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Treasury & Capital Markets
14th Asian Bond Market Summit – Why data plays an important role in sustainable finance
Data is vital for understanding and determining risks of portfolios
The Asset 13 Nov 2019

The important role of environmental, social, and governance (ESG) data cannot be overstated when it comes to determining the sustainability risks of corporate investment portfolios.

According to Jonathan Drew, managing director, sustainable finance in real assets and structured finance group of HSBC, the broad scope of sustainability risks covers both environmental risks and social risks.

“For the social side, if we are not fair or do not act in an inclusive way, the company will face a cost, the loss of customers, the loss of efficiency and workforce, or even fines if the lines are overstepped,” Drew says in conversation with Chito Santiago, managing editor of The Asset at the 14th Asian Bond Markets Summit in Singapore.

Drew cites as an example risks related to climate change which he says are difficult to quantify because these risks are intangible and involve a time factor in terms of the effect of climate change.

“For example, as we head to a two-degree target (in global warming), as a bank you would be looking into managing and assessing the risks of financing mortgages where the properties are in flood-risk areas or coastal areas. This is something that is manageable,” Drew says.

“For something unmanageable, like the drying out of continental land, that is putting pressure on the food supply and migration of people. This is not manageable because it is really outside the model that we use to make our forecast,” he says.

Drew says there is room for new technology, especially in data collection and management.

“We have a massive need for data and data processing for earth modeling in managing those impacts due to climate changes. There are discussions with academics to try to increase the granularity of data processing in order to produce a predictive model and manage climate risks, for example, in predicting the likelihood of hurricanes in a particular area,” he says.

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