GLBA

Introduced in 1999 while removing barriers in the financial sector, the Gramm-Leach-Bliley Act (GLBA) also established a set of rules and regulations that protect consumer privacy and secure consumer data.

 

To ensure compliance with the GLBA, it is recommended that financial institutions mask names, date of birth, social security, tax ID number, accounts, and credit card numbers. Automated data masking is the standard method of de-identification for the above-mentioned sensitive data elements that retains the referential integrity of data.

 

Data masking meets the requirements of the following provisions of the GLBA:


Section 501(b)

Requires organizations to establish financial institution standards for protecting the security and confidentiality of customers' non-public personal information. These standards relate to administrative, technical, and physical safeguards.

  • to ensure the security and confidentiality of customer records and information;

  • to protect against any anticipated threats or hazards to the security or integrity of such records;

  • to protect against unauthorized access to or use of such records or information which could result in substantial harm or inconvenience to any customer

 

Learn more about privacy laws here.

How Hush-Hush can help with GLBA compliance

For the financial and banking industry, regulatory compliance is essential. As a result, data protection tools have to meet certain criteria and guarantee consistent, accurate results every time. One of the best ways to secure financial information and restrict access of PII to internal and external parties is to use data masking to secure sensitive financial records. Data masking works by de-identifying or masking certain data elements to ensure they cannot be used to identify an individual, making it the preferred method of data protection of the financial sector. Unlike with encryption that can be undone using an encryption key, masked data cannot be re-identified, which is why it is considered one of the safest methods of data protection for sensitive financial information.

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