大數(shù)據(jù)的快速增長正被尋求關(guān)鍵投資優(yōu)勢的資產(chǎn)管理者視為一項(xiàng)越來越有吸引力的信息來源,而數(shù)據(jù)提供商可以出售一切信息——從社交媒體聊天記錄、用電郵發(fā)送的收據(jù)。然而出售前,很多這樣的“另類數(shù)據(jù)”未能充分抹去個人資料。
測試中可能遇到的詞匯和知識:
adequately足夠地;適當(dāng)?shù)豙'?dikwitli]
scrub用力擦洗;使凈化[skr?b]
anonymise使匿名[?'n?n?ma?z]
consultancy咨詢公司[k?n's?lt(?)ns?]
misuse濫用;誤用[m?s'ju?z]
zealous熱情的,積極的['zel?s]
hedge fund對沖基金 對沖基金(又稱避險基金或套利基金,是指由金融期貨、金融期權(quán)等金融衍生工具與金融組織結(jié)合后,以盈利為目的的金融基金。)
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
解釋:多家對沖基金表示,一些賣家出售的信息仍包含可被用于識別個人的敏感個人信息。
(2) 答案:A.2
解釋:對沖基金Point72的首席市場情報官馬修·格拉內(nèi)德(Matthew Granade)說?!皢栴}相當(dāng)嚴(yán)重,以至于我們有兩名專職技術(shù)人員負(fù)責(zé)清洗數(shù)據(jù)?!?a couple of full-time tech people)。
(3) 答案:B.sophisticated algorithmic approaches
解釋:“機(jī)器學(xué)習(xí)”等復(fù)雜算法可以使得資金管理人可以梳理海量數(shù)據(jù)集,從中發(fā)現(xiàn)有利可圖的規(guī)律。
(4) 答案:C.hedge fund managers
解釋:一位對沖基金經(jīng)理指出,如果出現(xiàn)法律問題,訴訟的矛頭更有可能落在他們身上,而非數(shù)據(jù)提供商。