Mercer has launched a new tool that uses artificial intelligence to help defined benefit pension schemes predict the outcomes of member option exercises.
It is thought this is the first AI-powered tool in this space.Using anonymised data from completed member option exercises and the scheme’s own data, the machine learning algorithm determines the probability of a member accepting a tailored offer.
This new data driven approach helps pension schemes and sponsors better manage risk, and plan projects that have optimum member offer structures.
Mercer’s new AI tool has identified several factors impacting a member’s decision on whether to transfer out of their DB scheme. Age is a key factor, with those who are aged 55 plus more likely to accept an offer.
Mercert’s statistics show thosein this age group are on average 18-20 per cent more likely to accept an offer than younger members.
Other issues include a member’s place of residence, with overseas members 10 per cent more likely to accept a transfer value than those based in the UK.
It also found that the time of year the offer is presented can impact a member’s decision, with more responding to offers in spring.
Mercer’s tool will continue to evolve as data from more completed exercises are added.
Mercer partner and head of risk transfer Andrew Ward says: “Since the introduction of pensions freedoms, transfer options have played an increasingly important role in pension schemes’ risk management.
“With gilt yields at historic lows, members may be balancing taking higher transfer values against the backdrop of uncertainty caused by Brexit. However, while market conditions can influence take up, the decision to transfer is more likely to be driven by personal circumstances.”
He adds: “By using AI and data driven insights, we can help schemes predict the chance of each individual member accepting a particular offer.
“This information will help schemes create offers that are tailored to the scheme’s specific characteristics, ensuring that members are presented with a range of pension options to consider. It also ensures that member options projects are utilised in the best possible way to help schemes achieve their ultimate long-term funding target.
“It is important that members also seek financial advice to ensure they are able to make an informed choice that will meet their retirement needs.”
Mercer’s AI tool draws on anonymised data from over 20,000 member transactions who have been through an ETV exercise. With this considerable amount of data, Mercer can support clients make better choices and help solve issues with DB pension arrangements.