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Trust cements the foundation of the banking industry.  Without it, we would be more apt to keep cash stuffed under our mattresses than in the impenetrable vault of a stranger. Modern digital banking wins and maintains customers' trust based on the security, transparency and accessibility of their data.  Unfortunately that trilogy is not always mutually inclusive. 

A series of publicized actions over the past 14 months have highlighted the struggle for this balance, as J.P. Morgan Chase & Co. and Wells Fargo & Co. limited direct linking between customer accounts and third party providers such as Intuit (maker of QuickBooks and owner of Mint.com) due to security concerns and, according to a 2015 WSJ article, a perception of "increasing competition." Now it appears that the business value and consumer benefit of secure data sharing has prevailed, as both J.P. Morgan Chase & Co. and Wells Fargo & Co. have signed deals with Intuit.  As stated in a Feb. 7 Business Insider report, "customers will be able to share their account data with Intuit's services through the bank's open application programming interface (API) — without entering online banking details — from the second half of 2017."  This opens greenfield opportunities for both the banks and third party providers to create new revenue streams from collective data sets while offering their customers a more integrated experience. 

The decision to make it easier for clients to access and share their data with third parties suggests that these banks are trying to rebuild trust and loyalty.
— BI Intelligence

Customers obviously want the value that such service providers and 'data aggregators' can bring, but centralizing sets of highly sensitive personal information is generally not a prudent path to minimize security risks, nor is relinquishing control or access to the data the best way for banks to maximize their value-added services.  There are cryptographic and computational methods that enable each party to keep their information private while running aggregate models and algorithms on the distributed data. This is one of the challenges that we are addressing with our next-gen platform, which we will be announcing later this year, going beyond secure data search and sharing to secure data computing.