Lying – it’s something that all humans do. Most of the lies we tell are small and harmless. But deceptive behaviour in the investment industry lowers trust and increases costs and complexity.

We are deceptive for many reasons and one of them is that we can get away with it. This is because, despite what we might believe, most of us are pretty terrible at spotting lying – including highly experienced financial analysts.

But what would happen if we all had access to AI-powered technology on our phones that could spot deception with a high degree of accuracy? Would that change how the industry behaves?

This is no idle speculation – in this episode of Decision Nerds, we explore research that suggests that AI is significantly better at spotting lying than humans. And as we all know, AI has a habit of surprising us by appearing in the wild far faster than we might expect.

How would this technology impact the investment industry? We discuss:

𝙏𝙝𝙚 𝙢𝙤𝙩𝙞𝙫𝙖𝙩𝙞𝙤𝙣 𝙛𝙤𝙧 𝙙𝙚𝙘𝙚𝙥𝙩𝙞𝙤𝙣 𝙞𝙣 𝙩𝙝𝙚 𝙞𝙣𝙙𝙪𝙨𝙩𝙧𝙮 – the entirely logical reasons that we don’t always tell the truth

𝘿𝙞𝙛𝙛𝙚𝙧𝙚𝙣𝙩 𝙠𝙞𝙣𝙙𝙨 𝙤𝙛 𝙙𝙚𝙘𝙚𝙥𝙩𝙞𝙤𝙣 𝙖𝙣𝙙 𝙩𝙝𝙚𝙞𝙧 𝙧𝙚𝙡𝙖𝙩𝙞𝙫𝙚 𝙞𝙢𝙥𝙖𝙘𝙩𝙨 – what are the traps that managers fall into and why

𝙅𝙪𝙨𝙩 𝙝𝙤𝙬 𝙢𝙪𝙘𝙝 𝙗𝙚𝙩𝙩𝙚𝙧 𝙞𝙨 𝘼𝙄? – the results might surprise you

𝙒𝙤𝙪𝙡𝙙 𝙖 𝙩𝙧𝙪𝙩𝙝 𝙢𝙖𝙘𝙝𝙞𝙣𝙚 𝙙𝙚𝙨𝙩𝙧𝙤𝙮 𝙩𝙝𝙚 𝙞𝙣𝙙𝙪𝙨𝙩𝙧𝙮 𝙤𝙧 𝙢𝙖𝙠𝙚 𝙞𝙩 𝙗𝙚𝙩𝙩𝙚𝙧? – our take on ‘creative destruction’

𝙏𝙝𝙚𝙧𝙚’𝙨 𝙣𝙤 𝙩𝙧𝙪𝙩𝙝 𝙢𝙖𝙘𝙝𝙞𝙣𝙚 𝙮𝙚𝙩 - we discuss a few better questions that we can use today.

Affectiva facial recognition demo
Paper on analysts' ability to spot CEO deception
Paper on AI's ability to spot CEO deception
Lying on CVs

𝗛𝗼𝘄 𝗺𝘂𝗰𝗵 𝘁𝗶𝗺𝗲 𝗱𝗼 𝘆𝗼𝘂 𝗴𝗶𝘃𝗲 𝗮𝗻 𝘂𝗻𝗱𝗲𝗿𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁 𝗺𝗮𝗻𝗮𝗴𝗲𝗿?

1. Hire a manager after a period of strong performance.

2. Watch in horror as you don’t experience that outcome, maybe the opposite.

3. Spend a huge amount of time and emotional labour deciding on whether your initial thesis was wrong, something has changed at the manager, or with market dynamics.

4. After sucking up a huge amount of governance time, decide to sack the manager.

5. Rinse and repeat with potentially similar outcomes.

Now that might not be you, but it is a story that plays out regularly.

Experiencing underperformance is one of the unavoidable realities of hiring an active manager. And it’s painful for everyone; clients, managers and advisers. And badly managed pain creates some predictably bad outcomes for all parties.

One important and manageable issue is time horizon mismatch. And this is what and I explore in the latest episode of Decision Nerds. We discuss

𝗪𝗵𝘆 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁 𝗲𝗱𝗴𝗲 𝗶𝘀 𝗻𝗼𝘁 𝗲𝗻𝗼𝘂𝗴𝗵 – managers need an appropriate amount of time to let their edge play out. It may be longer than you think.

𝗧𝗵𝗲 𝗕𝘂𝘅𝘁𝗼𝗻 𝗜𝗻𝗱𝗲𝘅 – a simple way of articulating time frames that would help everyone.

𝗘𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝗵𝗮𝘀 𝗮 𝗽𝗹𝗮𝗻 𝘂𝗻𝘁𝗶𝗹 𝘁𝗵𝗲𝘆 𝗮𝗿𝗲 𝗵𝗶𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗳𝗮𝗰𝗲 – we posit that most people’s ability to predict how they will deal with the pressure of underperformance won’t reflect reality when things get tough.

We talk about the distinct behavioural pressures facing clients, advisers and managers and what they might consider doing to make things easier. A couple of takeaways if you don’t have time to listen.

𝗖𝗹𝗶𝗲𝗻𝘁𝘀 - what is your real capacity for tolerating underperformance, how do you know this?

𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀 - have a clear view of the timeframe your results should be judged over. Whilst this a tough problem, if you don’t have a view, one will be forced on you.

𝗔𝗱𝘃𝗶𝘀𝗲𝗿𝘀 - is your role to be a behavioural bulwark and help clients through this period, or just keep them happy? They are not always the same thing.

More information on the Buxton Index is here: https://lnkd.in/eHXDfkfe

Thinking and talking about failure can be tough, especially when it’s us who’s failing. But it’s important for us as individuals and investment teams to find a way to do this in an effective manner that allows us to both learn and evolve. In this episode of Decisions Nerds…

- Joe pits his inner Brian Blessed against an AI auto-editor

- We examine Joe’s framework for thinking about errors around investment beliefs, processes and outcomes.

- We then think about this in the context of broader research that thinks about different typologies of errors; basic, complex and intelligent.

- We then discuss the practical steps that can make life easier.