During the last 12 months, the EY Investment Advisory team has helped 15 insurance companies and 30 asset managers in the UK alone, and has grown its teams across Europe, the US and Asia. As insurers invest more across borders and learn from each other's investment habits, this global footprint has proven very helpful to the EY team and its clients.
EY's work has varied from traditional actuarial work on capital models and regulatory updates, to helping firms enter new asset classes, hedging the Solvency II balance sheet and optimising matching adjustment (MA) portfolios.
Among the highlights have been helping three more firms gain MA approval for their equity release mortgages; the re-optimisation of a book of new student loans for the market; and helping to place the largest offshore windfarm with insurance clients, generating innovative inflation-linked assets in the process.
"We've also been helping insurers improve their operating models to make them more commercial and more successful. It's been an interesting year," says Gareth Mee, an EY partner and leader of the team.
The search for yield in the low rate environment and the need to optimise balance sheets is a perennial challenge, none more so than in the bulk purchase annuity markets where competition among insurers has been fierce. But other sectors are joining in the trend.
"We are doing more work with non-life and with-profits funds than we did 12 months ago. The spotlight on illiquid assets has also expanded from annuity funds to other areas – particularly shareholder funds – which brings a different set of potential asset classes into play, because they tend to be of shorter duration," says Gareth Sutcliffe, investment advisory leader in the UK.
EY has assisted insurers in improving their investment decision-making, "and being slick at understanding the impact of a decision, and whether it forces you to hit a constraint, such as liquidity risk," Sutcliffe says.
In this regard, EY highlights its innovative analytics and visualisation tools which, for example, have dramatically reduced the run time for an MA portfolio analysis from 11 days to just 30 seconds.