A Defined Contribution pension scheme places the investment risk with the member. The member’s retirement income is determined by how much was contributed, how those contributions were invested, and what the accumulated fund provides at retirement. In principle, each member chooses their own investment strategy. In practice, most do not. The proportion of members invested in the scheme default — the fund they are placed in when they do not make an active choice — consistently runs above 80 percent in most workplace DC schemes. The default strategy is not the fallback option. It is the primary investment decision for the overwhelming majority of members.
The trustee board that designs or selects the default is making an investment decision on behalf of members who will never review it, never understand its implications, and will experience its outcomes only at retirement when it is too late to change them. The stakes are not abstract. A default strategy that generates a 40 percent replacement rate — the proportion of pre-retirement income the fund provides — leaves members materially short of the 60 to 70 percent typically associated with an adequate retirement income. At scheme scale, that shortfall affects thousands of members simultaneously.
Where the default design decision breaks down
Generic lifecycle investment theory provides the conceptual basis for most DC defaults. In the growth phase, members invest in higher-return, higher-volatility assets. As they approach retirement, the portfolio de-risks into lower-volatility assets and cash. The glidepath — the transition between the growth and consolidation phases — is calibrated to protect the member’s accumulated fund in the years immediately before retirement.
The problem is the assumptions this theory embeds. It assumes a normal distribution of retirement ages, consistent salary growth, uniform member needs at retirement, and broadly similar financial circumstances across the membership. Most scheme memberships do not match these assumptions. A scheme whose membership is concentrated in a sector with high income volatility and early voluntary exit has a different demographic profile from a professional services scheme with long service and late retirement. A default calibrated to the first profile will systematically underperform for the second membership, and vice versa.
The retirement pathway assumption creates a second dimension of mismatch. Automatic enrolment into drawdown, annuity purchase, or cash at retirement each require different de-risking glidepaths. A default designed around annuity purchase de-risks into bonds. A default designed around drawdown maintains growth asset exposure closer to retirement. For a scheme whose members predominantly take cash or drawdown, a bond-focused de-risking glidepath actively reduces expected retirement income by transitioning out of growth assets too early.
What scheme-specific outcome modelling adds
Member outcome modelling calibrated to the actual membership profile produces a default strategy assessment and design that reflects the scheme’s specific circumstances rather than industry averages. The model inputs are the scheme’s own data: age distribution, salary levels and growth patterns, contribution rates, typical retirement ages, and where observable, likely retirement choices. Projected against a range of investment return scenarios, the model identifies the default configuration that maximises the probability of adequate retirement income for the specific membership.
The Value for Money framework that The Pensions Regulator requires all Defined Contribution schemes to assess includes member outcomes as a primary dimension. Projected replacement rate — the expected proportion of pre-retirement salary the default fund will provide — is the measure trustees must be able to evidence. A trustee board that can demonstrate that the default strategy was designed against the scheme’s actual member outcome data, tested across a range of scenarios, and reviewed against the Regulator’s adequacy benchmarks has met the governance standard. One that cannot demonstrate the basis for its default design is exposed.
The technology dimension
Default strategy outcome modelling requires processing the full member dataset against actuarial projection models and investment scenario generators. For administrators running their member data and benefit calculation infrastructure on IBM Z, deploying outcome modelling via IBM Machine Learning for z/OS enables projection of individual member outcomes across the full membership population, using the complete contribution and demographic data held on the same platform. The model outputs — projected replacement rates, adequacy gap distribution, scenario sensitivity — are available to the trustee board through their governance reporting process.
What success looks like
The primary metrics are average projected replacement rate across the membership, proportion of members projected to achieve adequate retirement income, default strategy adequacy score under The Pensions Regulator’s Value for Money framework, and actual retirement income outcomes for members reaching retirement on the default. The last metric requires a longer measurement window but is the only direct evidence of whether the default strategy is delivering for the members it was designed to serve.
