PPP data errors show 98% of names exposed are used Bank of America – Quartz
The release of Paycheck Protection Plan (PPP) loan data aimed to bring transparency to the US $ 517 billion loan program to support small businesses during the coronavirus pandemic. But the mistakes of some banks may have caused more transparency than the Small Business Administration (SBA) expected.
Quartz analysis of the data shows that there are at least 842 occasions where a loan seeker’s name appears in a place they shouldn’t. In a few cases, this means that an organization’s loan data contains the name of a person involved in the request. In most cases, this is the result of an applicant’s name appearing in the city field of the recipient’s mailing address.
Of those 842 loans, 792 were less than $ 150,000, which should have given the recipient more confidentiality under the SBA’s release policies. The data files of these loans do not even contain a field to name the beneficiary. The data lists loans over $ 150,000 as a range rather than a specific number, and the problem affects loans between $ 36.9 million and $ 54.2 million in total that claim to keep around 6,000 jobs. .
This error appears almost exclusively on loans prepared by Bank of America. The bank declined to comment for this story.
In the fine print of the PPP loan application, applicants were warned that their name could be publicly disclosed through registration applications, so disclosure of this information should not be too much of a concern from a point of view. confidentiality. However, the fact that the errors are so heavily biased in favor of a bank should give Bank of America customers pause. These loans represent only 0.25% of bank loans, but it was making the mistake at a rate 337 times higher than JPMorgan, which had 0.0007% of its loans with the mistaken name for the city.
To find these loans, we compared the city listed with those that the US Postal Service associates with the zip code of the loan. We then narrowed the list down to those whose city fields contained both a name from a list of 98,000 American names and a name from a list of 162,000 American surnames. To eliminate common misspellings, we’ve narrowed the list further by looking only at possible names that appear less than 10 times in the data. Finally, we manually checked the resulting list to remove any misspelled or incorrectly assigned city names.