert Gidari,director of privacy at the Stanford Center for Internet and Society. Still,there are no signs of a backlash.

“Ultimately,history shows how willing people are to give up some privacy for some convenience,”Mr Gidari said.

1.what could sensitive personal information be used to as several hedge funds said?

A. to steal card information

B. to identify individuals

C. to send spam

D. to discover someone who was probably having an affair

答案(1)

2.How many people did Point72 hire to wash the data?

A. 2

B. 4

C. 6

D. 0

答案(2)

3.What can help money managers to sift through enormous data sets for profitable patterns?

A. full-time tech people

B. sophisticated algorithmic approaches

C. sophisticated robots

D. strict law and legislation

答案(3)

4.Who is likely to be punished if there are any legal issues?

A. data vendors

B. algorithmic approaches

C. hedge fund managers

D. users

答案(4)

(1) 答案:B.to identify individuals

解释:多家对冲基金表示,一些卖家出售的信息仍包含可被用于识别个人的敏感个人信息。

(2) 答案:A.2

解释:对冲基金Point72的首席市场情报官马修·格拉内德(Matthew Granade)说。“问题相当严重,以至于我们有两名专职技术人员负责清洗数据。”(a couple of full-time tech people)。

(3) 答案:B.sophisticated algorithmic approaches

解释:“机器学习”等复杂算法可以使得资金管理人可以梳理海量数据集,从中发现有利可图的规律。

(4) 答案:C.hedge fund managers

解释:一位对冲基金经理指出,如果出现法律问题,诉讼的矛头更有可能落在他们身上,而非数据提供商。

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