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社交平台征信遇降温 何时再现转机?

使用Facebook档案来评价一个人是否信用良好,这样的主意似乎不再那么受欢迎了。

但这并不代表将社交媒体等另类数据作为信用评估方法的努力已经半途而废。

表面上看,社交网络巨头Fackbook曾在一段时间对这个想法很感兴趣,甚至申请了可以让出借人使用其社交网络人脉来评估贷款申请人的专利。不过《华尔街日报》上月的一篇报道却指出,Facebook已经与于去年5月修改了第三方开放数据政策,这意味着在线银行机构不能够再从Facebook下载账户公开资料用于其社交信用评分。

除此之外,该报道还指出,监管当局也正在要求其他在线借款人与信用数据提供商放缓其使用社交网络平台数据进行信用评分的活动。

今年1月,联邦通信委员会发布的一份报告提出,如果社交媒体平台出于征信目的使用数据,该委员会就将把这些公司视为消费者报告机构进行监管。一旦如此,那么这些公司就可能涉嫌违反《公平信用报告法案》、机会平等法律以及《联邦贸易委员会法》。

贷款出借人与金融科技创业公司一直在尝试使用社交媒体来评估信用状况,因为相比传统信用评分,这些包罗万象的数据可能更充分地反映一个人的信用背景。

传统信用评分总体上通过五种主要因素来评估一个人的偿债能力:偿债历史、债务余额、信用历史长度、信用类型、新信用需求。你可以通过访问Credit.com来免费查询自己每月的两种信用分数,看看自己在这几个方面处于什么位置。

那么其他的社交数据效果怎么样呢?

另类数据的使用可能不会彻底消失——事实上,它可以帮助那些信用数据不足的小企业打开融资大门。

Experian DataLabs正在试图控制社交媒体和其他大数据的力量,为征信所用。其数据科学家正在分析社交媒体数据和其他"另类"数据,期望借此帮助小企业更好地发展,展现自身价值,增加其获得大额商业贷款的机会。

事实证明,一些表面上看起来很简单的方法,比如在线评估,有朝一日可以帮助小型企业建立借款信誉。

Experian DataLabs执行副总裁Eric Haller表示,该集团关注旅行历史、信用卡交易数据以及社交媒体等另类数据,并将其与商业信用记录进行匹配,观察这些另类数据是否能预测小企业的信用风险。如果的确如此,那该集团使用这些数据搭建信用评分模型就是可行的。

"当你不能获取一家企业的任何信息,你预测其偿债能力的能力就会显著下降"Haller表示,"在一种无法获得信用数据的条件下,社交媒体数据、信用卡交易数据、旅行信息事实上都是很有意义的。"

那么意义有多大?这种评估并不像传统信用资料一样可靠,但迄今为止这一模型在实验室中表现良好。

"我们测试了所有主要的社交媒体站点,我们知道数据是有预测能力的,例如登陆、点赞和评分等行为的记录无疑是可以预测信用风险的"Haller说,"所以我们是在为没有信用的企业带来全新的信用"。他估计多达三分之一的小企业没有足够的传统信用记录,以供出借人来评估其偿债能力。

我们一直在广泛地寻找与小型企业相关的数据",他表示。

Lenders appear to be backing away from the idea of using individuals' Facebook profiles as part of determining whether they're creditworthy.

But that doesn't mean the effort to tap social media and other forms of alternative data as a predictor of creditworthiness have completely fallen to the wayside.

While social media giant Facebook was seemingly interested in the idea for a time - even going so far as to secure a patent on technology that would allow lenders to evaluate loan applicants based on their social network connections - the company revamped its data access policies for third parties last May, meaning online banking institutions would not be able to download data from public profiles for their scoring metrics, the Wall Street Journal reported late last month.

And regulators have caused other online lenders and credit data providers to slow efforts to use social media platforms for credit scoring purposes, the paper said.

This January, the Federal Trade Commission released a report suggesting that if social media platforms used data for loan criteria purposes, it could regulate those companies as consumer-reporting agencies. These companies could then potentially be held accountable for violations of the Fair Credit Reporting Act, equal opportunity laws and the Federal Trade Commission Act.

Lenders and fin-tech startups had been experimenting with the idea of using social media to assess creditworthiness because the wide-reaching data could potentially tell more about a person's credit background than a traditional credit score.

Traditional credit scores generally assess a person's ability to repay a loan via five major factors: payment history, amounts currently owed, length of credit history, types of credit and search for new credit (inquiries.) You can see where you currently stand in these areas by viewing your two free credit scores each month on Credit.com.

What About Other Social Data?

The use of alternative data may not be going away entirely - in fact, it could be used to open up financing for small businesses who don't have thick credit files.

Experian DataLabs currently is looking to harness the power of social media and other big data sets for this very purpose. Its data scientists are analyzing social media and other "alternative" data in hopes of helping small businesses better establish themselves, show their worth, and have a better chance of getting approved for a business loan.

It turns out something as seemingly simple as an online review could one day help a small business establish creditworthiness.

Eric Haller, executive vice president of Experian DataLabs said the group looks at these alternative data sets - like foot traffic, credit card transaction data and social media - then pairs that with commercial credit data to see if it's predictive in small business credit risk. If it is, the group could feasibly build credit scoring models based on these data sets.

"When you don't have any information on a business, your ability to predict the [creditworthiness] outcome drops dramatically," Haller said. "In an environment where there's no credit data, social media data, card transaction data, foot traffic, that actually all is meaningful."

How meaningful? It's not the same as a robust credit file, but so far the models in the lab are positive.

"We've tested all the major social media sites … we know the data's predictive - things like check-ins and likes and ratings are definitely predictive of credit risk," Haller said.

"So it's bringing new credit to businesses who don't have credit," Haller said. He estimates that as many as a third of small businesses do not have significant traditional credit profiles that lenders could use to determine their creditworthiness.

"We're always, broadly, looking for good things to do with data for small businesses," he said.


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