There’s a natural tendency for all asset managers to report performance as if they were talking to the trustees of a defined benefit pension scheme. Fact sheets, league tables and projections for pensions have been created out of what actuaries consider best practice for institutional investors and it has been assumed that is what is good for DB is good for DC.
But of course, the DC saver has entirely different needs, especially when they get to that stage in life when savings need to be spent to supplement later life income from pensions, paid work and investments. Savers looking to drawdown income from their pension savings are ill-served from the DB style reporting which is what they get.
Faced with “the nastiest hardest decision in finance” – how to make savings last as long as we do, most of us are given plenty of rules of thumb as to what might work, but too little information on how things have worked. There is surprisingly, no commonly agreed way of measuring how a drawdown strategy is doing and – annoyingly – no way for the consumer to judge whether they are doing well or badly.
This will have to change if the consumer duty is to do its job. The consumer duty puts an onus on advisers to assess whether they are delivering value and that means understanding how things have gone both in absolute and relative terms.
So, what is the measure that people can use and how can they or their advisers compare their experience with the common view?
The answer to the first of those two questions is that people’s actual experience is measured by their internal rate of return (IRR). This is based on fund performance, the impact of charges and transition costs and the timing and incidence of drawdowns.
The way this is calculated, is not by using fund performance tables and netting off the costs – that doesn’t work because it doesn’t pick up the impact of the single swinging price, nor out of market, nor the impact of sequencing risk. It is calculated by measuring the net asset value (the size of the pot) with the contribution history (what has been paid and when). When you are saving, what has been paid is paid into the fund, in drawdown, it is paid out of the fund.
But how can you compare this personal performance number, the IRR with what others have got? If there was sufficient data to compare, we could be able to calculate a price track through regression analysis representing the daily price movements implied by the IRRs, but that is one for years ahead.
Right now, the only way to calculate how an IRR compares with the average saver’s IRR , is to calculate the average saver’s IRR with a price track created to represent the average drawdown fund. By notionally investing a drawdown history into such a fund – it is possible to get a comparable “benchmark IRR and by comparing one with another – people can find out how they have done.
Further help can be given by creating an algorithm that turns that comparison into something like a ratio or a score. This takes into account the duration of the drawdown, if people have done well for a long time, that should lead to a high score and vice versa.
Is this practical for a financial advisory practice? The answer is yes. Provided the practice can get hold of a drawdown history and current net asset value, calculating an IRR is simply down to good software. Accessing an appropriate benchmark is a little harder, there is help on the way on this but expect many an argument before one is agreed. Finding an easy way to compare IRR and benchmark IRR is technically challenging but not impossible.
Supplying the calculation mechanism under licence looks like an opportunity for a forward-looking Fintech.