How can operations teams use AI to improve reporting?

Industry figures discuss latest technology improvements and how they can assist or hinder investment operations teams in reaching reporting synergy.

Fund Operator Editor POSTED ON 12/6/2023 2:00:00 PM

(L-R) Yelton, Herold, and Willman.

How can operations and investments teams work together to achieve compliant and efficient ESG regulatory reporting throughout the investment chain?

At a recent Clear Path Analysis webinar, produced in conjunction with Clarity AI, Hannah Herold, Director of Sustainable Research, American Century Investments, Glen Yelton, Head of ESG Client Strategies, North America and EMEA, Invesco, and Thomas Willman, Senior Researcher (Regulations), Clarity AI spoke on the topic of “Maximising visibility in ESG regulatory reporting through the investment chain”.

The group were asked for their thoughts on where technology could help improve sustainability reporting – and whether there was a place for Artificial Intelligence (AI), the buzzword of 2023. “New technology can really help improve sustainability reporting,” said Willman on the topic.

The discussion now forms part of a report, available to download, that covers the topic from many angles. The report also features insights from senior figures at Legal & General and Manulife Investments.

The group highlighted the often-fraught relationships that exist between operations and investment teams at asset managers due to differing priorities. The group discussed how to work through these issues, highlighting how to leverage technology for data analysis, and why this was necessary.

They also emphasised that these processes should be done carefully and monitored by human oversight.

Read more of their thoughts below.

Maya Sibul: How can investment teams better utilise technology to improve sustainability reporting?

Thomas Willman: Artificial Intelligence (AI) and machine learning techniques are key – especially with the collection of data at scale – whether it be natural language processing to scan prospectuses or looking at different news articles or sources.

When it comes to speed, this is the chalk and cheese in terms of the amount of data you can process by leveraging technology versus relying on the analysts.

There is also the reliability point – using reliability models to ensure that the different data points you are collecting are accurate and robust.

"Client needs should always be the basis; good regulation isn’t backwards-engineered."

There are techniques to automate that process so that it only flags difficult cases to be reviewed by humans because we always involve humans in this loop.

My final recommendation is to personalise analytics in ‘Spotify’ style to really understand the types of insights that the client is trying to get and deliver better products.

Client needs should always be the basis; good regulation isn’t backwards-engineered.

Hannah Herold: Emerging technology will, I hope, really help with supply chain data and management. One of the biggest topics is usually Scope 3 emissions and the need for more transparency and data collection in this area.

"We’re still at the step of measuring exposure, and we need to move past this. I don’t think we can without technology."

There’s also an opportunity for more information about social supply chain issues. Over the last 6-12 months, many companies have made efforts to use new technologies to track modern slavery or child labour issues. We have a long way to go here, but I’m tentatively optimistic that there are technology solutions that could fill some of these gaps.

We’re still at the step of measuring exposure, and we need to move past this. I don’t think we can without technology.

Glen Yelton: Technology is a challenge because the algorithms that interpret machine learning of course have biases baked in. Whilst the speed of adjustment and adaptation of the technology is increasing, we need to recognise biases and ensure we don’t lose the richness of the data.

It’s a similar situation for reporting tools and supply chain-related disclosure elements. Being able to analyse and crunch those numbers and get the proofing back to ensure the data is actionable is a gap we will hopefully see close within a year.

To see more of the group’s thoughts, and read the report in full, please click here.


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