Globally recognised expert in applied decision science, behavioural finance, and financial wellbeing, as well as a specialist in both the theory and practice of risk profiling. He started the banking world’s first behavioural finance team as Head of Behavioural-Quant Finance at Barclays, which he built and led for a decade from 2006.
Serendipity, mainly. In 2001 I had been working as a management consultant doing geeky quant/risk stuff in financial services but had decided to return to academia to attempt my PhD. The original plan was to focus on a topic bridging Economics and Philosophy, which was my academic background to that point: the philosophy of rationality. As I read more widely to focus on a more specific topic I stumbled on the field of behavioural economics. I had no previous background in psychology, but was drawn to the combination of economics, philosophy, maths and psychology … but also to the blend of both theory and practice, and of empirical data and abstract thinking. So I plunged into behavioural decision science instead – though from within an economics faculty, where at the time behavioural econ was definitely considered to be the lunatic fringe.
Well, on the practical side I suppose it was being able to start and build the banking world's first dedicated behavioural finance team – I had already done some commercial consulting focussed on applied decision science, but was given the wonderful opportunity in 2006 to found a permanent behavioural team at Barclays at a time when the field was still relatively young outside academia. I don't think anyone really knew what a behavioural finance team was going to do, but this was pre-crisis and we were given a lot of room to experiment in the first couple of years. Then after the financial crisis it became clear to everyone that human emotions were at the centre of almost everything, and behavioural economics shot up in prominence.
On a more theoretical note, I have always enjoyed the intersection between descriptive behavioural science and normative/quantitative decision theory – how do we combine observations of how people do behave with models of how they should behave. In this regard I'm proud of contributions I've made to rework modern portfolio theory to ground it in behavioural foundations, retaining the best of each. Behavioural economics should not be seen in opposition to classical theory, but rather as a generalisation of the powerful, yet limited, traditional decision models … throwing out only the bathwater, not the baby.
It is easy to imagine I could have just remained in management consultancy; or perhaps become an academic philosopher. The reality is I have no idea … I have always pursued whatever seemed most interesting to me at the time, and have always had an interest in multiple disciplines. I'm fairly sure that the specific things I have focussed on have been largely an accident of specific circumstances outside my control. I could quite easily have instead pursued early fascinations with ecology, maths, or music.
Most stringently I strive to practice what I preach as completely as possible in managing my own finances and investing. This wasn't always the case as I used to approach the field much more academically. But in the extreme behavioural stress of the financial crisis of late 2008 I realised that I was blithely telling investors that there was never a better time to take risk, but didn't really have any skin in the game myself. It felt somewhat disingenuous so, both because I believed it to be right, and because I felt I couldn't recommend others do what I wasn't doing myself, I threw every penny I could scrape into the markets (in as sensible way as was possible in those times). I didn't have access to much, and I made a lot of mistakes, but applying the theory to myself gave an unparalleled opportunity to learn.
I've been much less effective in applying behavioural science outside of my financial decisions … diet, exercise and health for example…
Curiosity. It's a field that requires constant juggling between disciplines, and there is always something that other fields can teach you, so willingness to step outside of your zone of comfort is important.
At the same time I think that taking the time to really understand the underlying decision theory, though often dauntingly technical and mathematical, is too often glossed over in favour of glib lists of “biases”. Digging deep leads to a depth of understanding that isn't easily found in learning to recite a list of biases.
I think we'll see much more focus on prescription (designing tools and approaches to help people make better decision) rather than just building an academic description of how they do behave. In both, we'll see ever more focus on understanding individual differences, rather than average effects – how do specific people differ in their behavioural and decision making, and how do we use a combination of robust profiling and data analytics to understand and assist each person in making better decisions.
I also believe we need to see much more focus on systems thinking and behaviour in complex environments. A (necessary) feature of much academic study, and the vast majority of practical applications, is to isolate decisions to where individual influences and effects can be understood and nudged, but this tends to narrow the focus on a single decision node and simple problems. Real world decisions don't happen in isolation and I think we will increasing focus on understanding decision making in complex systems, and helping people to navigate the irreducible complexity of their lives.
For example, behavioural design of a savings account to encourage savings into that account can be extremely effective … but without considering the individual's whole financial system we can't say whether this increased savings is actually beneficial. Where has the money been taken from? What alternative use might have been better? Has the increased savings balance in this isolated account contributed to overall financial wellbeing? Or set up bigger problems elsewhere? These are questions that require holistic, systems-based thinking, something which most applications of current behavioural science are quite weak on. (This is also one reason why the quasi-religious focus on randomised control trials as the “gold-standard” of behavioural success are misplaced … they seldom consider the knock-on effects on people outside of the isolated intervention in question).
I'd like to see some of those who have real depth of decision theoretic understanding pervading their practical and empirical work: Colin Camerer, Drazen Prelec, Peter Wakker, Daniel Read, Nick Chater are a few who come to mind.
Also any of the philosophers of rationality who have thought very deeply about many of the issues that behavioural science is now shining an empirical light on. If we are to move beyond mere description of behaviour, to improving decisions, then the descriptions aren't enough, we need sophisticated interpretations of when to encourage certain behaviours and discourage others. What is it good, right, or rational to pursue?
These are philosophical questions, and there is a huge literature on the philosophy of rationality and decisions that is often sadly neglected by behavioural science practitioners. Jon Elster's dauntingly thorough work on the nature of self-control, for example, has had a very big influence on me.
In a similar multidisciplinary vein, Judea Pearl's work on causality has deep implications for behavioural science.
Originally published by Money on the Mind on 13/4/2020.
This is the fourth post in a series giving our response to the FCA’s Call for Input on how to apply behavioural finance to help people make engaged investment choices more comfortably and confidently, and what role regulations can play in helping that to happen.Read More
This is the fifth post in a series giving our response to the FCA’s Call for Input on how to apply behavioural finance to help people make engaged investment choices more comfortably and confidently, and what role regulations can play in helping that to happen.Read More