Rethinking mental illness exclusions in the context of the Ingram decision05 April 2016
In a recent VCAT decision, QBE Insurance (Australia) Ltd was held to have engaged in unlawful discrimination when it refused to indemnify a claimant under a travel insurance policy, relying on a mental illness exclusion in the policy. This decision is a reminder to the insurance industry that if legislation requires the industry to rely on actuarial or statistical data when dealing with mental illness exclusions in policies, that data must exist at the time the particular policy was issued to the market. It also reinforces the importance of history and information management, and the retention of data that underpinned why an exclusion or term was introduced in a policy.
The fact that the exclusion is common in the market is not a defence.
Background and Ms Ingram's claim
In late 2011, Ms Ella Ingram elected to join a school trip to New York scheduled for March and April 2012 and purchased a travel insurance policy issued by the insurer. In early 2012, Ms Ingram was diagnosed with, and received treatment for, depression and the decision was made for her to withdraw from the trip. In May 2012, Ms Ingram made a claim for the costs of cancelling her trip, which was denied by the insurer that relied on a general exclusion clause preventing claims directly or indirectly arising from mental illness.
Ms Ingram began proceedings against the insurer in the Human Rights division of VCAT. She contended that her mental illness should be regarded as a "disability" and therefore an attribute that invokes the protection of the Equal Opportunity Act 2010 (Vic.) (EOA). Ms Ingram argued that by including the mental illness exclusion in the policy and then refusing to indemnify her on the basis of that mental illness, the insurer treated her unfavourably because of her disability and directly discriminated against her, contrary to ss 44(1) (b) and 44(1)(a) of the EOA.
QBE's defence and the Tribunal's findings
The insurer conceded that Ms Ingram had a disability in August 2012 when it refused to indemnify her but argued she had no symptoms or diagnosis when the policy was purchased in 2011. However, Member Dea noted that the statutory definition of "disability" under the EOA includes disabilities that may exist in the future.
The insurer argued that if it did discriminate as alleged, then that discrimination was lawful because an exception contained in the EOA and/or Disability Discrimination Act 2004 (Cth) (DDA) applied:
- when the policy in question was first issued in March 2010 and when indemnity was denied in August 2012, the acts of discrimination by the insurer were based on actuarial or statistical data [s 47(1)(b) of the EOA and s 46(2)(f) of the DDA], and
- the insurer would have suffered unjustifiable hardship if it had not included the mental illness exclusion in the policy (s 29A of the DDA).
The insurer ultimately failed to make out either defence because there was no evidence that it relied upon particular actuarial and statistical data, as required under s 46 of the DDA. The evidence it relied upon mostly post-dated the issuance of the policy and the insurer could not prove that it relied upon the data that pre-dated the issuance date.
With regard to the first defence, Member Dea inferred that the insurer must have had a rational reason for including the exclusion. However, the insurer's provision of predominantly retrospective evidence led her to conclude that it had failed to establish that any person involved in the drafting of the policy wording had any knowledge of, or regard to, information relevant to the actuarial and statistical data exception.
When considering the insurer's second defence, Member Dea again concluded that there was insufficient material for her to determine that it would be an unjustifiable hardship for the insurer to be unable to rely on the mental health exclusion. She held that Ms Ingram was entitled to economic loss in the value of her cancelled trip as well as $15,000 for hurt and humiliation and a portion of her costs.
What this means for the insurance industry
The insurer submitted that the inclusion of a blanket mental illness exclusion is general industry practice. Only a minority of insurers do not rely upon a similar exclusion in travel policies.
Like many policy exclusions, the mental illness exclusion has crept into personal accident and travel policies without a proper understanding of why the exclusion was introduced, the effect of s 46 of the DDA and that, absent of actuarial and statistical information, the exclusion constitutes discrimination.
One argument raised by the insurer was that it had no actuarial or statistical data because, given the mental illness exclusion, it does not receive claims or, if someone believes they have a claim, it will be denied on the basis of the mental illness exclusion. Many insurers will find themselves in a similar position.
So what can be done to prevent a repeat of the outcome? With adequate information management, it should be possible to identify the historical reason why an exclusion, such as the mental health exclusion, is introduced.
But are insurers keeping this historical data? The second issue is that when someone drafts a policy wording, the mere fact that an exclusion is commonplace or market accepted may not be good enough. Both insurers and lawyers vetting policies should enquire why the exclusion is there.
Does this open the floodgates to claims? This is possible, although Member Dea sought to limit the decision to the particular facts. The legislation is clear and has been known to the industry for more than two decades. The challenge for the industry is to use statistical and actuarial data that it has to price the cost of removing the exclusion, to avoid the allegation of discrimination. Most probably that will involve an increase in premium for all buyers of travel insurance but it treats all buyers equally without discrimination.
The argument flows that you unlawfully discriminate if you do not rely upon actuarial and statistical data—so make sure you use that data to properly price products.