Pricing fairness: tackling big data and COVID-19 insurance discrimination

Research highlights the need for regulators, consumer advocate groups and industry associations to be involved in determining what insurers can – and cannot – discriminate against

In 2015, insurance giant QBE was found guilty of unfairly discriminating against a young woman, Ella Ingram, for a pre-existing mental health condition. QBE issued Ms Ingram with travel insurance that excluded mental health coverage, then rejected her claim after she was hospitalised with depression and had to cancel a school trip to New York. The case was an Australian first and was viewed as a test of the lawfulness of insurance discrimination against mental illness. Ms Ingram made headlines for publicly challenging QBE and went on to be named among BBC's 100 inspirational women that year.

In 2019, the Insurance Council of Australia announced it would lead an industry-wide mission to extend travel insurance policy coverage for mental health conditions, which followed an investigation by the Victorian Equal Opportunity and Human Rights Commission. This found 365,000 travel insurance policies sold over eight months contained terms that discriminated against people with a mental illness. As a result, around 80 per cent of the travel insurance market either removed general exclusions for mental health conditions, with cover becoming more widely available for first-instance episodes. With 45 per cent of Australians likely to suffer a mental health condition at some stage in their lives, these developments could have a significant impact on many.

Discrimination in the insurance industry

The insurance industry is based on discrimination, says UNSW Business School's Dr Fei Huang, Senior Lecturer and Honours Program Coordinator in the School of Risk & Actuarial Studies. Unfair discrimination has been a crucial topic for the insurance industry over the past few decades, and Dr Huang says it continues to evolve in part due to insurers' extensive use of big data.

"Discrimination issues regarding privacy and use of algorithms are taking on increased importance, especially as insurers' extensive use of data and computational abilities evolve," says Dr Huang. She explores this in her paper: The Discriminating (Pricing) Actuary, alongside co-author Edward W. (Jed) Frees, Emeritus Professor in the Risk and Insurance Department at the University of Wisconsin–Madison and Professor in Actuarial Studies & Statistics at the Australian National University.

Insurers often discriminate and charge more from some people for the same product-min.jpg
Insurers often discriminate and charge more from some people for the same product. Image: Shutterstock

Discrimination is the act of treating groups differently – groups are distinguished by obvious features such as hair colour, age, gender, heritage, religion, and so forth. Is insurance discrimination ever justifiable? 

"For example, auto insurers often charge younger (and presumably riskier) drivers more than older (presumably safer) drivers, but do not make a distinction between brown-haired and red-haired drivers (presumably because the two groups are equally risky). So, discrimination based on age is done routinely, whereas discrimination based on hair colour is not," explains Dr Huang.

The treatment of 'related variables' is a key factor here, and raises potential issues. The use of variables related to a prohibited variable constitutes indirect discrimination. Although they do not have the usual characteristics of an unfair variable, they negatively affect society. A classic example of this is redlining – drawing red lines on a map to indicate areas insurers will not serve, areas typically containing high proportions of minorities or people of lower socioeconomic status. 

"In this example, it was prohibited to use race as a rating variable and yet, through the use of a geographic proxy (such as an area with a concentration of minorities), at one time insurers were able to indirectly discriminate against minorities," says Prof. Frees.

Read more: A smarter approach to analysis refines insurance predictions

The authors present different arguments to identify different situations when insurance discrimination is fair and ethical and when it is unfair and morally indefensible. They conclude courts, legislatures, and other stakeholders including regulators, consumer advocates, and industry associations should all play a role in determining what insurers can and cannot discriminate against.

Big data discrimination: privacy and proxies

Big data is changing the way insurers do business. As with all institutions, insurers are redefining how they do business with the increasing capacity and computational abilities of computers, availability of new and innovative sources of data, and advanced algorithms that can detect patterns in insurance activities that were previously unknown. But conceptually, the authors say big data itself is not a discrimination issue.

Big data presents two key issues: privacy and the use of proxies. In terms of privacy, detailed information is sometimes provided voluntarily by individuals to insurers and is not treated as sensitive. This includes information from global position systems (GPS) that we put in our cars, comparable devices for our homes (the Internet of Things), devices we wear to improve our health etc., explains Dr Huang.

Businessman looking at computer screen with data (1).jpg
Privacy and the use of proxies are two key issues in insurers' use of big data. Image: Shutterstock

Insurers may also use other information that is not provided directly by individuals for their own commercial purposes. For example, privacy issues are raised any time a carrier classifies risks on intimate, personal information, like HIV status, marital status, sexual orientation, or genetic information, she says. 

Proxy discrimination occurs when a surrogate (proxy) is used in place of a prohibited trait, such as gender, race or nationality. This proxy is a facially neutral trait, like the size of an automobile's engine being used as a proxy for gender. In the world of big data, complex algorithms are being developed using thousands of traits. Proxy discrimination may be unintentional; moreover, Dr Huang says an insurer may not even be aware it is engaging in discriminatory behaviour due to the opaqueness of machine-driven algorithms.

The impact of COVID-19

As with other parts of the global economy, the COVID-19 pandemic has rocked the insurance industry. The lines of business most affected on the commercial side include workers' compensation, business interruption insurance, cyber liability, general insurance liability and event cancellation, while health and travel insurance have been most affected on the personal side, says Dr Huang.

Insurance legislation is being introduced to prohibit discrimination based on the diagnosis of this disease. “For example, on 14 April 2020, the Australian Competition and Consumer Commission granted interim authority to the Financial Services Council and its members to ensure frontline healthcare workers are not excluded from coverage due to exposure to COVID-19. That means life insurers cannot use the exposure to COVID-19 as a factor for pricing or applying risk exclusions to any new policy,” says Dr Huang.

Doctor nurse in protective face mask listening to breath with a stethoscope suspecting Coronavirus (COVID-19).jpg
Insurance legislation is being introduced to prohibit discrimination based on the diagnosis of COVID-19. Image: Shutterstock

Such legislation has several implications. "For example, in absence of this legal restriction, rates may well increase for grocery store workers, due to their exposure and increased suspicion of a diagnosis of COVID-19. Is this in the best interest of society?” Dr Huang asks. "For a pandemic, the weight of evidence suggests societal concerns dominate and that a prohibition based on diagnosis, real or suspected, of COVID-19, is warranted."

Ensuring pricing fairness

Understanding the principles of ethical discrimination is vital for actuaries and other financial analysts. Actuaries are heavily involved in setting insurance prices; they are also often influential in determining the scope of contractual insurance coverages and who the company insures, both initially and at renewal, the authors say.

Indeed, the research provides a framework to help actuaries present financial cost recommendations in a meaningful way by summarising different perspectives. To tackle discrimination in the industry, Dr Huang says actuaries can make significant contributions to these discussions by quantifying policy alternatives' financial impact.

Read more: Is income-indemnity insurance an aged care solution?

Policies describing what insurers cannot discriminate against (having ever contracted COVID-19, for example) will also increase consumer confidence in the insurance system more broadly.

"Our position is not that actuaries should dictate whether or not information should be unrestricted, partially restricted, or prohibited. Rather, choices regarding insurance prohibitions involve policy choices should also involve legal and economic scholars, as well as government representatives and advocates for the industry and consumers," say the authors.

Read the paper: The Discriminating (Pricing) Actuary, co-authored by Dr Fei Huang Senior Lecturer in the School of Risk & Actuarial, and Edward W. (Jed) Frees, Emeritus Professor in the Risk and Insurance Department at the University of Wisconsin–Madison and Professor in Actuarial Studies & Statistics at the Australian National University. For more information, please contact the academics directly.


You are free to republish this article both online and in print. We ask that you follow some simple guidelines.

Please do not edit the piece, ensure that you attribute the author, their institute, and mention that the article was originally published on Business Think.

By copying the HTML below, you will be adhering to all our guidelines.

Press Ctrl-C to copy