The global pension industry is increasingly tapping big data to learn how fund members behave, and then applying these insights to improve product design.
Big data is a term that refers to a very large collection of data-sets from multiple sources. Companies are now using computers to analyse this information for patterns or trends.
Northern Trust Asset Management’s US-based global head of retirement solutions, Sabrina Bailey, shared some of what the firm learned by examining large data sets on switching investment options during last month’s market correction.
“[The beginning of February brought] the first week of a significant market downturn since the GFC and it gave us the opportunity to look at the way younger members actually behave, compared with the risks they say they want to take,” Bailey said.
Northern Trust analysed the switching behaviour of members in lifecycle-style funds across 50 of its largest US pension clients.
Bailey said the results showed younger members were likely to have reacted to the market shock by switching to a more conservative investment option.
Younger people with smaller balances were, most likely, among those investors who moved into cash in early February and have not moved back, Bailey said, “which means they locked in all of those losses and haven’t experienced any of the recovery”.
She said this knowledge has important implications for product design. Traditional thinking goes that younger people should have a higher allocation to risk assets, such as shares, because they have more time to recover from any falls. Bailey argued that this notion is flawed because it fails to take into account behavioural bias, which makes people with small account balances likely to worry more about losing their money, making them more prone to switch to cash in response to market volatility.
“We argue you [pension and super funds] should potentially consider taking less risk for younger participants and increasing that risk for a while over time,” she said. “Having less in risk assets, such as equities, at the beginning of a career, has a very minimal impact on outcomes over the long term because account balances are so low that risk assets, even in a great environment, are not adding that much to the overall dollar amount of their retirement balance.”
Bailey suggested super funds consider starting younger members in a more conservative investment option, with a glide path to a higher allocation to risk assets as they approach 45 years of age.
“That’s when individuals have been shown to have both the appetite and capacity for risk; you capitalise on those growth assets when they can add the most to retirement outcomes for members,” Bailey said.
She added that it also makes sense for funds to default their members back into more conservative investment options as they approach the age of 65, to manage sequencing risk.
Bailey said another approach worth thinking about is applying factor-based investment strategies to manage risk profiles as fund members age.
“You can have equity portfolios that have less downside market risk [not more] upside opportunities, for younger members, and really leverage those more at the front end and back end of someone’s career and investment in super, rather than throughout their entire life.”
Bailey made her comments on Thursday, March 15, at the Conference of Major Superannuation Funds 2018, being held in Brisbane, March 14-16. She spoke during a panel session titled, “How can big data inform investment product design?”.
She shared the stage with JPMorgan Asset Management’s US-based portfolio manager and head of retirement solutions, Anne Lester, and Schroders’ UK-based global head of defined contribution and retirement, Lesley-Ann Morgan, who also shared how insights gleaned from big-data analysis are challenging their assumptions about retirement product design.
READ MORE: All the coverage from CMSF 2018
