Martina McPherson tells Finextra Research of the need to “get alternative data and sources into the mainstream”, in order to “create real-time inputs and triage real-time information to provide the past, present and forward-looking perspective”.

While demand for ESG investments has held up particularly well amidst the Covid-19 pandemic, seeing significant inflows of $33bn in Q1 2020, McPherson believes that AI-driven sustainability data would offer the opportunity to create innovative solutions that reflect hidden risks and opportunities, not picked up by conventional financial data.

“Decision makers in financial industries are using more specific linked processes to provide simpler, more efficient data to empower decision making and break down information barriers and biases, modernising information architecture,” she says.

This could act as a strategic enabler for ESG analysis to help financial institutions better understand the interconnection between different environmental and societal risks and opportunities and the information linked to them.

This would then create demand for technology providers that can structure and align this ESG information and establish links and analyse macro trends to improve investment decisions.

“We see the need and support ambitions for more alignment, collaboration and more transparency of ESG information and standards to enhance better long-term decision making.”

She refers to work undertaken by Moody’s in creating integrated ESG risk assessment for credit analysis, incorporating risk assessment and stress testing for the effects of climate change, for example.

McPherson believes this could be an antidote to the current variance in the quality and reporting of data related to sustainability of investments. She claims this is why it is difficult for financial institutions to assess impact across different sectors, when different companies use different materiality thresholds to assess the effect of climate change and other risks.