In the current environment, understanding the demographic profile of your membership has never been more important. Assumptions which once may have been considered immaterial can now have a large impact on the liabilities of a pension scheme.
Member Analytics gives a wealth of information on the scheme membership which can be used to inform scheme specific assumption setting for funding and insurance valuations, accounting standards and transfer values, and is used to improve communications and risk management.
- Setting scheme specific demographic assumptions - provides evidence to inform longevity assumptions and set dependants’ assumptions. Used for scheme funding and insurance valuations, transfer values and company accounting disclosures.
- Analyse vulnerability to COVID-19 and other serious health conditions - where a vulnerability is identified Trustees may wish to add a mortality screening service to ensure data accuracy. The analysis provides information to inform the impact of COVID-19 on long term longevity via the COVID-19 Analytics service.
- Assess financial and digital vulnerability - if some members are considered financially vulnerable Trustees should add the XPS pension scams service to protect members when they transfer and consider the appointment of an IFA to ensure members have access to high quality transfer value advice.
- Understanding how members want Trustees to engage with them – use to develop the most efficient approach to member communication based on evidence of their preferences. The analysis can inform response rates to choices members may be asked to make such as whether to take a transfer value.
How Member Analytics works
XPS use a database provided by CACI which contains a huge array of data for each postcode. The software enables XPS to analyse the characteristics of a group of pension scheme members using postcodes by comparing it to XPS’s pension scheme data pool. The outputs include information on household income, financial behaviours, health and cohabitation rates.
XPS have built analytical tools tailored to our pension scheme clients’ needs that use the CACI analysis to produce scheme specific demographic assumptions. The XPS methodology is market leading in the pensions consultancy space, and the techniques employed are similar to the analysis that bulk annuity reinsurers carry out when they set their longevity assumptions.
A client on a journey to securing benefits with an insurer used member analytics to refine its demographic assumptions to calculate a more accurate insurance premium. This included an analysis of the proportion of members’ with dependants and their age.
The member analytics indicated that members had less dependants than assumed and, when also allowing for the refinement of the initial addition parameter, indicated that the prudence within these assumptions was nearly 5% of the total liability.
Dependants’ data was collected from the members, with responses accounting for 75% of the liability, and the proportion with dependants was accurate to within 1%. The Trustees were able to use the analysis as evidence to refine the longevity and dependants’ assumptions (for those members who did not respond.).