XPS launches Covid-19 vulnerability analysis tool

James Phillips reports

A scheme vulnerability analysis tool aiming to allow pension schemes to understand the likely impact of Covid-19 on their members’ life expectancy has been launched by XPS Pension Group.

With around 53,000 deaths since the start of the pandemic expected to list Covid-19 as the reason, XPS’ tool uses a database compiled from public sources to categories members by postcode and provide assumptions on vulnerability to Covid-19, as well as the associated scam risk.

The database already provided a way to analyse relative wealth, health and mortality, financial dependents and age difference, and methods to engage with members. XPS said it allows trustees to better understand their demographic characteristics and therefore their scheme liabilities.

The idea of the tool is to quantify how vulnerable a scheme’s members are to contracting Covid-19, based on information such as underlying health conditions and domiciles.

Head of member profiling Matt Plail explained: “By looking at the postcode analysis, we’re able to tell if members are in care homes or hospitals and then project the probability that they’re likely to have particular diseases or underlying health conditions. Based on that information, we can tell if a scheme has a vulnerability to Covid-19.”

Designed as an integrated risk management tool, the vulnerability analysis also allows XPS to put the profiling results into a modeller and then look at scenarios. One such example is the impact on the NHS and how many years it might take to recover.

“The idea of the service is to identify vulnerability, including financial and digital vulnerability,” Plail said.

This can allow schemes to identify the risk of scams to members, and then put in place extra protections and communications, where necessary.

“It’s a tool that’s very easy to use. It doesn’t require much data, but it gives schemes an immediate idea of whether they are vulnerable to this particular disease.”

The tool has previously been used to help schemes understand their member population, particularly in terms of age gaps between dependants and whether they are married or not. General population statistics as often used but these can be incorrect for specific schemes.

“I’m finding that 90% of our schemes are assuming members are married at retirement, but it’s quite a lot lower,” Plail continues. “Also, men are always assumed as three years older than women, but when we do the analysis, while that may be true for the pensioner population, for a younger population that is a lot closer. Men seem to be cohabiting or marrying women of a similar age.

“What that does for a male-dominated scheme is reduce liabilities, because you potentially won’t be paying for as long. Combining those two parts can really bring down liabilities by around 5%. If you apply that to a deficit, you get a gearing effect and that can make quite a big difference.”