{"id":5351,"date":"2017-04-05T23:28:08","date_gmt":"2017-04-06T03:28:08","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/friendly-score-using-social-data-to-build-credit-profiles\/"},"modified":"2017-04-05T23:50:45","modified_gmt":"2017-04-06T03:50:45","slug":"friendly-score-using-social-data-to-build-credit-profiles","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/friendly-score-using-social-data-to-build-credit-profiles\/","title":{"rendered":"Friendly Score: Using Social Data to Build Credit Profiles"},"content":{"rendered":"

Based in the United Kingdom and founded in 2014, Friendly Score uses social network data to build \u201csocial\u201d credit scores.\u00a0 The circumstances of the founders illustrate the institutional voids that Friendly Score is seeking to solve.\u00a0 One founder, despite being a 性视界 college grad, found it difficult to obtain credit after moving to the United Kingdom, because he lacked a credit history in that country.\u00a0 Another founder, a small business owner in Nigeria, found it difficult to obtain credit in her native country, because traditional credit bureaus had low penetration, and credit histories were thin generally.<\/p>\n

The potential market for Friendly Score\u2019s service is enormous.\u00a0 Of the 50 million unique loan applications submitted by European millennials, Friendly Score estimates that half are \u201cthin file borrowers,\u201d meaning their credit histories are too thin to lend against.\u00a0 Of the 4.5 billion underbanked people across the globe, 1.3 billion are \u201ccommercially active and online.\u201d\u00a0 (The latter figure, of course, is growing quickly thanks to the continued penetration of smartphones).<\/p>\n

\"\"<\/a><\/p>\n

The company seeks to sell its services to credit bureaus and lenders.\u00a0 Friendly Score mines publicly available social media data about potential borrowers (family status, employment information, education, travel, etc.), as well as data about their social connections, to infer the borrower\u2019s creditworthiness.\u00a0 Access to Friend Score assessments are then either combined with traditional credit metrics, or used as a substitute when traditional credit metrics are absent.\u00a0 The idea behind Friendly Score is in some ways comparable to the idea behind Sofi, a student loan provider that started off lending to people who attend prestigious universities.\u00a0 The logic for Sofi was that \u201ceven if Jane has a thin credit history, the fact that she is attending a great college likely reflects strong job prospects, and therefore strong repayment prospects.\u201d\u00a0 In the case of Friendly Score, the logic might be as follows: \u201cJane has a thin credit history, but she went to a great school, has a great job, and seems to be related or socially connected to a lot of probably-wealthy people who would be able to help<\/em> her if she fell behind on her payments; therefore, we\u2019ll lend to her.\u201d<\/p>\n

According to Crunchbase, Friendly Score has not succeeded in attracting much venture capital.\u00a0 Since launching in 2014, the company has raised 6 rounds of seed capital amounting to a little over 800K GBP, including, most recently, a 200K GBP round in February 2017.\u00a0 The primary founder appears to have left in September 2016 to start another company, ClearScore, which \u201chelps users manage their finances better\u2026 by offering them free credit reports and educational tools.\u201d\u00a0 The company also indicates that it is \u201cworking with some of the most innovative and consumer-friendly financial service companies in the UK\u2026 to bring access\u2026 to our user-base,\u201d which I suspect means that they are using inputs from Friendly Score.<\/p>\n

I su\"\"<\/a>spect that Friendly Score may encounter (or may have already encountered) two primary impediments to adoption.\u00a0 The first has to do with the nature and perceived fairness of the inputs that are used to generate credit scores.\u00a0 For example, it is conceivable<\/em> (though I have no data to suggest that Friendly Score\u2019s algorithm would actually produce this result) that the company\u2019s algorithms would implicitly discriminate against people of a particular race, gender, or demographic profile, since people tend to be socially connected to people like themselves.\u00a0 Most developed nations have laws that prohibit lending practices that discriminate on certain demographic bases (ethnicity, gender, etc.), which would significantly challenge Friendly Score\u2019s ability to participate in the institutional ecosystem of the lending industry.\u00a0 The second concern has to do with borrowers gaming the system.\u00a0 For example, if I knew that I was about to apply for a loan, and that my lender used Friendly Score to assess my creditworthiness, I might be tempted to log onto Facebook, \u201ccull\u201d my friends for perceived creditworthiness (e.g. by unfriending poor people, and sending friend requests to rich people), and change my personal data (e.g. by posting fake photos of myself travelling to exotic destinations).\u00a0 It is unclear how Friendly Score might address these concerns.<\/p>\n","protected":false},"excerpt":{"rendered":"

Friendly Score uses social media data to create its own credit scores. But can you do that without unintentionally discriminating against certain groups?<\/p>\n","protected":false},"author":1114,"featured_media":5355,"comment_status":"open","ping_status":"closed","template":"","categories":[862],"class_list":["post-5351","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-credit-score"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/data-and-analytics-as-digital-assets\/","yoast_head":"\nFriendly Score: Using Social Data to Build Credit Profiles - Digital Innovation and Transformation<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-digit\/submission\/friendly-score-using-social-data-to-build-credit-profiles\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Friendly Score: Using Social Data to Build Credit Profiles - Digital Innovation and Transformation\" \/>\n<meta property=\"og:description\" content=\"Friendly Score uses social media data to create its own credit scores. 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