9 min read
Data, data everywhere, but not a drop to drink, or so might have thought the Ancient Mariner if he had been here in 2023. But investors and asset managers might well be considering that mixed metaphor of Coleridge’s famous line if the most frequent frustrations expressed by speakers at this ESG Data & Tech Summit, from A-Team Group in London are to be believed.
If anything was clear at this comprehensive overview of the challenges facing the measurement and application of Environmental, Social and Governance (ESG) data, it was that as this new influence on the finance industry begins to go mainstream the perspective becomes ever murkier. Although under the terms of the event we were allowed to write about what was said, we could not directly attribute it back to the speakers. But it was clear from a large majority there that the industry’s biggest headache is data and how to use it more effectively.
Thirst for data
There’s certainly no shortage of data. If anything, the opposite given all the new data sets being generated to cope with the thirst for information to measure, analyse and understand the ESG and sustainability credentials of both asset managers and their corporate investment targets.
One example was a criticism of the ratings companies who have tried to build standards and indices that can be comparable. However, as one delegate said,
Nevertheless, it was a common theme, or plea for help, by a wide cross section of speakers from asset managers, regulators, data providers and technologists who are desperate for the data to show more consistency, more clarity and be of better quality if it is to deliver the answers required.
In fact, given the relative short time of ESG’s existence it is staggering to realise just how many sources of data are now being offered to the industry, over 600 at the last count – and not including data self-generated by individual investors and companies. Even those who have filtered and consolidated their trusted sources of data are dealing with 30-40 suppliers.
Data congestion
Although the finance industry has always struggled with growing mountains of data, this situation has produced a completely new challenge. Terms like “data congestion” have become commonplace as users struggle to aggregate structured and unstructured data sets into comparable formats that can enhance decision-making without fragmentation and isolation.
As one speaker said, the situation needs to focus on six key challenges:
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Data Availability
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Standardization
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Data Scope |
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Data integration
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Forward looking data
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Data Privacy, sharing,
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In order to deal with these and deliver data in a digestible and comparable way new approaches are needed. As one said, “We need to reduce the information overload.” This has resulted in an inability to create proprietary ESG metrics as well as being unable to integrate the results into existing workflow tools. In a nutshell, current IT systems have proven unable to cope with the large, varied and constantly changing data sets, which now require a new IT culture and a cloud-based data platform.
Unintended benefits
When asked about their biggest ESG data challenges, some 70% of the around 100+ audience said it was either the difficulty of integrating new with existing data or filtering inaccurate and incomplete data. But there have been some unintended benefits resulting from the new approaches required to deal with these data challenges.
“By accident we have seen the creation of a Trojan horse that has started to force the merger of capabilities within the business” said one asset manager. “People in previous business silos like risk, investing and trading that rarely communicated before are being forced to discuss ESG in order to produce common answers.”
“We are breaking down a lot of silos where people now have to work together to make the picture look the same across the enterprise.”
But in order to enable this integrated access and common perspective, technology needs to be adapted to operate on a cloud platform with significant data storage and analytics that can provide access to the data when required by those disparate users. It is transition in its infancy. And as an IT specialist noted, “For this to work businesses must embrace change. It’s not just a question of taking current business practises that operate on-premises and moving it all to the cloud. New skill sets and new governance must be applied once operations are transferred off-prem.”
AI expectations
There are also huge expectations around the ability of Artificial Intelligence to make sense of these huge swathes of new data. “There are currently huge discrepancies between some estimates (of carbon use, sustainability etc…) and the truth,” said one fund manager. “It is important for us to know how far off those estimates were before they were reported and what that external data will mean for future forecasts.”
“AI methods can identify inconsistencies and show what is the most credible. Algorithms can then be trained to analyse data sets.” However, he was quick to qualify the observation by adding, “I am beginning to understand AI and what it can do, but I don’t necessarily trust it. You have to realise that ESG data is still in its infancy, and we are still understanding how to report it and use it.”
As another said, “Five years ago everyone was becoming an ESG expert, now they are all becoming experts in AI. The pace of change needs to slow down.” Another qualified that by saying, “We don’t need more data now, we need more contextualised data.”
Time to pause
And there lies the conundrum. This industry is moving so quickly, driven in many ways by regulatory zeal, that it is struggling to keep up with its own ambitions. When asked how soon SMEs in supply chains will be subject to ESG reporting standards and rules, one industry expert called for a pause and said,
There are degrees of frustration with the regulators, some feeling the pace of change is too slow and others wanting to see more consistency and collaboration across jurisdictions – the latter a familiar gripe in financial services. But the role of regulation cannot be underestimated and here speakers felt the EU is clearly playing a leading role, while their UK and (particularly) US counterparts are seen as more equivocal and where changing political winds can have a more direct impact on policies.
Reference points
Eventually, some conclude, ESG will become a data set in its own right to be used within financial organizations equally by investment, risk and data science teams. But this is a long way off as the industry starts to contend with sectoral, segmental, geographic and geo-spatial data among many other points of reference that are increasingly being deemed essential to judge a firm’s ESG credentials.
There are further debates to be had about how much of this should be mandatory and how much optional guidance, with only minimal regard so far shown to the costs of implementation. However, very much on the radar are activities that many see as muddying the ESG waters – notably “greenwashing.”
This practise, particularly where money is used to buy carbon credits, and other misleading and sometimes inappropriate use of ESG credits and working practises, have produced a notable speedbump in ESG’s path. Most agreed that the industry needs to address these concerns if it is to both maintain its wholesome credentials and keep critics at the fringe.
Nevertheless, so far it seems to only be a speedbump and one the industry is moving quickly to rectify. Most of the investment management industry appears to be getting on with the practicalities of delivering a clearer ESG picture that helps with more meaningful investment decision-making. When asked “What is the next milestone in your Cloud ESG journey” over 50% replied “We are in production and planning more use cases.”
Transparent and simple
So, despite political objections in some quarters and problems with some over-enthusiastic and un-co-ordinated regulatory creep in others, there is little doubt that ESG will be here to stay as a metric for the investment industry to be held to account by. The challenge now is to make the process as transparent as possible, as simple to understand as possible and to only extend it once the high-level indicators have been accepted and are shown to be working.
As one speaker said: “The future is already here. There is no reason why you should not be able to sign a contract (with a data supplier) and have access to the data in a few hours.” The secret to success will be in the preparation and planning of IT systems to be able to handle the vast quantities of structured and unstructured data, analyse it quickly (most agreed that real-time is not necessary) and make sure it is clear and comparable by those who need to use it.
A final word of advice was, “Whatever you do, do not build a behemoth multi-year data warehouse and analytics strategy – as they will never deliver.” Keep it simple, but smart was the message.
So if data is not to become the industry’s metaphorical Albatross around the Ancient Mariner’s neck, it needs to decide quickly how to address the new data challenges and agree on methods, practises and technologies that deliver the desired outcomes. If it does, there will be plenty for all to drink.
