Recently I was invited to attend a focus group to discuss a mutual fund company’s idea for a new retirement product. During the discussion, it dawned on me that advisors think about retirement risk rather differently than their clients. To understand why this occurs requires a more precise understanding of retirement risk.

For many Canadians moving into retirement, the focus shifts from concern about portfolio growth to concern about sustainable income. We are all familiar with talking about growth of assets: performance is measured by investment return and risk is measured by the portfolio volatility. High returns are better than low returns and low volatility is better than high volatility.

For retirees, performance measures relate to income: more income is better than less income and the risk is the risk of running out of money.

A common way of assessing the risk of running out of money is to calculate ruin probabilities. The ruin probability for a portfolio is the chance that the client will run out of money before they die. The retirement product under review by the focus group estimated ruin probabilities by running multiple simulations with each simulation having a different sequence of market returns during retirement.

For example, a client with $1 million of investment capital at age 65 requires an annual withdrawal rate of $40,000. We might say to that client “we have designed your portfolio so that there is a 10% chance of running out of money”, so the ruin probability is 10%. (In reality, smart advisors much prefer to express the 10% chance of running out of money as the more positive sounding 90% chance of success, but there is no difference). Calculating ruin probabilities is greatly preferable to ignoring them, which is all too common in financial projections that ignore portfolio volatility and use only average returns. The consequence is a serious overestimation of the income that a portfolio can sustain.

However, ruin probabilities are not a complete measure of risk because they do not account for the cost of failure. Auto insurance offers an analogy. The cost of auto insurance depends not only on how often the insurance company thinks you will have an accident (ruin probability) but also the cost of each accident, based on the price of the car you drive. Similarly, protecting retirement income against loss requires considering the cost, not just the frequency, of market downturns.

Which brings us to the issue posed at the start: that ruin probabilities mean different things to the advisor than to the client. The advisor’s perspective, as became clear from the focus group, is that the advisor sees a pool of clients, many in different stages of retirement. If 10% run out of money then the impact to the advisor is a downturn in revenue that is unwelcome but tolerable. In statistical terms, the advisor takes an ensemble average and pools the risk to his business: the consequence of failure is low.

The client has a different perspective: risk cannot be pooled – her money either lasts or it doesn’t and the advisor’s other clients aren’t going to bail her out. For the client, the consequence of failure is high.

With this in mind, if your advisor smiles from across his desk, as he reassures you that your retirement plan has a 90% chance of success, imagine him as a flight attendant welcoming you aboard your next flight with a 90% chance of a safe landing and seeing him standing on the runway as you depart.