Addressing the ESG Data Challenge

In his new blog, Eagle’s Australian-based Director of Client Services, Manu Sathananthavel, discusses the growing prominence of ESG factors in the investment process and the accompanying data challenges this presents. He reveals how a data-centric approach can help firms effectively integrate and ensure the quality of ESG data and highlights how Eagle’s clients, such as First State Investments, are using Eagle for their ESG reporting.

Manu Sathananthavel, Director of Client Services – Australia


In recent years, we have witnessed a surge in interest in environmental, social and governance (ESG) considerations among asset managers. Despite attempts to define and standardise ESG factors, most notably by the United Nations which set up the Principles for Responsible Investment (PRI) in 2006, best practice still hasn’t fully emerged and reporting from region to region remains inconsistent. Furthermore, there is little consensus around the measurement of ESG factors, scoring and definitions many of which are more subjective than other performance measures, and there is little in the way of formal regulation to shape that consensus. As a result, the collection and reconciliation of high quality data are among the key challenges facing asset managers as they look to improve their ESG reporting.

Interest in ESG and impact investing is being driven by a number of factors. First, asset owners and investors are keen to have a positive impact on society and the environment. Issues like climate change have forced their way up the agenda in recent years while high-profile man-made environmental disasters such as the Deepwater Horizon oil spill in 2010 and the Vale/BHP Billiton iron mine collapse in Brazil in 2015 have also brought ESG into sharper focus for investors.

There is also a mounting body of evidence that suggests ESG factors can help mitigate risk and have a positive effect on long-term performance. Firms with better ESG ratings have been found to carry lower firm-specific risks. Certainly there are plenty of high profile examples of companies demonstrating poor ESG practices that have seen detrimental impact on share price. Furthermore, research conducted by Deutsche Asset Management and the University of Hamburg at the end of last year, for example, established a positive relationship between ESG and corporate financial performance.

As a result, ESG considerations are increasingly finding their way into the investment decision-making process. This is highlighted in the 2015 EY Global Institutional Investor Survey, which reveals that the percentage of investors who considered corporate social responsibility ‘essential’ or ‘important’ when making investment decisions rose from 35% in 2014 to 59% in 2015.

Despite an increased focus, there are a host of data issues that present significant challenges for asset managers when it comes to integrating ESG factors into investment decision-making and client reporting. There are no specific regulations covering ESG risk measures with the result that disclosure is largely voluntary for corporations. Indeed, there is not even a unified definition of ESG. Within E, S and G, there are multiple variables or indicators that could be taken into account. At one end of the spectrum it may cover CO2 emissions, which is relatively simple to measure but, depending on the investments in question, it may also include more intangible factors that contribute to ‘making a positive contribute to society’, such as local community relations, which cannot be so easily compared from one company to the next. If this didn’t complicate matters enough, many of the factors requiring consolidation are ‘softer’ than standard financial ones and not so easy to quantify, thereby introducing an element of subjectivity into reporting. As a result, ESG factors are inconsistently reported making the collection of consistent and accurate data – and the reconciliation of it at a portfolio level – a tricky process.

This is where a data-centric approach, like Eagle’s, can help. With a central repository firms have the ability to integrate and validate all data from multiple sources at a security level. With this baseline, firms are able to identify and analyse the relevant ESG factors they wish to measure for reporting purposes, either in isolation or presented alongside other financial factors. For example, Eagle works with First State Investments, a global investment manager that incorporates ESG data from Sustainalytics and MSCI into Eagle from which they are able to report, on extract, a view of ESG quality at a portfolio level. This is used to provide insight to the investment teams and reporting to their Investment Assurance team and its Global Responsible Investment Steering Group in order to more effectively incorporate ESG factors into its investment governance oversight and processes. In the future it will also be used to enhance its client reporting. The flexibility of Eagle’s performance measurement system also enables firms to build their own custom tables and benchmarks based on the ESG factors that suit their unique needs and risk strategies.

ESG looks like it’s here to stay as part of the investment decision-making process for asset managers but while definitive reporting standards have yet to emerge, data quality and consistency remains a significant hurdle for portfolio managers. In its absence, firms that adopt a data-centric approach to data management are at an advantage as it provides a way to compile, integrate and identify the relevant ESG factors from which to build their reports.

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