Overview
Governance
Keeping us on target
FutureWise has a structured, multi-layered governance framework built in, to ensure the investment strategy remains aligned to its long-term objectives and is continuously delivering for members. It includes independent reviewers and peer benchmarking.
FutureWise brings our best investment philosophy to all our default members through a target dated fund strategy, built and maintained on a strong governance framework. Whilst many peer strategies believe members will choose an annuity or take cash at retirement, our experience shows this doesn’t reflect how most members behave - and may not deliver the best outcomes. Find out more in our Retirement Choices paper.
Multi-Layered Governance Structure
Governance in practice
Watch our latest quarter governance update below. To access our quarterly governance library, please click here.
A single default approach
Our belief in having one default investment solution is embedded in the following
Flexibility
Members want flexibility to adjust retirement timing and access options based on pot size and cost. This does not require multiple defaults, a single, well-designed strategy can preserve flexibility and remain outcome-agnostic, avoiding unnecessary complexity.
Reactivity
Members often respond to shortterm pot losses, even when their retirement income is improving. In 2022, many saw their pot fall and switched to cash too early, despite rising annuity rates strengthening their income outlook. Multiple defaults create more points where this behaviour can occur, increasing the chance of reactive, poorly timed switches. A single default reduces this risk by keeping members in a consistent, outcome focused strategy.
Self-selection
Engaged members overwhelmingly selfselect investments, while alternative defaults see minimal use. Maintaining multiple defaults for such limited takeup is inefficient and can weaken outcomes, a point reinforced by our proprietary modelling. A single, robust default simplifies governance, reduces cost and complexity, and better aligns with actual member behaviour.