With the onset of spring, a bunch of different NAIC groups and states are springing up to consider the use of big data and algorithms by insurers, including algorithms based on machine learning. Many are focused on life insurance underwriting and seeking to ensure that any unfair bias is eradicated from the data and algorithms used by insurers. The NAIC’s 2022 activity will be cultivated by the newly formed Innovation, Cybersecurity and Technology (H) Committee (H Committee). States are also bustling with activity, and Colorado planted its bulbs in early 2022 by hosting two stakeholder meetings, as required by Senate Bill 21-169 (as codified in Section 10-3- 1104.9 of the Colorado statutes).
NAIC
The new H-Committee facilitates all NAIC groups and addresses innovation and technology issues so that information and ideas can be crossed between all regulators and interested individuals. The objectives of Committee H are to:
- Identify problems related to the use of innovation and technology;
- Understand how the use of innovation and technology affects the insurance market;
- Understand how insurers innovate and use technology; and
- Understand how the use of innovation and technology by these insurers can be regulated.
To further foster collaboration and ensure that no unfair bias takes root, one of Committee H’s first projects is a collaboration forum that will (i) address algorithmic biases by identifying and addressing fundamental issues and (ii) develop a common framework that can inform the specific workflows in each NAIC group. This will bring together the work of:
- NAIC Accelerated Underwriting Working Group (AU WG)
- NAIC Big Data & Artificial Intelligence Working Group (Big Data & AI WG)
These working groups also reported on their activities at the NAIC’s Spring 2022 National Meeting.
The AU Task Force Education Report has come into full bloom as it was adopted by the AU Task Force at the National Spring Meeting. The educational report provides broad insight into the use of big data and accelerated underwriting by life insurers, setting the stage for regulators and interested parties. The educational report examines the differences between Accelerated Underwriting, Traditional Underwriting, and Simplified Underwriting, as well as the current prevalence of these practices and anticipated trends for the future. It also examines the use of various types of consumer data, including traditional data, non-traditional data, Fair Credit Reporting Act data, and the issue of the use of biased data.
Some consumer representatives have criticized the education report’s lack of concrete guidance for states and reliance on current unfair trade practices laws. However, the Chair of the AU Task Force noted that the next work product of the AU Task Force would be to create a Regulator’s Guide which builds on the Educational Report and provides specific guidance to Regulators.
Within the Big Data & AI WG, several projects are emerging.
- Workstream One – Initially, the Big Data & AI working group sought to increase regulatory understanding of the use of artificial intelligence and machine learning in private passenger auto insurance; now the field of work is branching out to conduct similar surveys for homeowners and life insurance.
- Workstream Two – Seeks to develop tools to help regulators review accelerated underwriting models and help regulators determine if biases are “built in” to the data or models used.
- Workstream Three – Investigates the industry’s reliance on third-party data and algorithm providers and how to “best regulate these entities”, including through revised review standards.
- Workstream Four – Seeks to seed a white paper on a regulatory framework that pulls together all of the other workstreams’ news clippings.
States
Oklahoma sprouted Bill 3186 and Rhode Island spawned Bill 7230, which are substantially similar to Colorado Senate Bill 21-169. As we previously reported, Colorado prohibits insurers from using external consumer data, information sources, algorithms, or predictive models based on that data in a way that unfairly discriminates based on race, color, national or ethnic origin, religion, sex, sexual orientation. , disability, gender identity or gender expression. Colorado hosted two stakeholder meetings focused on life insurance underwriting practices where the key terms “external sources of consumer data and information” and “traditional underwriting practices” and the process of required test were discussed.
Other state activities include:
- New Jersey Assembly Bill 5651 requires annual reports from auto insurers using an automated or predictive underwriting system, to demonstrate that there is no discriminatory outcome in insurance pricing, and directs the Commissioner of Banking and Insurance to cultivate rules and regulations.
- A preliminary investigative statement was filed by Washington regarding possible insurance underwriting transparency regulations to address its concern that “insurance consumers are not receiving full disclosure and transparency from insurers for adverse actions, rate changes or factors that insurers consider in determining premiums. The proposal would require insurers “to provide notices to consumers for all factors assessed in any related insurer action, which must include detailed disclosure of all variables considered in underwriting, as well as proportionality or weight at which these factors were assessed”.
- Connecticut updated its departmental advisory regarding “the use of big data and the prevention of discriminatory practices” to remind insurers of their obligation to ensure that their use of big data complies with federal and state anti-discrimination laws, that the seeds of their data and algorithms come from in-house or from a third-party provider. Insurers are also required to submit annual data certification to the Connecticut Department of Insurance. The notice also affirms the authority of the Connecticut Department of Insurance to require insurance companies and third-party data providers, model developers, and offices to provide the department with access to data used to create models or algorithms included in all subscription rates, forms and filings.
As spring turns into summer, more varietals are sure to emerge as other regulators begin to tend to their gardens. We will continue to monitor NAIC and state activity regarding the use of big data and algorithms by insurers.