Insurance pricing discrimination and Aristotelian equality: an application to annuity pricing

International courts often apply the social justice standard of Aristotelian equality—treating like people alike and unlike people differently—to cases involving insurance pricing discrimination. This article examines whether the use of insurance pricing variables like gender and race results in discriminatory pricing categories consisting of heterogeneous policyowners, in violation of Aristotelian equality. This article applies this discrimination standard to the pricing of annuities, drawing from studies investigating the racial mortality crossover, findings that show that the mortality rate of Black Americans falls below the rate of White Americans at advanced ages. Based on the crossover literature, this study demonstrates how race-based annuity pricing would be discriminatory because it results in heterogeneous pricing within racial pricing categories, but that insurers can control for this heterogeneity by using the wider variety of annuity pricing data (e.g., medical history, diseases, and smoking) developed in the enhanced annuity submarket. The article demonstrates how the increased use of data analytics in insurance pricing to control for heterogeneity is consistent with Aristotelian equality.

Do Health Insurers Manage Their Medical Loss Ratios? At What Cost?

We use plan-level data to examine a reporting incentive unique to health insurers—the federal Affordable Care Act’s (ACA’s) Medical Loss Ratio (MLR) provisions—which require that health plans spend a specified percentage of premiums on claims or else pay policyholder rebates. While there are no penalties for noncompliance with the MLR provisions, incentives for insurers to comply include avoiding political and reputation costs, reducing administrative burdens, and eliminating rebate payments. We find that health plans with pre-managed MLRs— i.e., the MLRs that would be reported without reporting discretion—below the required MLR overstate claims, thereby increasing their MLRs and reducing or eliminating rebate payments. Overall, results suggest that overstating claims reduced rebate payments by approximately $190 million to $325 million for 20112013; i.e., about 10–17% of total rebates actually paid. We also find that plans with pre-managed MLRs significantly greater than the minimum required MLR understate claims, thereby improving plan earnings while still complying with the MLR provisions. These understatements average between 14–34% of plans’ pre-tax earnings.

AI-Enabled Underwriting Brings New Challenges for Life Insurance: Policy and Regulatory Considerations

Insurers are increasingly using novel data sources and automated systems for risk classification and underwriting. Automation has improved operational efficiencies in the accuracy and speed of underwriting, but it also raises new considerations relating to unfair discrimination. In this paper, we review the current regulatory structures relating to unfair discrimination and suggest they are insufficient to police the myriad new big data sources available. Moreover, AI-enabled systems increase the risk of unfair discrimination if a facially neutral factor is utilized by an automated system as a proxy for a prohibited characteristic. Furthermore, many insurers rely on unregulated third-party algorithm developers, and therefore do not own and may not have access to the logic embedded in the system, which raises unique ethical implications, particularly with respect to accountability among AI actors. To address these issues, we propose a framework that consists of three parts: (a) the establishment of national standards to serve as guardrails for acceptable design and behavior of AI-enabled systems; (b) a certification system that attests that an AI-enabled system was developed in accordance with those standards; and (c) periodic audits of the systems’ output to ensure it operated consistent with those standards. The framework rests on the existing state-based regulatory infrastructure and envisions a self-regulatory organization who can work with the NAIC to develop standards and oversee certification and audit processes. Regulatory enforcement remains with the states. Part I describes the use of technology in life insurance underwriting. Part II discusses the unfair discrimination that can occur due to factors that reflect societal biases, and the unfair discrimination that could occur in artificially intelligent systems if facially neutral factors are substituted by the system for prohibited factors. The current industry standards and regulatory scheme for unfair discrimination in underwriting is also discussed in Part II. Part III describes the ethical concerns regarding accountability when third-party data inputs and underwriting systems are utilized. In Part IV, we propose a governance approach and framework to address these concerns.

The changing of the guard (LIBOR to SOFR) and how both insurers and regulators are responding

The London Inter-bank Offered Rate (LIBOR), the rate for which banks can borrow short-term from each other, and perhaps the most common floating interest rate benchmark, is going away, and may become obsolete by end of year (EOY) 2021. LIBOR is being replaced by the Secured Overnight Financing Rate (SOFR) in the U.S. and by other country-specific alternative risk-free rates abroad. However, SOFR differs in several key respects from LIBOR; for example, LIBOR includes credit risk, is unsecured, is based on expert judgment, and has a full-term structure, whereas SOFR is a risk-free rate, is collateralized, is based on market transactions, and has no term structure. We examine the credit risk and maturity risk adjustments needed to ease the transition, along with fallback provisions for legacy contracts tied to LIBOR. We discuss the ramifications of rate transition to insurance companies, as it relates to their assets, liabilities, and internal processes. We then consider the perspective of both U.S. and global insurance regulators while highlighting specific areas of inquiry. We conclude with an overview of general recommendations for insurers to manage these risks, along with a detailed discussion about whether interest rate swaps tied to LIBOR will continue to be deemed as an effective hedge for accounting and valuation purposes.

A framework for defining a role for insurance in "uninsurable" risks: insights from COVID-19

Recognizing the challenges facing insurers and the public sector in dealing with the COVID-19 pandemic, this paper proposes a decision-making framework for evaluating the performance of risk management strategies for dealing with the impacts of risks traditionally considered by insurers as uninsurable. We discuss three alternative options through which the property/casualty (P/C) industry may be able to play a role in supporting businesses, nonprofits, and the public sector in managing future pandemics and other catastrophic and systemic risks.

Insurance for Social Media Liability

Whether a claim involves “bodily injury” or “property damage” is a threshold issue for coverage under Coverage A of the standard comprehensive general liability (CGL) policy and homeowners policy. Social media-related claims that allege pure emotional distress, without corresponding physical manifestations, or that allege damage to intangible property, such as intellectual property rights, may not fall within the insuring agreements of these policies. Social media claims often allege intentional conduct, if not intentional harm, which raises the threshold issue of whether the claim alleges an “occurrence” such that coverage is triggered. To the extent a social media claim falls within the policies’ insuring agreements, the next issue is whether the policies contain exclusions that might apply. Exclusions for expected or intended injury, employer’s liability, and electronic data may limit coverage for social media claims. Likewise, exclusions in homeowners policies for “bodily injury” or “property damage” arising from a home business, professional services, or physical or mental abuse may apply to common social media claims.

Citizens and the Florida residential property market: how to return to an insurer of last resort

Developments in 2020 have heightened concerns regarding market disruptions, which could result in increases in Citizens Property Insurance Corporation's (Citizen's) exposure. As a result, Citizens contracted with Florida State University (FSU) to conduct an analysis of Citizens' exposure and identify: 1) opportunities to reduce its exposure; and 2) ways to increase the availability of private market residential property insurance. The FSU study finds that while Citizens has real opportunities to effectively reduce its exposure in the long term, a combination of strategies will be necessary to ensure the adequacy of rates and solvency of private insurers operating in the residential property market. Additionally, several actions must first be taken to improve the attractivenss of the Florida market and increase the capacity of the private market before changes to the structure of Citizens can be made. Finally, the FSU study notes that to achieve Citizens' goal of reducing its exposure, the issue of affordability of homeowners insurance may need to be addressed outside of the insurance process.

The COVID-19 Pandemic and Health Insurance Regulation

With projections of costs in the billions for COVID-19 treatments alone, and heightened scrutiny on COVID-19-related health insurance coverage, the National Association of Insurance Commissioners (NAIC) convened in March 2020 to discuss how the industry could best deal with a pandemic. While the ramifications of the COVID-19 event are in their infant stages, it is important to consider the implications such catastrophic risks have on an insurance market. We evaluate state-level changes presented by the NAIC in response to the COVID-19 pandemic and use prior research to offer insight into health insurance in a post-COVID-19 world. This manuscript aims to provide a summary of the NAIC’s current standing during the pandemic, while presenting insight into policy implications regarding regulation in health insurance markets during catastrophic events.

Gender X and auto insurance: is gender rating unfairly discriminatory?

There are three goals of insurance rate regulation. Rates must be: 1) adequate; 2) not excessive; and 3) not unfairly discriminatory. Rates that are adequate yet not excessive are overall high enough to pay claims and expenses, yet not so high overall that they result in unreasonable profiteering by insurers. The third regulatory goal—that rates are not unfairly discriminatory—is the topic of interest in our research. The concept of unfair discrimination in an insurance context—determining what constitutes fairness in pricing—can differ substantially from the thinking on fairness in a societal context. As a result, the term “discrimination” may be used quite differently in these two contexts. Discrimination, with negative societal connotations, is endemic in our world broadly and largely unjustifiable, yet in the narrower world of insurance, it is the basis for the entire industry’s viability and sustainability. In the insurance context, we can receive the term “discrimination” in a neutral manner, simply taking it to mean different treatment for different groups having different characteristics, without it necessarily connoting any negative intent or outcome. Indeed, the purpose in insurance for engaging in “fair discrimination” —that is, discrimination that price differentiates between discernibly different levels of risk—is itself rooted in economic fairness. An insurance carrier charges differential prices for its products based on differentials in risk. Nevertheless, when risk transfer to an insurer is priced based on uncontrollable and/or immutable classifications such as race and gender, there can be profoundly different views of what constitutes fairness. In many areas of U.S. law, discrimination on either the basis of gender or sexual identity is prohibited in a number of jurisdictions for a number of consumer situations. Yet the broad concept of societal fairness and the much narrower concept of actuarial fairness differ, and so within insurance markets, U.S. law has historically set insurance apart from other products in speaking to issues of fairness and discrimination (West, 2013). Within the last year, several states have enhanced their recognition of nonbinary or genderqueer identities by implementing a Gender X option on driver’s licenses. Insurance carriers are left with minimal direction on how to appropriately price this emerging class within the three goals of rate regulation. Additionally, as diversity and inclusion continue to be a strategic initiative within the insurance market, the insurance industry and its regulatory environment have to navigate carefully between the business imperatives for adequate pricing and inclusion efforts. This paper addresses the potential for unfair discrimination in some lines of business—with special focus on auto insurance—should gender-based rating be continued into the future. It also explores an immediate opportunity to enhance the insurance industry’s social compact with its insureds via recognition of the Gender X identity. Part I gives a primer on nonbinary and trans-identity followed by a brief history of the role of gender in insurance pricing, Part II discusses nonbinary, transgender, and the introduction of Gender X as an additional categorical level of the gender identify rating factor as used in insurance pricing. Part III and Part IV dive into the economic and social implications of movement in U.S. law toward more gender inclusivity.