New Facebook Patent Lets Lenders Determine Whether to Give you a Loan based on Your Facebook Friends

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the lender examines the credit ratings of members of the individual’s social network who are connected to the individual

With a new patent issued this week, Facebook is now able to give lenders access to information about who is in your social circle, and when you apply for a loan the lender will look at your Facebook friends’ credit ratings to determine whether or not to give you a loan! That’s right, approval for your loan will be based on your Facebook friends’ credit worthiness.

Says the patent, in the relevant part, “When an individual applies for a loan, the lender examines the credit ratings of members of the individual’s social network who are connected to the individual through authorized nodes. If the average credit rating of these members is at least a minimum credit score, the lender continues to process the loan application. Otherwise, the loan application is rejected.”

loan approval based on credit scores social network

 

Let’s make sure that this is crystal clear: Facebook is going to give lenders access to information about your circle of Facebook friends, through “authorized nodes”, and then these lenders are going to determine whether to approve or deny your loan based, at least in part, on the credit scores of your Facebook friends.

What could possibly go wrong there??

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First, credit scores ‘informed’ (and we use the term loosely) by data found online are notoriously wrong. In fact, just last year the National Consumer Law Center put out a report on the use of big data in credit scoring that found, among other things, that “In general, obtaining the data was challenging and the reports our volunteers received were riddled with inaccuracies or included little or incomplete information. Errors ranged from the mundane—a wrong e-mail address or incorrect phone number—to seriously flawed.”

(You can see a PDF of the NCLC’s full report, Big Data: A Big Disappointment for Scoring Consumer Credit Risk, [destination content has been removed at other end :~( ] (PDF download).)

Second, of course, lots of people have lots of Facebook friends who they barely know – if they know them at all. Who your Facebook friends are is hardly a way to determine who you are. Unlike the good old days, pre-Internet – and unlike what your mother and father told you – it is not the case that the company you keep – especially on Facebook – can or should be used as a measure of who you are.

With those things in mind, here is how the loan application decision based on the credit-worthiness of your Facebook friends part of the patent is said to work:

Flowchart for Lender Determining Your Credit-Worthiness Based on Your Facebook Friends’ Credit Ratings:

facebook friends credit ratings loan approval system

Description of how it works, from the new Facebook patent:

FIG. 9 is a flow diagram that illustrates the steps carried out in authenticating B for access to a loan. In Step 910, the lender receives a request for a loan from B. The request includes certain identifying information of B, such as B’s e-mail address. In Step 920, in accordance with the methods described in the application, “Method of Sharing Social Network Information with Existing User Databases,” (U.S. patent application Ser. No. 10/854,610, issued as U.S. Pat. No. 8,478,078), filed Jun. 14, 2004, this lender makes a request to a social network database for a graph representation of B’s social network and receives the graph representation of B’s social network. In Step 930, a black list that is maintained for B is requested and received from the social network database in the same manner as in Step 920. In Step 940, a gray list is derived from the black list and B’s social network In Step 950, a breadth first search (or alternatively, a depth first search) is conducted on B’s social network to generate a white list. All members of B’s social network who are connected to B along a path that does not traverse through any unauthorized nodes (i.e., individuals identified in the gray list) get included on this white list. Optionally, the lender may specify a maximum degree of separation value (e.g., N.sub.max). If it is specified, the white list will include only those members of B’s social network who are within N.sub.max degrees of separation from B. In Step 960, the credit ratings of individuals in the white list are retrieved and weighting factors are applied to the credit ratings based on the degree of separation between the individual and B. As an example, a weighting factor of 1/10.sup.N may be applied to the credit ratings, where N is the degree of separation between the individual and B. If the average credit rating is above a minimum score, B is authenticated and the processing of B’s loan application is permitted to proceed (Steps 970 and 980). If not, B is not authenticated, and B’s loan application is rejected (Steps 970 and 990).

For a full explanation of what is involved with the blacklists, whitelists, and gray lists, you can read the patent, but the main point is this – and keep in mind that you are “B”: “In Step 960, the credit ratings of individuals in the white list are retrieved and weighting factors are applied to the credit ratings based on the degree of separation between the individual and B… If the average credit rating is above a minimum score, B is authenticated and the processing of B’s loan application is permitted to proceed… If not, B is not authenticated, and B’s loan application is rejected”.

Of course the other concern is exactly how, if John is your Facebook friend, is the lender and/or Facebook accessing John’s credit information?

So just how much do you need to worry about this?

Well, Greg McBride, a chief financial analyst for Bankrate.com, told CNN that he thinks “It’s nothing to lose sleep over for people with decent credit history, but it could potentially affect those who are borderline to begin with.”

Of course that completely side-steps the whole issue of privacy (yours, your Facebook friends’, and yours as a Facebook friend).

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