Back in the 19th Century, the founding fathers of the then new discipline of psychometrics spent much of their time attempting to measure intelligence, developing Darwin’s theory that those individuals who can adapt will be more likely to survive. More than a century later that same strand of psychometrics has developed into the theory behind sophisticated tools that help advisers ensure clients invest in portfolios of assets that match their risk appetite as closely as possible.
Attitude to risk (ATR) profiling tools has only really been around for the last couple of decades. But even within the relatively short time that they have been in existence we have seen the way they are designed and used evolve considerably. This evolution has been fuelled by the growing amount of data upon which to base the theory behind these tools, regulatory and market changes and the financial services industry’s attitude to and acceptance of them.
When psychometric risk-profiling questionnaires were first developed they relied heavily on graphs, numbers and percentages. This number-heavy approach may have seemed logical to people working in the financial services industry at the time, but these early tools were deemed to be failing to communicate to people in language that they understood. The feedback from the regulator was clear: lots of people simply do not understand percentages and many find it hard to extract anything meaningful from looking at a graph.
This customer-centric emphasis led to a substantial overhaul of the format of risk-profiling tools, toning down the maths textbook-style examples and making them more user-friendly.
Changes to questionnaires have also come about as a result of the growing body of knowledge around how humans engage with and experience risk, both as a result of research based on user feedback and on the ongoing development of the psychology behind the questionnaires. Our very own expert psychologist is regularly weaving the latest academic research into the fabric of our tools.
One example of this is shown in the way an ambiguous middle answer in a scale can be seen differently by different people. Whilst “neither agree nor disagree” is designed to be used in context as the middle of a scale, it could also be potentially interpreted as having no opinion at all. Subtle changes in the wording used can have unintended consequences for the unwary and testing the questions is important to avoid bias.
