Financial planners play a key role in the movement of superannuation fund members between funds, along with retention strategies.
A new predictive analytics tool could improve the way they receive leads by drastically improving the data mining capabilities of super funds.
Many of these face a considerable challenge holding onto members. Funds are having to adapt to new legislation, including Stronger Super, Superstream and new reporting requirements from the Australian Prudential Regulation Authority.
Additionally, increased consumer awareness of, and engagement with super is also increasing the movement between funds.
Identifying better ways to leverage their member data is one way funds are doing this. While traditionally, member information is used to prepare reports of past activity, an algorithmic approach from Empirics enables more predictive analysis.
Industry super fund REST is one of the number of funds that has already implemented Empirics solution.
“We think there is an opportunity for super funds to be better in this space, in engaging the customer experience,” says Empirics chief executive officer Darrell Ludowyke.
Measuring what he terms “a propensity to defect” is an overarching goal, which the software helps achive by pulling together a few key ‘red flags’ from individual members. These include the appointment of a third-party authority, a recent job change, voluntary contributions or member inactivity.
“One of the problems in super is when people change jobs, they often change their super fund too,” Ludowyke says.
“[Super funds] need to be not only reactive, but proactive across various touch points. They need to ask ‘what are we doing that is working, and what are we doing that’s not working?’”
According to Dr David Black, Empirics head of advanced analytics, “We want to tell them why their members behave the way they do, and predict future behavior.
“We’re using existing data to understand member behaviour,” he adds.
With the technology able to be applied within any industry that relies on vast volumes of customer data, Ludowyke says they are also looking to roll it out to other sectors, including life insurance companies.
Asked what the system costs, Ludowyke is unable to provide a figure, with the cost varying widely between individual customers in line with variables such as reporting frequency and breadth. However, he says this includes a one-off licensing fee along with an ongoing charge.
