10 minute read 5 Jul 2021
Bridge in sea

Why data remains the biggest ESG investing challenge for asset managers

There’s a profound disconnect between the environmental, social and governance (ESG) data asset managers need and what’s available to them.

In brief
  • We examine three key dimensions of the ESG data challenge from the perspective of institutions that manage financial investments.
  • We explore how asset managers are upgrading their ESG capabilities and how their efforts compare with those of banks and insurers.
  • We explain what’s hindering progress, from inadequate disclosure of ESG risks by issuers and conflicting ESG taxonomies to contradictory ESG ratings.

With rapidly growing investor expectations of ESG integration into investment decision-making, we examine how asset managers are seeking to develop their ESG capabilities to meet investor and regulator demands.

The latest EY Global Institutional Investor survey  shows that financial institutions’ interest in ESG has become virtually universal. Working with ESG data is no longer optional. Asset managers, banks and insurers are all moving toward a more disciplined and rigorous approach to evaluating companies’ nonfinancial performance. However, progress is hindered by the inadequate disclosure of ESG risks by issuers, and further slowed down by conflicting ESG taxonomies and contradictory ESG ratings.

In this article, we examine three key dimensions of the ESG data challenge from the perspective of institutions that manage financial investments: from ESG data accessibility to consistency and suitability. We will discuss the data challenges associated with ESG investing, but also explore how asset managers are upgrading their ESG capabilities, and how their efforts compare with those of banks and insurers. 

Stakeholder demands are driving asset managers’ ESG focus 

The asset management industry has a long history of stewardship, but it’s undisputable that the evolution of principles-based regulation is a crucial driver of ESG scrutiny. The EU’s action plan on sustainable finance and its proposed taxonomy of environmental factors generated the most headlines. Arguably, it’s the EU Sustainable Finance Disclosure Regulation (SFDR) that will have the greatest impact on asset management, given its strict “ESG” and “sustainable” labeling requirements and the disclosure burdens it imposes on funds and managers. Asian financial hubs are also raising their sustainability standards: These include the Hong Kong Securities & Futures Commission’s “Consultation paper on the management and disclosure of climate-related risks by fund managers” and the Monetary authority of singapore’s recently published “Guidelines on environmental risk management”. 

Ultimately, investor demand and competition are significant drivers of asset managers’ interest in ESG performance. This is illustrated by high-profile fossil fuel divestments made in recent years by end investors ranging from Nordic sovereign wealth funds to US pension funds. 

Data remains the sector’s greatest challenge

Data suitability

Unfortunately, asset managers’ desire to focus on ESG performance is not always matched by reality. When it comes to investment decision-making, asset managers are more dependent than banks and insurers on publicly available sources of nonfinancial data. Historic in nature, the data from these public sources are only disclosed once or, at most, twice a year. The EY Global Institutional Investor survey shows that this presents an additional challenge for the sector:

1. Privileged data

Asset managers need to model future earnings, but The EY survey shows that 50% of asset managers see a lack of forward-looking disclosure as limiting the value of ESG reporting, compared with 31% of insurers and 25% of banks.

EY Global Institutional Investor survey


of asset managers see a lack of forward-looking disclosure as limiting the value of ESG reporting.

This is because banks and insurers have more sources of privileged forward-looking data, e.g., loan businesses, mortgages and trade finance.

2. Real-time data 

Asset managers need to take day-to-day decisions in response to fluctuating market risks and prices, but this is at odds with the frequency of public nonfinancial disclosures. The EY survey shows that 46% of asset managers view the lack of real-time information as a limitation on the value of ESG data, compared with 41% of insurers and 35% of banks.

EY Global Institutional Investor survey


of asset managers view the lack of real-time information as a limitation on the value of ESG data.

Data accessibility

In addition to these shortcomings in underlying data, asset managers face structural obstacles to using nonfinancial information. Much of it is presented in either narrative or unstructured form. Asset and wealth management firms still struggle with developing and maintaining a “golden” copy data architecture of investible instruments — a single source of the truth. In contrast, repositories of client risk information are central to the core activities of banks and insurers.

Data accessibility affects smaller and more specialized institutions more, as they typically rely on third-party data vendors for critical information, such as ratings. Bigger firms, on the other hand, often have access to in-house research and are able to calculate proprietary ESG scores.

Taken together, these limitations have an inevitable effect on asset managers’ ability to perform frequent, rigorous analysis of nonfinancial disclosures:

1. Frequency of use

The survey shows that while the use of nonfinancial disclosures in investment decision-making is becoming more frequent, asset managers are lagging behind in other sectors. For example, 55% of asset managers use nonfinancial data occasionally and 37% frequently. In contrast, 49% of insurers use nonfinancial data frequently and 42% occasionally.

Frequency of use

2. Informal or methodical evaluation 

A similar picture emerges from the type of analysis employed by the institutions. The proportion of asset managers conducting structured analysis of nonfinancial data (67%) exceeds those conducting informal evaluations (30%), but the use of methodical approaches is notably higher among insurers (79% to 19%).

Informal or methodical evaluation

Data consistency

Asset managers’ data problems are compounded by conflicting ESG taxonomies, as well as the national identifiers established by individual governments, particularly given that ESG spans both financial and nonfinancial worlds. Different frameworks often use contrary definitions — does nuclear energy or carbon capture constitute “green” investments, for example? Despite efforts at standardization, these challenges are set to continue. 

In addition to the EU taxonomy, China, Japan, Singapore and Canada are now developing their own taxonomy versions and a UK Green Technical Advisory Group was established on 09 June 2021 featuring ESG experts to review EU Taxonomy metrics to ensure they are appropriate for the UK market. Asset managers, who typically make more cross-border investment decisions than banks or insurers, will be troubled by inconsistent definitions for the foreseeable future, as a single globally recognized standard in ESG reporting and transparency does not exist.

Though there is a multitude of market data providers and specialized ESG ratings companies, the majority of these only offer a partial solution to the sector’s data headaches. We see, however, that data providers are trying to match these ESG reporting needs by developing a suite of solutions for their clients. Nowadays, it’s not unusual for large asset managers to use various ESG data providers, brokers and academic research feeds. 

EY analysis of 62 of the largest asset managers worldwide shows that most asset managers use between 2 and 5 different providers and some even use up to 10 different third-party vendors to cover their ESG data needs. Looking ahead, it’s possible that ESG data providers could fall within the regulatory perimeter set by EU. That would fundamentally change how nonfinancial data is accessed and could trigger a wave of consolidation among providers.

In short, nonfinancial disclosures are not yet sufficiently accurate, consistent, appropriate or timely enough for asset managers to use them as often or as effectively as they would like.

How asset managers are investing in their ESG capabilities

Faced with these continuing challenges, many asset managers are seeking to develop their proprietary ESG capabilities. The industry is also working to improve its own disclosures — a process that should be given further impetus by measures such as the SFDR. Demonstrable ESG leadership in this area will be a valuable source of differentiation, but no single strategy is without its drawbacks. Let’s look at the three different ways in which asset managers are seeking to tackle the ESG investing challenge:

1. One approach is to develop in-house research expertise, enabling asset management firms to generate their own ESG ratings and project these into the future. However, only the largest firms can make the necessary investments in talent and technology. Internal ratings can also create problems, for example, when financial and nonfinancial ratings contradict each other or when E, S and G ratings tell a different story, or when some of the components (e.g., S or G ratings) are unavailable.

2. Screening techniques are another area of focus. Positive screening is seen as the “gold standard”, but objective quantification is exceedingly difficult. Negative screening is easier to execute, but its use by itself is limiting, as the process may not be sufficient to classify a product as “sustainable” according to some regulators. The survey shows that 23% of asset managers expect oil companies to be affected by exclusions over the coming year. But, with many major fossil fuel providers now investing heavily in renewable energy, this strategy faces questions over its usefulness.

3. A third area of potential differentiation for asset managers is the analysis of nonfinancial data from alternative sources such as satellites, drones or social media. Deriving actionable insights from this data typically depends on the use of data analytics and scenario modeling using artificial intelligence or machine learning. In both cases, the ability to work with external vendors and service providers is vital to success.

The described three approaches are different ways through which asset managers are seeking to rise to the ESG investing challenge. We believe that asset managers need at least a minimum of in-house research expertise, as well as sophisticated screening techniques. The application of data and analytics is expected to become a trend in the future, and is fundamental to the successful integration of forward-looking and alternative data for scenario analysis and risk modeling.

EY has developed two key accelerators that can help firms move at the fast pace required:

1. An end-to-end ESG Data solution, EY Arena. EY Arena ingests ESG data from multiple sources, harmonizes into a common ESG Data taxonomy, then represents the ESG information required for various ESG data usages (such as particular regulatory reporting requirements). All of these EY Arena components can be used as patterns and templates and hence accelerate implementation.

2. An analysis of the ESG Data provider landscape to inform your ESG data sourcing strategy. The analysis identifies the providers that support key regulations (e.g. SFDR, EU Taxonomy, TCFD). It also identifies the category of data provided (e.g. ESG scoring, ESG indices, sentiment analysis, etc.). Finally, it identifies the modelling coverage supported (Net Zero, Climate Risk, etc.).

Looking ahead

Asset managers are working hard to overcome their ESG data challenges, but it’s clear that the sector is still far from meeting, let alone exceeding investor expectations. On the upside, the survey suggests that financial institutions worldwide see asset owners and asset managers as better placed — than regulators or international bodies — to close the gap between the nonfinancial disclosures made by issuers and the transparency desired by investors.

However, no single sector — let alone one confronting the data challenges that asset managers face — can deliver against that ambitious goal alone. In the long run, integrating ESG into investment decision-making will depend on aligning ESG strategy across the investment value chain. That needs to involve corporate issuers, asset managers and asset owners, banks, brokers, data providers and external stakeholders, such as regulators and governments.

In the long run, integrating ESG into investment decision-making will depend on aligning ESG strategy across the investment value chain.
Gill Lofts
EY Global Financial Services Sustainable Finance Leader

In short, asset managers, issuers and other stakeholders need to work together to enhance the standard and consistency of ESG disclosures in order to deliver a sustainable, equitable future. There have been widespread calls for a “green recovery” from the COVID-19  crisis, with economic stimulus packages prioritizing environment-friendly infrastructure projects to “build back better.” Asset managers cannot deliver this single-handedly, but as part of their fiduciary and stewardship duty on behalf of shareholders, they are likely to drive companies to care about ESG — whether they like it or not.

The ESG data challenge will continue as regulatory requirements and investor demands evolve over time. As ESG investments are becoming more mainstream, ESG data will become more and more important. We expect future ESG data challenges to include the integration of real-time ESG data into investment decision-making, requiring the development of a “golden” copy data architecture.  


By driving companies to see sustainability as a business imperative rather than “just” a moral one, asset managers play a crucial role in improving the quality of nonfinancial disclosures. This will in turn make ESG investing a less complex and more profitable business for asset managers. On a practical level, asset managers need to:

  1. Enhance their screening strategies and develop their own ESG scoring methodologies.
  2. Understand data from ESG data providers and position themselves better for the future with ESG data.
  3. Leverage advanced data and analytics tools to develop forward-looking scenarios.