Articles - Smarter than your average bear


Yogi Bear! The genius of Jellystone Park was, as we all know, smarter than your average bear. I wonder what does your average bear look like? The other bears that I know with any sense of familiarity are Winnie-the-Pooh, Baloo and Goldielocks’ three porridge eating friends. Certainly these bears are all different but I’m not sure what the average is. Perhaps a porridge eating, red jacket and green tie-wearing, John-Wayne speaking singer of songs!

 By Duncan Robertson, Marketing Director at Aegon Ireland
 So what does it mean to be ‘average’?
 Let’s think about our customers. I think we’d find it hard to find an average customer. Think about how they vary? Women, men, young, old, family or singleton, all have varying personalities that make them distinct. Yet despite this diversity, when helping clients plan for retirement, too often as an industry we rely on solutions that are driven by underlying averages.
  
 Let’s take life expectancy for instance. That’s an average. If you’re a female aged 65 your life expectancy is to age 91*. Of course there’s a real danger that if we quote this age then females will start planning their retirement income pattern around the expectation of dying at age 91. But of course half of females will reach age 91 and having done so these females will then have a life expectancy of a further 6 years. (I don’t want to get too Bayesian on you but does this mean that if you expect to live to age 91 then you expect to die at age 97? I’m probably in the Yogi Bear camp on this question so I’ll let the academics amongst argue this one.) If a 65 year old female plans her retirement on the premise of dying at age 91 then half of the time she will die sooner and half of the time she will die later than expected (and less than 0.03% of the time she will die right on time!)
  
 For this reason, binary retirement solutions based on averages are thankfully starting to become a thing of the past.
  
 Traditionally the industry has worked on the assumption of deterministic returns, but this environment is changing. There’s a rapidly growing realisation that in many circumstances “average” deterministic returns just don’t tell customers the full story and some form of stochastic analysis is required. For a long time talk of stochastic modelling was confined to what are often termed “complex” products. However increasingly I’m seeing people realise that for decumulation products the sequence of returns is vitally important for even the simplest income drawdown product. As pension funds decumulate the outcome for the customer is heavily dependent on the performance in the initial few years of decumulation. This should be no surprise as the fund weighted average of the performance is heavily weighted to the initial years when the fund is at its largest. However, it’s often only by demonstrating the impact of different sequences of returns that this messages starts to be better understood by customers and advisers.
  
 Of course the challenge with stochastic analysis is in presenting the results in an understandable fashion. However, technology is helping significantly with insurers and advisers using smart dynamic tools to get the message across.
  
 I’ll leave the last word to Yogi and his side-kick Boo-Boo.
  
 Yogi Bear: Boo Boo, you've tried to stop my brilliant ideas with common sense a thousand times. Has it ever worked?
 Boo Boo: No.
 Yogi Bear: Then... let's go-go-go!
  
 *Aegon CMI Personal Pensioners, females, vested _PPFV00 ultimate. www.actuaries.org.uk Publication date 01 August 2006

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