Defined benefit (DB) pension schemes will be able to predict the outcome of member options exercises using artificial intelligence (AI), says Mercer.
The consultancy giant has launched an AI tool that contains a machine-learning algorithm from anonymised data from completed member options exercises, alongside the scheme's own data.
The tool then determines the probability of a member accepting a tailored offer, which Mercer said ensures pension schemes and sponsors can manage risk more accurately.
It can also help schemes to build a more accurate picture of member behaviour, Mercer added.
Decisions such as whether or not to transfer out of a DB scheme can also be analysed by the algorithm. Mercer said this has revealed several trends that could assist in better prediction of other members future choices; age and residence are noted as key factors, along with time of year.
Mercer partner and head of risk transfer Andrew Ward said: "We can now help schemes predict the chance of each individual member accepting a particular offer [and] this information will help schemes create offers tailored to the scheme's specific characteristics.
"It also ensures that member options projects are utilised in the best possible way to help schemes achieve their ultimate long-term funding target."