Data-driven personnel assessments have become a key part of how many banks and financial institutions enhance their human resources strategies and mitigate employment-related risks and liability. Although personnel data analyses offer many benefits, they can also generate risks if implemented or used without due care.
Two of the primary goals of gathering and analyzing workplace data are to enhance organizational efficiency and ensure compliance with employment laws. Tools like pay equity analyses, compensation assessments, and adverse impact analyses help ensure legal compliance and fairness. These tools can highlight areas for improvement, such as attracting talent and addressing promotion disparities.
The benefits of data collection are significant. By analyzing data, banks and financial institutions can help protect themselves from potential lawsuits and regulatory penalties, ensure compliance, and identify potential problems in HR processes. This proactive approach not only reduces the risk of legal challenges but also promotes a positive work environment by enhancing employee morale and reducing turnover.
Collecting and analyzing workplace data is not without its challenges. There is a risk the data collected could inadvertently create evidence that might be used against the bank or financial institution. Additionally, if the data collected is incomplete or inaccurate, or if the protocols used to conduct the analyses are improper or not followed, an employer could end up relying on flawed results to its detriment.
Recent legal developments and executive actions have also raised concerns. For instance, President Donald Trump’s Executive Order 14173 emphasizes merit-based opportunities and the need to end federal contractors’ “illegal” diversity, equity, and inclusion (DEI) programs. Consequently, data analyses supporting illegal DEI programs can create risks. Similarly, Executive Order 14281 seeks to eliminate or discourage the use of disparate-impact liability theory, where neutral policies disproportionately affect individuals based on protected characteristics, including in the employment context.
Although these executive actions have created some confusion about pay equity and other data-driven requirements, it is important to recognize that they do not change employers’ fundamental legal obligations. Pay equity continues to be a critical compliance area. Although federal agency enforcement priorities may shift, the underlying laws prohibiting pay and other forms of discrimination are unchanged.
Employers are well advised to ensure their pay decisions do not discriminate against employees based on protected characteristics. Similarly, Title VII of the Civil Rights Act of 1964 continues to prohibit discrimination in all aspects of employment, including hiring, promotion, termination, and compensation, based on race, color, religion, sex, and national origin, and the Age Discrimination in Employment Act continues to prohibit discrimination on the basis of age. For example, in most cases, adverse impact analyses are important when conducting reductions in force to determine whether the company’s selection decisions disproportionately disfavor employees on the basis of race, ethnicity, gender, or age.
In addition, the U.S. Supreme Court’s recent decision in Ames v. Ohio Dept. of Youth Services confirmed that Title VII protections apply to all employees, regardless of minority or majority-group status. Therefore, employers should ensure that their analyses consider not only whether women or members of specific minority groups are disadvantaged, but whether there is any indication of “reverse discrimination” against men or white individuals.
To mitigate potential risks, banks and financial institutions should identify the legal authority supporting their data collection and analysis efforts. This support could include compliance with EEO-1 reporting obligations or state pay data reporting and conducting artificial intelligence bias audits. Moreover, it is crucial for banks and financial institutions to protect their communications and analyses as much as possible with the attorney-client privilege.
In sum, banks and financial institutions should carefully weigh the risks and benefits of conducting data-driven personnel assessments. If analyses are conducted, employers should ensure that the data collected is complete, accurate, and serves a clear business-related purpose. Employers should also evaluate whether to seek data not required by law and protect the access to confidential data. Staying informed about changes in executive orders and regulatory requirements is also essential to maintaining compliance and leveraging data analytics effectively.
Banks and financial institutions should navigate these complexities carefully to harness the full potential of their data analytics while minimizing risks.
Daniel V. Duff III is an equity principal in Jackson Lewis' Litigation and Affirmative Action Practice Groups and works in the firm’s New York Metro region. Reach him at Daniel.Duff@jacksonlewis.com.
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