Lauren N. Ybarra, Burnie Burner, Jeffrey H. Thomas
To kick off the New Year, the New York Department of Financial Services (“DFS”) published Insurance Circular Letter No. 1 (2019) warning life insurers that use of external consumer data and information sources, commonly coined as “BigData,” against use in underwriting life insurance. The DFS stressed data, algorithms, or predictive models should not be used unless the insurer can evidence the data is not unlawfully discriminatory or otherwise in violation of New York and federal laws.
This letter was published in response to an investigation of insurers’ practices and underwriting guidelines related to the use of BigData in underwriting life insurance.
This circular letter, the first of an impending many, poses many issues to insurers who outsource their data. For example, how can an insurer verify the accuracy and completeness of data vendors use? The letter raises the issue that the underlying data as input for the algorithm could include data based on discriminatory or propertied data. Insurers should strive to understand the data and protect themselves from potentially problematic outcomes. The process in which information is evaluated is usually a “black box” algorithm that is, or should be, proprietary and protected. Under the FCRA, consumer-reporting agencies must provide notice to applicants and an opportunity to review the data when an adverse decision was made. Will this be the future way to regulate data vendors? It is apparent the current insurance statutes in place did not contemplate the reality of data changes and use.
The letter also stresses insurers “must also disclose to consumers the content and source of any external data upon which the insurer has based an adverse underwriting decision.” The “[t]ransparency is an important consideration in the use of external data sources to underwrite life insurance.” As the circular letter indicates, information collected can include retail purchase history, social media activity, even how a person is represented in photos, and other otherwise personal and potentially bias conclusions about an individual. How to determine the accuracy of the data and evaluation will be an issue for regulators and insurance companies alike. Additionally, it will be difficult for insurers and data vendors to negotiate who owns the propriety data collected.
Where most companies strive to be more relatable to the public, how can insurers ethically manage data that provides better rating and underwriting opportunities for the public?
The use of Big Data will be discussed in multiple forms at the upcoming National Association of Insurance Commissioners (“NAIC”) meeting with action expected by several committees.
One thing is certain, the way insurers use data with the open availability of information will drastically be influenced by how quickly state and federal regulators can determine how and when BigData is used.