Introduction

The impact of COVID-19 on medical insurers across Europe will vary significantly, depending not only on the profile of infection rates and hospital capacity in each country, but also on the specifics of coverage of the typical benefit plan for health insurers (which is usually itself a function of state-funded benefits). However, in talking with our clients across multiple countries and carrying out some initial modelling, we have identified a number of common themes across Europe.

1. Underwriting risk

The impact of COVID-19 on loss ratios for 2020 and into 2021 could be net positive or negative for 2020, depending on the exact terms and conditions and benefits covered, as well as the impact on the local healthcare delivery system. The various assumptions required to model COVID-19 incidence rates and hence claims are still highly uncertain and changing on a daily basis. Having a framework which allows rapid updating of models with new information as it becomes available is critical.

Medical insurers with a high proportion of claims costs in non-COVID-19 hospitalisation benefits are likely to see reduced claims for some months in 2020, but with a potential uplift later in the year or into 2021 if the lock down period is protracted and delay of services continues later into 2020. This presents significant challenges for reserving and pricing for 2021 and potentially 2022, where the most recent historical trends that those processes rely on are likely to be highly unstable and unreliable for forecasting purposes. For insurers with material proportions of more routine claims (dental checkups, optical exams, etc.), services are more likely to be cancelled than deferred, with a positive impact on claims in 2020, but some potential for more severe treatment due to the deferment of preventative care or routine checkups to catch problems early. Some emergency services that could have been provided by dentists during the lockdown period of 2020 may even have ended up taking place in other settings (for example, hospital) and may not have therefore been reimbursed by insurers in the same way.

In many countries, there is a material risk of increased lapses from the economic downturn. Employers and brokers are reducing staff and requesting payment holidays or other deferment of premiums (which means insurers need to be careful not to recognise profits from premiums that may not ultimately arise). Combined with low levels of new business due to lack of sales capability and customer reticence to change insurers during periods of uncertainty, there is likely to be a significant impact on revenues. A proportion of lapses will be selective, i.e., the younger healthier lives are most likely to leave risk pools, leaving behind older, unhealthier lives.

Some insurers have rushed to provide new benefits for COVID-19 claimants – the most common being to allow remote consultations and to promote their general practitioner (GP) helplines. However, providers of GP helplines are struggling to find staff to scale up their operations and there is a strong risk that policyholders find the experience less than efficient if they cannot access what they need in a timely fashion, increasing the propensity to lapse.

2. Market and counterparty risk

For those medical insurers with significant equity exposure, the impact of COVID-19 has already been significant due to turmoil in the financial markets – which have seen falls similar to the 1 in 200 Standard Formula stresses. Some insurers also have high levels of currency risk and therefore are exposed to high levels of volatility in the foreign exchange markets. For those markets with heavy levels of reinsurance, counterparty default risk is a potential issue; even without a default, a downgrade of credit rating can put pressure on Solvency Capital Requirement (SCR) coverage as credit rating drives Standard Formula capital requirements for reinsurance counterparties. Similarly, capital requirements related to deposits, corporate bonds and cash are also driven by credit ratings and hence, could also spike if a lot of downgrades were to occur.

Government interventions vary significantly by country and the stringency of any lockdown provisions will inform both the period of mitigation required and the macro-economic factors which will dictate the speed and pace of market recovery.

3. Operational risks

The range of responses by medical insurers to operational issues caused by lockdowns has been wide. Some insurers have managed to get the vast majority of their call centre and back office staff working from home within a couple of days and have robust business continuity plans in case of high staff sickness. Others are still struggling to get remote working up and running for a large majority of administrative staff. Some insurers, to their surprise, have found increased efficiency and productivity from having teams working from home, while others have found the transition far less smooth. Some have speculated that this forced change will be transformative for the industry – both in terms of product and proposition development for policyholders, but also in terms of their own structure and operations. The best-prepared insurers have already updated their risk registers and carried out significant stress-testing of their operational models under this “new normal”. Others appear inadequately prepared to identify and mitigate the new operational risks that arise, including, for example, increased cyber risks due to large numbers of staff working from home as well as the risks associated with empty offices and staff sickness rates.

4. Conclusion

The impacts for specific insurers are very dependent on benefit packages and policy terms and conditions, as well as government responses and macro-economic factors. However, they are not necessarily net negative from an insurance risk perspective and may even provide opportunities as well as risks from an operational risk perspective. There are still significant levels of uncertainty, but a common framework to analyse the issues is useful and allows for a constant updating of the modelling as new information arises.