The Black Hole of Green Finance

March 31, 2022
Greg

Greg

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.

The Black Hole of Green Finance

As the ESG industry expands, so does recognition of its darker elements. There are signs of trouble ahead. And it’s likely to be unsuspecting and unsatisfied investors left picking up the tab.

Investor demand for investments with some sort of socially conscious edge is obviously rising. But it is in asking: ‘what is it, exactly, that they want?’ that we start to see difficulties.

The main issues with ESG – from ‘greenwashing’ (promoting the appearance of alignment with ESG objectives, regardless of its reality) to a lack of standardised terminology and governance – are fundamentally linked to suitability: matching investors to the right investments for them.

The right products are not always bought by the right investors. Outright scams aside, investment mistakes tend to be less about objectively poor investments, and more about subjectively unsuitable ones.

As with standard suitability, because of the complex web of data to crunch, and moving parts to assess, appropriate use of tech is at the heart of matching investors with specific social goals and preferences to investments with the best chance of meeting them.

However, in the current ESG environment, the tech is not always used appropriately; it’s often as likely to act as a blindfold than a microscope.

The role of tech

In ESG even more than traditional investing, investors are after a simple solution for their complex preferences. This isn’t impossible. But in the short term it’s easier to sell a simple solution by ignoring the complexity of those preferences.

This is a problem. Because the onus can’t be on investors to figure out when a solution that sounds great works poorly, whatever their incentives for doing so.

The parallel here with traditional suitability is that all investors should have their risk tolerance measured by a questionnaire that’s scientifically valid and reliable. Most questionnaires, however, are nowhere near either.

The tech traps in ESG suitability come from being so caught in the ‘green rush’ that the power of tech is focused on slick sales at the expense of sound solutions.

Three main expressions of this are:

  1. Promotion of ESG in general.
  1. Precision of investor preferences.
  1. Prioritisation in product creation.

Tech can overcome all of these, but it can also ignore or even exacerbate them.

Problem 1: Promotion – Calling something responsible doesn’t mean it is

For want of a standardised menu of meaning, ESG labels on funds are becoming as meaningless as the word ‘natural’ on a food label. Sadly, such labels are often all investors have to go on; and being told to trust everyone is grounds for trusting no one.

There’s a parallel here with standard suitability regulations that can require only that ‘risk tolerance’ be ‘considered’. Which is shorthand for ‘measured somehow’ rather than ‘measured accurately’.

Problem 2: Precision – Profiling preferences doesn’t mean they’re used accurately

Investors, especially when it comes to ESG, have complex recipes of preferences, yet most ‘measures’ allow for no such nuance. This is akin to using risk tolerance as a proxy for all behavioural aspects of financial personality.

ESG preferences are far from one-size-fits-all. This is a job that requires more than asking people how much they love polar bears or hate Monsanto.

At Oxford Risk, we’ve been tracking responsible-investing preferences for years, and it’s clear that investors interested in ESG are trying to meet many different – and often insolubly contradictory – goals.

To take only the most consequential example: some are not only willing, but positively keen to make financial trade-offs for social good. Others are not. Some want to see a big positive impact. Others are happy with simply screening out the worst sinners.

Problem 3: Prioritisation – Being able to count something doesn’t mean it counts

A focus on what can be measured risks products being developed not to help investors meet their social goals, but to game the measurement system.

Focusing products on what is easier to measure, rather than what best meets investors’ goals is akin to measuring ‘risk capacity’ with reference only to current assets simply because they have a known value, even if future assets – even adjusted for uncertainty – can have a much greater influence on the right level of risk to take.

A focus on the easier metrics to hit – even when they match stated preferences – can even work against potentially higher-order preferences. Because individual investor preferences are not a shopping list of independent items, but a recipe of interdependent ingredients.

What evidence of impact do investors want to see?

There’s an argument that until there is a demand for anything more, these problems are overstated.

Yet it’s hard to demand what you do not know exists.

As above, like aspirant healthier eaters being led astray by manipulative use of ‘natural’ on a food label, the onus cannot be on investors to not only look for evidence, but to interrogate it too.

Our research has demonstrated that when it comes to knowing if investments are fulfilling their promises, investors – understandably – seem not to distinguish much between sources of evidence, or between more or less credible evidence.  

We also asked what information investors would find most useful when considering making a sustainable investment – e.g. an independent suitability ranking relative to peers, or against an absolute score, or simply being labelled as ‘sustainable’, and so on.

There was remarkable consistency across all options – investors simply don’t differentiate between them much.

For most it’s not only about the details or the numbers, it’s about emotional comfort that these things do what they claim to do, and trusting in independent parties to verify those claims.

It is the responsibility of those with the relevant technological capabilities to use them to make suitable solutions for investor desires, not merely manipulate the desires to fit the simpler solutions.

How might this be done?

An ESG suitability framework

We need a robust framework that turns a rich human profile full of nuance and uncertainty into a process for suitable portfolio recommendations and ongoing investor management.

The Oxford Risk approach (simplified for the purposes of this article) is as follows:

Step 1 is to ask ‘How much ESG should the investor be encouraged to have in the overall portfolio?’ This is akin in traditional suitability to determining how much risk an investor should be encouraged to have, and a personalised analysis of the barriers to investing further into ESG.  

Step 2 is to ask ‘From how far down the impact spectrum (from a heavy focus on impact, to mere exclusion) should the components be selected?’ This is akin in traditional suitability to a high-level asset allocation.  

Step 3 is instrument selection. There are multiple ways to meet any high-level asset allocation. Key aspects here are investor preferences for the level, the immediacy, and the location of impact they want to have, and whether they would prefer to support more secure causes, or take a punt on more ambitious ‘moonshot’ ones.

Step 4 is ongoing investor management: what tailored behavioural messages should be used around how and why ESG is integrated into the portfolio?  

The opportunity and responsibility of tech

The role of technology in the hands of investment providers and advisers is crucial to grasping the opportunities, and meeting the responsibilities of matching socially-minded investors to suitable ESG investments.

Given the complexity of both human preferences, and the ESG world in general , there is a temptation to dodge the hard questions.

But with the right use technology we don’t have to. A behaviourally conscious analysis of the nuanced world of investor ESG preferences, set within a framework designed to match investors to investments at scale, allows us to see better solutions more clearly, and generate better and more sustainable outcomes as a result.

Related Posts

Oxford Risk is proud to be leading the way in the field of data and analysis to support and understand investor behaviour and preferences around sustainable investing and ESG.

Read More

Investment management specialists, 7IM have partnered with behavioural finance pioneers, Oxford Risk to support growing demand amongst advisers and wealth managers for risk-mapped funds and portfolios.

Read More

Measuring investor ESG preferences has gone from a nice-to-have to a must-have. Without behavioural forethought, how to do it risks prioritising the false economy of easy pigeonholing over a genuinely valuable understanding of an investor’s preferences.

Read More