1、畢業(yè)設(shè)計(jì)/論文外文文獻(xiàn)翻譯院 系 經(jīng)濟(jì)管理學(xué)院專業(yè)班級(jí) 金融1202姓 名 陳雯雯原 文出處that Social Media Can BeUsed for Credit Scoring評(píng) 分指導(dǎo)教師 劉綺濤蔡危微華中科技大學(xué)武昌分校20 16年 3月 5日將社交媒體用于個(gè)人信用評(píng)分的新穎途徑關(guān)于出借人在發(fā)展中國(guó)家面對(duì)的挑戰(zhàn)：對(duì)借貸公司而言，在將貸款發(fā)放之前，他們想弄清幾個(gè)問(wèn)題。他們想知道你認(rèn)為自 己是什么樣的人，想確證你的確是個(gè)“好人”（goodperson）。我這里所說(shuō)的“好人”， （是指）值得信任的人，可以把錢借給他的人，而且是會(huì)還錢的人。這是個(gè)很有挑戰(zhàn)性的工作。在美國(guó)和其他發(fā)達(dá)國(guó)家，做

2、到這一點(diǎn)可能要容易些。人們有 多種途徑獲取有關(guān)你的數(shù)據(jù)。（出借人）可以找到你，與你面對(duì)面交流，也可以找到你 身邊的人了解你。事實(shí)上，在這些國(guó)家，已經(jīng)有了完成這個(gè)工作的模式化途徑，比如， 查看你的信用歷史，信用歷史收集了你在一定時(shí)期內(nèi)的財(cái)務(wù)數(shù)據(jù)。另外，他們還可以查 閱你的信用評(píng)分，之后對(duì)你做出判斷。但在這個(gè)世界的其他地區(qū)一一比如發(fā)展中國(guó)家，借貸公司與人交流則是一項(xiàng)非常艱巨的 任務(wù)。在我看來(lái)，（社交媒體）已經(jīng)成了是否給要某個(gè)人發(fā)放一筆貸款的替代方法，理 由有四個(gè)。不妨看看印度、墨西哥、菲律賓和哥倫比亞的情況。我們可以看到，它們是采用這 類信用評(píng)分實(shí)踐最頻繁的國(guó)家。這些國(guó)家適合采用這類方法的理由在于

3、，首先，人們?nèi)?乏獲取資金的途徑，但已經(jīng)有數(shù)量眾多的人進(jìn)入了中產(chǎn)階級(jí)。他們出身于數(shù)十年來(lái)一直 務(wù)農(nóng)的家庭。而現(xiàn)在，這些家庭的年輕人中第一次有了大學(xué)畢業(yè)生，這些年輕人希望得 到貸款，可他們要想獲得貸款，就必須逾越銀行系統(tǒng)的諸多障礙在這些國(guó)家，大部分人面臨的一個(gè)重大問(wèn)題，同時(shí)也是這些國(guó)家偏遠(yuǎn)地區(qū)的人都要面臨 的問(wèn)題，是他們?nèi)鄙伲ǐ@得）金融服務(wù)的資源。他們沒(méi)處去找銀行的分支機(jī)構(gòu)，所以也 就無(wú)法獲得貸款。最近的銀行分支機(jī)構(gòu)離他們可能都有3小時(shí)車程。如果想一想獲得貸 款的所有可能性，或者說(shuō)，想一想交通條件的缺乏情況，那就意味著如果想獲得哪怕最 小的一筆貸款，你也必須在往返路途上花上一天的時(shí)間。所以，那些

4、地方確實(shí)缺乏獲得 金融服務(wù)的實(shí)體條件，這是我們通常都不會(huì)想到的。在沃頓的校園里，幾乎在每個(gè)角落 都有一個(gè)銀行的分支機(jī)構(gòu)，可在世界上的其他地方，這就成了一個(gè)很大、很大的問(wèn)題。 第三，當(dāng)然，在世界上的任何地方，如果你要申請(qǐng)信用貸款，就都要面臨很多的官僚主 義程序和大量的案頭工作。我曾和從事這種業(yè)務(wù)的很多公司交流過(guò)。一家從事這類工作 的機(jī)構(gòu)的技術(shù)總監(jiān)列舉了這樣的例證：如果你生活在亞洲的某個(gè)國(guó)家，現(xiàn)在需要一筆貸 款，如果你是個(gè)“好人”一一也就是說(shuō)，如果你的收入不錯(cuò)，你有一份很好的工作一一 在這種條件下去申請(qǐng)一筆貸款，他們會(huì)提出一些毫不相干的、幾乎無(wú)法接受的標(biāo)準(zhǔn)，比 如，你應(yīng)該在某家公司工作滿一年。在很

5、多發(fā)展中國(guó)家，換工作是非常常見的事情，如 果人們擅長(zhǎng)自己所做的工作，尤其是身處科技領(lǐng)域，他們往往每半年就會(huì)換一次工作， 他們總是為自己尋求下一個(gè)最好的機(jī)會(huì)。不需要看別的地方，只要看看人們?cè)谏暾?qǐng)信用卡時(shí)因?yàn)椴缓细穸痪艿那闆r即可。 除了其他條件以外，他們還有這種荒謬的規(guī)定，比如：我要給你的雇主打電話（核實(shí)）， 而且我給你雇主只會(huì)打一次電話。如果你的雇主恰好在那個(gè)時(shí)間沒(méi)在辦公桌前，你就會(huì) 再一次被拒。第四個(gè)障礙是，即便我可以給貸款申請(qǐng)人打電話，我也沒(méi)有獲取他的數(shù)據(jù)的現(xiàn)成途 徑。很多國(guó)家都沒(méi)有信用記錄，沒(méi)有任何金融支付的歷史信息。某個(gè)人可能是第一次申 請(qǐng)一筆貸款，所以，我和這個(gè)人并沒(méi)有既往關(guān)系。在這

6、樣的環(huán)境中，我就必須尋找能獲 取某人品行數(shù)據(jù)的其他途徑了。關(guān)于社交媒體在借貸行業(yè)的應(yīng)用不斷增長(zhǎng)：在這種環(huán)境中，你可以獲得有關(guān)某人手機(jī)使用情況非常詳盡的數(shù)據(jù)。因?yàn)槟懔私饬?手機(jī)的使用情況，你也就能獲得他們使用社交網(wǎng)絡(luò)的信息了。其次，因?yàn)樗麄兌加?Facebook. Twitter和其他社交網(wǎng)絡(luò)，所以，你也可以從這些資源獲取有關(guān)他們的信息。 對(duì)一家聰明的公司來(lái)說(shuō)，這種環(huán)境為他們提供了獲取他人個(gè)性信息的另一條途徑。這也 是那些打破金融服務(wù)覆蓋系統(tǒng)的公司發(fā)現(xiàn)的途徑，他們可以通過(guò)這條途徑獲取你的社交 網(wǎng)絡(luò)數(shù)據(jù)，而這些數(shù)據(jù)則能為判斷你是什么樣的人提供一些佐證一一首先，你是個(gè)真實(shí) 的人。第二，如果你是個(gè)“好

7、人”，你一定與身邊的人保持良好的關(guān)系，你一定有一定 數(shù)量的朋友，你擁有這個(gè)賬戶一定已經(jīng)有一段時(shí)間了。比起查看你的財(cái)務(wù)數(shù)據(jù)來(lái)，通過(guò) 借助社交媒體，（這些公司）收集到的有關(guān)你的信息要多得多。因此，它們轉(zhuǎn)向這個(gè)方 向就是自然而然的了。我們知道，這種實(shí)踐正在很多國(guó)家展開。Lenddo就是一個(gè)很好的例證。這家公司在 墨西哥、菲律賓和哥倫比亞等國(guó)與出借人合作開展業(yè)務(wù)，它在用戶許可的前提下收集并 提供他們的信息。公司從社交媒體收集信息后會(huì)對(duì)數(shù)據(jù)進(jìn)行處理，通過(guò)數(shù)據(jù)處理來(lái)判斷 你是否是個(gè)好人，你是否是個(gè)真人，你是否擁有獲得一筆貸款的資格，需要再次說(shuō)明的 是，我這里所說(shuō)的“好人”，是指有資格接受信用貸款的人。Le

8、nddo將這些信息提供給 出借人，出借人會(huì)最后確定你是否有資格獲得一筆貸款。關(guān)于為什么說(shuō)這是一種復(fù)古而不是個(gè)新潮流：雖然聽起來(lái)是新事物，可這種實(shí)踐可以追溯到數(shù)十年之前，事實(shí)上，我認(rèn)為，甚至 可以追溯到一個(gè)世紀(jì)或者更久遠(yuǎn)的年代。以前，當(dāng)你需要一筆貸款的時(shí)候，（銀行）會(huì) 考察你認(rèn)識(shí)什么人。他們?cè)噲D通過(guò)與你認(rèn)識(shí)的人進(jìn)行交流來(lái)確定你是否有獲得貸款的資 格。有這樣一個(gè)故事，以前，有個(gè)人向一個(gè)知名銀行家申請(qǐng)一筆貸款，那位銀行家說(shuō)：“可是，我不能給你貸款，你只需和我一起去公司停車場(chǎng)，別人就能向我證明這一點(diǎn)?！?道理是一樣的。你認(rèn)識(shí)誰(shuí)很重要，你的社交網(wǎng)絡(luò)也很重要。這些公司信賴的觀念一一你 交往的人，你的社交網(wǎng)

9、絡(luò)里的人，在品性和行為上與你非常相似一一是一種非常強(qiáng)大、 非常有效的觀念，可供他們有效利用。他們只需觀察一下你身邊的人的行為，就能（精 準(zhǔn)地）猜測(cè)到你的行為方式可能是什么樣的。關(guān)于這種方法在美國(guó)的應(yīng)用情況：很顯然，為什么我們?cè)诿绹?guó)看不到這種實(shí)踐的理由在于，（可供取用的）有關(guān)人們的數(shù) 據(jù)非常多。但是，我們依然可以通過(guò)查看他或她的社交網(wǎng)絡(luò)來(lái)改善信用評(píng)分的準(zhǔn)確性。 我們之所以看不到這種方法的應(yīng)用，無(wú)疑是因?yàn)楸O(jiān)管問(wèn)題。在美國(guó)，任何財(cái)務(wù)數(shù)據(jù)，甚 至任何與財(cái)務(wù)數(shù)據(jù)相關(guān)的信息，都會(huì)受到嚴(yán)格的保護(hù)。我們有關(guān)于歧視的法規(guī)。一家很 聰明的從事這種業(yè)務(wù)的公司，可能并不想在美國(guó)開展業(yè)務(wù)，其原因是，如果我查看了你 的社

10、交網(wǎng)絡(luò)，如果我根據(jù)你的社交網(wǎng)絡(luò)情況拒絕給你發(fā)放一筆貸款，那么，我可能最終 會(huì)攤上一場(chǎng)歧視官司。舉例來(lái)說(shuō)，如果我的朋友們是同性戀者，就可能成為拒絕為我發(fā)放貸款的一個(gè)理由。讓 人們?cè)谀硞€(gè)社交網(wǎng)絡(luò)上聚集到一起的很多特點(diǎn)，都可能成為歧視訴訟的緣由。我認(rèn)為， 大部分在這種環(huán)境中運(yùn)營(yíng)的公司都擔(dān)心出現(xiàn)這種情況，即便他們?cè)谛庞迷u(píng)分系統(tǒng)中并沒(méi) 有采用任何這類東西，他們也會(huì)覺(jué)得這會(huì)讓他們面臨嚴(yán)格監(jiān)管的風(fēng)險(xiǎn)，或者會(huì)在美國(guó)攤 上某些官司關(guān)于研究方法的確立：我們對(duì)這項(xiàng)實(shí)踐的研究，始于最初聽到的某些公司的消息，這些公司為了批準(zhǔn)你的貸款 申請(qǐng)，要求你提供自己的Twitter或Facebook賬戶密碼。當(dāng)然，這是非常不同尋常

11、的 要求，也是完全不合傳統(tǒng)的業(yè)務(wù)。隨后，我們開始更多地了解了這項(xiàng)實(shí)踐在美國(guó)和世界 其他地方的情況。我們（當(dāng)時(shí)想）：“我們可以研究這個(gè)系統(tǒng)嗎？首先，我們可以研究 一下，使用社交網(wǎng)絡(luò)數(shù)據(jù)是否能更精確地評(píng)估某個(gè)人的信用可靠性呢？其次，一旦（貸 款公司）采用社交網(wǎng)絡(luò)數(shù)據(jù)，一旦人們意識(shí)到（貸款公司）在使用這類數(shù)據(jù)，他們會(huì)在 這個(gè)系統(tǒng)中博弈嗎？在某種情況下，是不是從中得到的是更不精準(zhǔn)的信息呢？我們并沒(méi)有把信息分成A、B、C和D等類別，我們關(guān)注的是采集到的一般信息，我們想 知道的是，你的信息和我的信息之間是否有某種程度的相似性。比如說(shuō)，我們都在同一 個(gè)社交網(wǎng)絡(luò)，這就說(shuō)明我們的品性一定有某種程度的相似性，你我

12、之間可能有（非常重 要的）相似性，也可能在無(wú)關(guān)痛癢的方面有相似性。但是，我們兩人之間一定存在某些 我們都喜歡的東西，這種共同喜歡的東西就是我們相似性的基礎(chǔ)，也一定存在著我們喜 歡一起做的事情。當(dāng)我們想了解某個(gè)人時(shí)，如果我們可以采集到這個(gè)人的社交網(wǎng)絡(luò)好友 的額外信息，那么，我們就能更好地確證我們對(duì)這個(gè)人的判斷，就能對(duì)他更好地驗(yàn)證檢 查關(guān)于人們是否會(huì)在這個(gè)系統(tǒng)中博弈的問(wèn)題：你會(huì)因此而在這個(gè)系統(tǒng)中博弈嗎？我們檢視了這種可能性。我們發(fā)現(xiàn)，是的，的確 有人（會(huì)在這個(gè)系統(tǒng)中賭輸贏），如果他們意識(shí)到兩人都是在財(cái)務(wù)上負(fù)責(zé)的人，那么， 他們就會(huì)在社交媒體上向貸款公司表明兩人都是“優(yōu)質(zhì)客戶”（good types

13、），這樣可 以表明他們有資格獲得貸款。我們發(fā)現(xiàn)，人們有丟下其他好友的動(dòng)機(jī)，至少會(huì)讓自己的 信息、自己與（某些）好友之間的聯(lián)系不那么容易看到隨著時(shí)間的延續(xù)，他們這種 做法會(huì)在社交網(wǎng)絡(luò)上形成某種形式的“分裂”?！皟?yōu)質(zhì)客戶”，也就是在財(cái)務(wù)上更有責(zé) 任感的人，會(huì)遠(yuǎn)離“劣質(zhì)客戶”（bad types）。“優(yōu)質(zhì)客戶”會(huì)與更多（在財(cái)務(wù)上負(fù) 責(zé)的人）聯(lián)系?！傲淤|(zhì)客戶”也一樣。他們會(huì)與數(shù)量較少的“劣質(zhì)客戶”聯(lián)系。隨著時(shí) 間的推移，市場(chǎng)便會(huì)出現(xiàn)“細(xì)分”或者“分裂”。信用良好的人更多的會(huì)與其他信用良 好的人聯(lián)系，同時(shí)，信用不那么好的人同樣也會(huì)與其他信用較差的人聯(lián)系。這種“細(xì)分” 或“分裂”的結(jié)果是，（把社交媒體當(dāng)作

14、確定人們信用可靠性工具的）公司會(huì)面臨兩個(gè) 挑戰(zhàn)：首先，他們現(xiàn)在要從一個(gè)數(shù)量較小的群體中獲取信息了，因?yàn)槊總€(gè)人都想在自己 的社交網(wǎng)絡(luò)中擺脫“劣質(zhì)客戶”。所以，最終獲得的有關(guān)每個(gè)人的數(shù)據(jù)也較少但公司面臨的第二個(gè)效應(yīng)實(shí)際上卻 是一種正面效應(yīng)。如果他們可以獲得信息，如果他們查閱你的信息時(shí)了解到你試圖用這 個(gè)系統(tǒng)博弈，或者每個(gè)人都想用這個(gè)系統(tǒng)博弈，而你是個(gè)“優(yōu)質(zhì)客戶”，那么，你周邊 的人也很可能是優(yōu)質(zhì)客戶。當(dāng)我看到你周邊的是一群優(yōu)質(zhì)客戶時(shí)，我對(duì)你就會(huì)更有信心， 更相信你是個(gè)（在財(cái)務(wù)上負(fù)責(zé)的人）。因此，這種方式會(huì)提高判斷的精度。如果有足夠 多的人試圖在這個(gè)系統(tǒng)中博弈，那么，他們就能帶來(lái)積極變化與根據(jù)某個(gè)人

15、的歷史 數(shù)據(jù)進(jìn)行判斷相比，人們的社交網(wǎng)絡(luò)及其社交網(wǎng)絡(luò)的整體環(huán)境能提供更精確的信息. 關(guān)于這項(xiàng)實(shí)踐會(huì)傳播得多么廣泛的問(wèn)題：毫無(wú)疑問(wèn)，這樣的業(yè)務(wù)在美國(guó)以外的世界正在不斷發(fā)展。我認(rèn)為，它也有在美國(guó)增 長(zhǎng)的潛能。不過(guò)只有當(dāng)監(jiān)管機(jī)構(gòu)確信，這是減少風(fēng)險(xiǎn)的一條有效途徑時(shí)，這項(xiàng)實(shí)踐才會(huì) 在美國(guó)得到發(fā)展，而風(fēng)險(xiǎn)是客觀存在的。沒(méi)人想讓無(wú)力償付貸款的人獲得一筆貸款，因 為這些貸款是壞賬，這會(huì)導(dǎo)致金融環(huán)境的風(fēng)險(xiǎn)，會(huì)導(dǎo)致我們一直面對(duì)的各種危機(jī)。我們 必須主動(dòng)出擊，我們必須說(shuō)明，我們想讓個(gè)人得到更好的評(píng)估，我們需要比現(xiàn)在的模式 更好的模式?；蛟S，我們應(yīng)該放松這類監(jiān)管措施，或者制訂某些免責(zé)條款，找到一些個(gè) 人的社交媒體數(shù)據(jù)

16、一一尤其是當(dāng)他或她想分享這些數(shù)據(jù)時(shí)一一可以被用于評(píng)估他們是 否具有獲得貸款資格的例證。關(guān)于讓消費(fèi)者認(rèn)同的問(wèn)題：我一直在想這樣一個(gè)問(wèn)題：為什么有些人想與他人分享自己的信息呢？因?yàn)樵诿绹?guó) 的某些地方，在世界很多其他地方也一樣，（展示數(shù)據(jù)）最終可能證明你是個(gè)信用良好 的人。你是個(gè)能償還貸款的人，可你沒(méi)有把這個(gè)信息傳遞給銀行系統(tǒng)的良好途徑，就像 我在前面列舉的例子那樣。即便我是個(gè)好員工，即便我受過(guò)良好的教育，可我依然要面 對(duì)官僚程序和金融系統(tǒng)，要面對(duì)那些老規(guī)矩，它們就是不適應(yīng)全新的環(huán)境，它們還是會(huì) 拒絕我的信貸請(qǐng)求，這樣，你就關(guān)閉了讓我走向更好生活的大門。你讓我無(wú)法獲得抵押 貸款，無(wú)法獲得汽車貸款或者

17、用于繼續(xù)教育的貸款。很多道門將這些人關(guān)在了外面 關(guān)于這一實(shí)踐如何促進(jìn)經(jīng)濟(jì)增長(zhǎng)的問(wèn)題：我們經(jīng)常聽政治家、企業(yè)高管和金融界人士說(shuō)，我們必須給中產(chǎn)階級(jí)自主權(quán)，我們 一定要讓人們擺脫貧困，要給他們創(chuàng)造更好生活的機(jī)會(huì)?？扇绻藗儧](méi)有任何改善自己 生活的手段，我們?cè)趺床拍苓_(dá)致這些目標(biāo)呢？比如說(shuō)，他們要?jiǎng)?chuàng)業(yè)，可拿不到向自己農(nóng) 場(chǎng)投資的貸款，或者無(wú)法獲得教育貸款。這正是我們喜歡這一實(shí)踐的原因所在，它給人 們過(guò)上更好的生活創(chuàng)造了機(jī)會(huì)。關(guān)于重要的啟示：在這一行業(yè)運(yùn)營(yíng)的公司強(qiáng)調(diào)的一點(diǎn)是，你在現(xiàn)實(shí)生活中從沒(méi)見過(guò)的人，你可能在生 活中永遠(yuǎn)也不會(huì)遇到的人一一因?yàn)樗麄兪悄闩笥训呐笥训呐笥岩灰滑F(xiàn)在會(huì)影響到你的 信用評(píng)分。我們

18、討論的是個(gè)高度聯(lián)通的世界，一個(gè)連通性（比以往任何時(shí)候）都更高的 世界。所以，這就意味著在你的社交網(wǎng)絡(luò)中你從未見過(guò)的人會(huì)影響到你的信用評(píng)分。除 此之外，（這些公司）可以關(guān)注一切。一旦你讓他們進(jìn)入了你的社交網(wǎng)絡(luò)，他們就可以 了解任何信息以及你做的每件事情。他們會(huì)研究你有多少朋友以及你與他們的聯(lián)系頻度 如何等細(xì)節(jié)。他們不是坐下來(lái)閱讀你發(fā)布的信息，而是采用某種文本處理方式。我了解 到的是，有些公司會(huì)關(guān)注你使用“不良詞匯”（faultywords）的情況，使用某些表明 （你生活環(huán)境）的詞匯的情況。一個(gè)有趣的例子是，有一家從事這類業(yè)務(wù)的公司的一位 高管說(shuō)，他們會(huì)研究詞匯的使用情況與你的還款能力之間的相關(guān)性

19、。使用“請(qǐng)”這個(gè)詞 的人似乎是不會(huì)償付貸款的人。所以，即便是這種往往意想不到的詞匯，與（人們的信 用）也有某些相關(guān)性。原因或許與人們每天進(jìn)行的溝通有關(guān)。人們的生活方式當(dāng)然會(huì)影響到他們使用的語(yǔ) 言，會(huì)影響到他們提出某些要求時(shí)選擇使用的語(yǔ)匯。進(jìn)而，他們使用的詞匯就會(huì)與他們 償付貸款的可能性相關(guān)了。另外，這些公司還會(huì)讓你寫一個(gè)短文或者一段文字解釋你申 請(qǐng)這筆貸款的原因。你在書寫時(shí)會(huì)很注意內(nèi)容，但他們要看的并不一定是你的解釋，而 是看你犯了多少語(yǔ)法錯(cuò)誤。這些東西同樣能證明你的細(xì)心程度如何，或許也能說(shuō)明你對(duì) 細(xì)節(jié)的關(guān)注程度如何，當(dāng)然，也能反映出你的受教育水平。The Surprising Ways th

20、at Social Media Can Be Used for CreditScoringMany employers today are looking at the social media accounts of potential employees to get an idea of the type of person they might be hiring. Theyre not the only ones lending companies are also getting in on the act. And new research shows that some of

21、the more unusual things you post or the people you might be connected to could have an impact on your credit score.The paper, “Credit Scoring with Social Network Data,” was authored by Yanhao Wei, a Ph.D. student in economics at the University of Pennsylvania, Wharton marketing professors Christophe

22、 Van den Bulte and Pinar Yildirim, and Boston University professor Chrysanthos Dellarocas. Yildirim recently discussed their findings on the KnowledgeWharton show on Wharton Business Radio, which you can find on SiriusXM Channel 111.An edited transcript of the conversation appears below.On the chall

23、enges lenders face in the developing world:For the lending companies, there are a few things they would like to verify before they give their money to you. They would like to know that you are who you say you are and that you are indeed a good person. And when I say a good person, I mean someone who

24、m they can trust, whom they can lend money to and expect it to be paid back to them.It is a challenging task. In countries like the United States and other developed nations, this is perhaps slightly easier to do. There are alternate ways of getting data about you. Lenders can go find you, talk to y

25、ou or talk to the people around you. In fact, there are more institutionalized ways of doing this, such as looking at your credit history, which is a way of collecting your financial data over a period of time. They can look up your credit score, and then make a judgment about you.But this is a very

26、 challenging task when we talk about other parts of the world, the nations that are developing. There are four reasons why, in my opinion, social media became an alternate method of deciding whether to give a loan to somebody or not.Think of India, Mexico, the Philippines or Columbia. These are the

27、countries where we see some of these alternate credit-scoring practices most often. The reasons why they find these countries suitable is, first of all, there is a lack of financial access, and yet a huge number of people are moving into the middle class. They used to be in a family that had been fa

28、rming for decades. And now there is the young person who just for the first time in his family graduated from school and is looking for a loan and has to somehow go through the hurdles of the banking system to obtain credit.Third, of course, there is a high level of bureaucracy and a high level of p

29、aperwork involved in any application in any part of the world where you need credit. I have been talking to a lot of the companies that do this type of business. The chief technology officer of . one of the companies that does this type of work cites this example: If youre in one of the Asian countr

30、ies and you need a loan, if youre a decent person if youre making decent money, if you have a great job then you go and apply for a loan. And they have these somewhat irrelevant, almost unacceptable criteria for you to obtain a small loan, such as you should be employed by the same company for about

31、 a year. It just so happens that in many of these developing nations, if people are good at what they do, especially if theyre in technology environments, they keep changing jobs every six months or so. They are looking for the best next opportunity for themselves.So, without looking at anything els

32、e, you just immediately disqualified someone from obtaining access to credit. On top of that, they have these ridiculous rules, such as I need to call your employer, and Ill make only one call to your employer. And if your employer happens to be away from his desk at that point, youre again disquali

33、fied for a loan.The fourth hurdle is that, even if I can call people, I dont have well established ways of obtaining data about you. There is no credit history in many countries. There are no histories of financial payments whatsoever. This might be the first time somebodys applying for a loan anywa

34、y, so I dont have an ongoing relationship with this person. In such environments, I need to look for alternate ways of finding data about peoples character.We talk a lot about the Internet revolution that has happened in many countries, such as we talk about how, in the United States and in develope

35、d nations, the Internet has changed commerce. But the Internet revolution hasnt happened yet in many countries. In many developing countries where landlines never found access to the remote areas, the Internet didnt find access either. In fact, if you look at even the current numbers, only about 26%

36、 of the world has broadband Internet access. Ifs actually a relatively low number.On the growing use of social media in lending:In an environment of this sort, what you are going to end up with are very detailed data about peoples mobile phone use. And because you know mobile phone use, you end up h

37、aving information about social network use as well. And second, because they are also on Facebook, Twitter and other social networks, you also have access to their information from these sources.For a smart company, this creates an alternate way of getting data about peoples personalities. And thats

38、 exactly what these companies that have disrupted the financial access systems have figured out, that they can find data about your social networks, which would provide some sort of verification for who you are first of all, that you are indeed a real person. Second, if youre a good person you must

39、have some good connections with people around you, you must have a certain number of friends, and you must have had this account for a certain period of time. These companies can gather so much more information about you using social media than by looking at your financial data. So it became just na

40、tural for them to move toward this direction.We know that this is happening in many countries. Lenddo is one great example. It operates in Mexico, the Philippines and Columbia. It operates with lenders. It provides and collects information with the permission of the users. It collects information fr

41、om social media and then crunches it. It runs the numbers and figures out whether youre a good person and again, Im saying this in terms of creditworthiness whether youre a real person and whether you should be deserving a loan. And it gives this information to the lender, which then decides to esse

42、ntially qualify you for a loan.On why its more of a throwback than a trend:As new as it sounds, this type of practice goes back many decades, in fact, I think about a century or more. In the old days when you needed a loan, the bank looked at who you knew. It tried to qualify you by talking to the p

43、eople you knew. Theres a story that when someone asked for a loan from a big-named banker back in the day, he said, “Well, I cant give you a loan, but just walk with me to the park and somebody else will.”Its the same idea. Who you know matters. Your social network matters. Twitter The concept that

44、these companies are banking on 一 the idea that who you are with, the people who are in your social network, will have very similar traits and behaviors as you is a very strong, very powerful idea here that they are taking advantage of. Theyre simply looking at the behavior of people around you, and

45、by looking at that, they can guess with accuracy how you are likely to behave.On how the practice is being used in the U.S.:Of course, the reason why we dont see this in the United States is partially because there are a lot of data available about people. But we could still improve somebodys credit

46、 score by looking at his or her social network. The reason why we dont see this is, of course, regulation. Financial data, or anything that may relate to financial data, are heavily protected in the United States. And we have rules about discrimination. The reason why . a company that is smart and o

47、perating in this business may prefer not to be in the United States is because, if Im looking at your social network and if Im denying you for a loan based on your social network, that may end up as a discrimination lawsuit.For example, lefs say my friends are gay, and that might be one of the reaso

48、ns why, for example, I may then feel that Im denied. Many of the traits that bring people together in a social network could be the basis for a discrimination lawsuit. And I believe that most of the companies operating in this environment are simply afraid that, even though theyre not looking at any

49、 of these things as part of their credit-scoring system, they may feel that this puts them at risk for heavy regulation and perhaps some lawsuits in the United States.On how the research formula was created:The way that this started was first hearing about some of the companies that requested your p

50、assword for Twitter or Facebook in order to approve you for a loan. Of course, its a very unusual, very untraditional business. And then we started learning more about this practice that had been happening in the United States and in different parts of the world. We thought, “Can we study the system

51、? And can we look at, first, whether using social network data is going to result in a more accurate assessment of someones credit-worthiness? Second, once companies use this network and once people realize that companies are using these types of data, could they try to game the system, and at some

52、point would this result in less accurate information?We are not necessarily classifying info as A, B, C, D. Were looking at general information collection and if there is a level of similarity between your information and my information. Lets say we are in the same social network. That says we must

53、have similar traits to a certain degree. It could be a very significant similarity, or it could be something very small. But there has to be a certain level of mutual liking between the two of us, which is usually a function of our similarity, of the things that we enjoy doing together. And if we ca

54、n collect additional information from people who are in someones social network, then we simply get better opportunities to clarify our beliefs about the person. We are simply getting verification checks.On whether people could game the system:Could you start gaming the system? We looked at this pos

55、sibility. What we are finding is that yes, indeed, individuals could game the system, if they could know somehow that you are a financially responsible person and I am financially responsible, and we all need to show that we are good individuals to the company on social media so that we can be consi

56、dered worthy of a loan. We find that individuals will have some incentives to drop their friends or at least make the information, the connection of having a friendship with certain people less visible.What that could do over time is cause some sort of fragmentation in social networks. Good types, p

57、eople who are more financially responsible, have incentives to drop the bad types. Thafs also true for the bad types as well. They have an incentive to be connected to a higher number of financially responsible people. And they have an incentive to be connected to a smaller number of bad types. That

58、s going to result in, over time, a segmentation or fragmentation of the markets. The people who are credit-worthy will be more connected to other credit-worthy individuals, and people who are not credit-worthy being connected to, again, other non-credit-worthy individuals. As a result of this then,

59、firms that use social media as a tool for determining credit-worthiness are facing two challenges: First, now they are getting information from a smaller number of people because everyone has an incentive to get rid of the bad types in their own social networks. So Im ending up with a smaller number

60、 of data points for every single person.On how widespread the practice may become:This business is certainly growing outside of the United States. And I think that it has the potential to grow in the United States as well. It just has to happen that the regulators need to be convinced that this is a