Regulators Gearing Up to Monitor Accelerated Underwriting Programs

• Draft regulatory guidance document for regulators to use when reviewing life insurers’ use of accelerated underwriting programs. The draft, dated January 25, 2023, was exposed for comment with a requested due date of April 14, 2023;
• Draft referral to the Market Conduct Examination Guidelines (D) Working Group, suggesting changes to the NAIC’s Market Regulation Handbook to address questions involving accelerated underwriting in life insurance. The draft, dated January 11, 2023, was exposed for comment with a requested due date of March 24, 2023; and
• Recommendation that additional model laws, regulations, data, processes, and tools are needed for regulators to appropriately monitor the use of accelerated underwriting programs by life insurers. According to the AUWG, such initiatives should include regulating data and vendors that provide external consumer nontraditional, nonmedical data and predictive models to insurers, as well as mandating consumer disclosures related to insurers’ use of such data in artificial intelligence and machine learning models and algorithms.

The AUWG Draft Regulatory Guidance Document

The AUWG Draft Regulatory Guidance Document contains two sections:

• An introduction that describes the work conducted by the AUWG since its inception in 2019, and the AUWG’s plans for coordination with other NAIC groups on similar or overlapping issues related to accelerated underwriting. The introduction also contains the AUWG's recommendation that the Innovation Cybersecurity and Technology (H) Committee consider additional model laws, regulations, data, processes, and tools; and
• The regulatory guidance, which expounds on the recommendations the AUWG made in its educational paper and provides sample questions and areas for regulator reviews.

The regulatory guidance is composed of three parts:

1. Nine “regulatory considerations,” which the draft also refers to as “regulatory expectations.”

Four expectations relate to consumer data, algorithms, or predictive models used in accelerated underwriting. Among other things, these considerations require that the data being used is evaluated for “unfair bias,” that the data used and the decisions made are based upon sound actuarial principles, and that the algorithms and predicative models “accurately assess and price risk” and achieve an outcome that is not “unfairly discriminatory.”

Notably:

• While the educational paper also used the term “unfair bias,” that term is not defined in either the educational paper or the draft regulatory guidance. It also seems that the term “unfair bias” means something different from “unfairly discriminatory” or “unfair discrimination” as defined in the NAIC Unfair Trade Practices Act (Model 880); and
• Requiring that predictive models or machine learning algorithms accurately assess and price risk appears to demand a higher standard than applicable actuarial standards. The actuarial standard for setting nonguaranteed elements, ASOP 2, requires that the NGE scales be determined based on “reasonable expectations of future experience.” The actuarial standard for risk classification, ASOP 12, acknowledges that risk classification requires the “exercise of considerable professional judgement,” and that there may be “various acceptable approaches.”

Three expectations relate to the insurer’s policies and procedures regarding the consumer data being collected and used, including the ability of consumers to correct data, receive notices, and opt out of data sharing or otherwise restrict the use of data.

One expectation is that consumers are provided with all information upon which the insurer based an adverse underwriting decision.

One expectation is that the insurer will produce information to regulators upon request or in connection with market conduct examinations.

2. Five proposed “regulatory actions.”

Four proposed regulatory actions relate to requests for information that a regulator may make. These include information on the data sources, predictive models, and algorithms, including how they are used in an accelerated underwriting program and whether they are audited by the insurer to “ensure they are accurate, reliable, and do not result in unfairly discriminatory outcomes.”

One proposed regulatory action relates to the review of a life insurer’s “initial submission of policy filings to confirm the proper use of data elements.”

These five proposed regulatory actions raise a number of questions, including:

• What is meant by “unfair discriminatory outcomes”?
• If insurers file their products with the Interstate Insurance Product Regulation Commission, how would regulators review the policy filings to confirm the proper use of data elements? In addition, for products that are filed for use in all states, would the insurer be subject to a multistate review?

3. Fourteen example “regulatory questions and requests” to life insurers.

Seven questions relate to the insurer’s auditing of the data sets, predictive models, and machine learning algorithms to ensure accuracy, reliability, and outcomes that are not unfairly discriminatory and that the models “are based on sound actuarial principles” and “ensur[e] that external consumer data’s correlation to risk is not outweighed by any correlation to a protected class(es).”

Four questions relate to disclosures to consumers and consumers’ rights in the event of an adverse underwriting decision, including the right to correct mistakes in the external data. 

Three questions relate to the external data or information being used by the accelerated underwriting program and how such data is utilized, stored, and destroyed after the completion of the underwriting process.

The concluding paragraph of the regulatory guidance makes clear that additional guidance will be needed from other NAIC committees and working groups.

AUWG Draft Referral to Market Conduct Examination Guidelines (D) Working Group

The draft referral includes a recommendation that the NAIC’s Market Regulation Handbook include a new standard in Chapter 23 — Conducting the Life and Annuity Examination — related to a life insurer’s use of big data, artificial intelligence, and machine learning to underwrite life insurance. According to the AUWG, the applicable standard should address how accelerated underwriting programs are fair, transparent, and secure. Under the AUWG’s recommendation, examiners would review “policy rates and forms, accelerated underwriting models and/or summaries of those models, information about source data used as part of the accelerated underwriting program, consumer disclosures, and testing and/or auditing policies and procedures of the models.”

We will continue to monitor AUWG activities, and other NAIC groups with respect to their review of insurers’ use of consumer data, algorithms, and machine learning.