{"id":4970,"date":"2024-03-07T13:36:33","date_gmt":"2024-03-07T13:36:33","guid":{"rendered":"https:\/\/staging.elixirrdigital.com\/us\/?post_type=case_study&p=4970"},"modified":"2026-03-16T10:47:18","modified_gmt":"2026-03-16T10:47:18","slug":"bank-of-america","status":"publish","type":"case_study","link":"https:\/\/staging.elixirrdigital.com\/us\/case-studies\/bank-of-america\/","title":{"rendered":"Improving data security and efficiency for Bank of America"},"content":{"rendered":"\n
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\n Back to Case Studies<\/a> <\/div>\n

\n Case Study<\/p>

\n Bank of America<\/h1> <\/div>\n
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Protected customer data is one of the top security challenges of modern times, especially financial data.<\/p>\n <\/div>\n <\/div>\n<\/div>\n

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About the brand<\/h2>\n

Bank of America Corporation accepts deposits and offers banking, investing, asset management, and other financial and risk-management products and services. Bank of America\u2019s operates one of the country\u2019s most extensive branch networks with some 4,600 locations and 16,000 ATMs and it\u2019s retail banking serves some 47 million customers and small businesses in the US, and is within reach of 80% of the US population.<\/p>\n

The challenge<\/h2>\n

Bank of America had a requirement to protect customer data and reduce the exposure of data as much as possible to both internal and external teams. The requirement was to build a production-sized data warehouse without exposing sensitive data to others for testing of internal and external applications. The data needed to be masked\/obfuscated and not fabricated in such a way that all names, street numbers and street names remained valid but not associated to a specific customer. Data masking is a method of processing data, sanitizing, shuffling production data and creating obfuscated data sets which is then used by other teams to test their major release.<\/p>\n

The solution<\/h2>\n

Elixirr Digital worked with IBM InfoSphere DataStage to automate the data obfuscation of Bank of America\u2019s production data into a QA EDW.<\/p>\n

The results<\/h2>\n

The process was able to run on a weekly basis to populate the test warehouse with fresh data. Prior to this solution the data was refreshed quarterly due to the complexity and length of processing time.<\/p>\n