OPINION: Applying big data in retirement funding
What if someone told you that compared to ‘the Joneses’, you’re saving about 20% less for retirement each month.
Chances are, that information would be impactful. You’d probably feel the necessity to relook your money management to try and put in a little bit more each month. That’s the potential power of big data in the retirement funding space to catalyse meaningful interventions at the right time using impactful insights.
These kinds of data driven interventions are essential as the Sanlam Benchmark Research shows just most employed South Africans will not be able to maintain their standard of living into retirement.
Johan Prinsloo, CEO of Retirement Fund Administration at Sanlam, says it’s a moot point that members don’t save enough. “We also know that HR practitioners and retirement fund administrators accumulate vast amounts of data. We need to start responsibly using this to see who is at risk and how we can intelligently intervene. Like for like comparisons between people in similar profile groups could be a mechanism to influence individuals to review their choices. Having a peer-based benchmark allows individuals to assess whether they are themselves at risk and to implement appropriate course correction.”
Prinsloo says that Sanlam Corporate is pioneering a first-of-its-kind big data project focused on how to address ‘retirement resilience’ by improving Net Replacement Ratio outcomes. “Customer expectations have shifted. Our clients expect us to offer them a bionic user experience that integrates the best of machine learning with considered human interaction to optimise member outcomes. That’s exactly what we’re aiming to do by presenting insights in formats employers and trustees can easily understand and implement.”
Motivating through competitive data is one such potential action. J.V. Wood – referenced in this research paper – says that people “tend to adopt the performance standards of others who are similar regarding surrounding dimensions”. This means we can be inspired by comparing ourselves to others, but only if we believe we can attain similar success. That’s the crucial bit. Big data can help us identify those who may benefit from a well-timed intervention. But the right guidance must accompany this so people feel like they can get back on track.
Prinsloo says, “If you’re told you’re one of the 1% of employees in your company saving successfully, that may motivate you to do even more. If you are suddenly aware you’re in the bottom percentage of savers, that’s probably also going to change your behaviour. There’s a powerful message in comparing the individual to the collective. But, as an industry, we need to ensure this is done responsibly, in a way that doesn’t further demotivate people and bring about more apathy.”
He adds that big data will allow for increasingly detailed information on all factors influencing retirement resilience, including the impact of stress, indebtedness, divorce and so forth. He says that, crucially, fund administrators need to be training in-house teams of data scientists and analysts to be able to extrapolate data. Additionally, cybersecurity must be top of mind to ensure data is protected.
“Ideally, in the future, members will trust us and give us permission to collaborate across industries to responsibly share data in order to build more complete pictures. To give members the best possible guidance, we need a holistic understanding of their financial lives.”
Prinsloo says interventions are required throughout an individual’s life. “We need to make sure people know they have access to Retirement Benefits Counselling and other benefits. Big data will assist us to enable employers not to have a ‘shotgun’ approach with information, but to be more targeted with communications. “For instance, one insight that emerged from Sanlam’s project was that members receive salary increases below inflation resulting in them not increasing contribution rates adequately, which means they contribute less to their retirement funds in real terms.”
He concludes, “To start integrating big data, fund administrators or trustees need to understand the reality of the 4th Industrial Revolution on this data. It’s a journey with many factors to consider but you have to start somewhere.”