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February 16, 2024

Unlock value via ESG data management strategies

With the integration of ESG data in investments, the spotlight is shifting to data management

 

 

 

 

Nick Dalbis 

Associate Director

Data Analytics

CRISIL Global Research & Risk Solutions

 

 

 

 

Shivami Jaiswal 

Research Analyst

CRISIL Global Research & Risk Solutions

 

 

 

 

Dwait Mehta 

Research Analyst

CRISIL Global Research & Risk Solutions

 

Asset management firms are increasingly recognizing that incorporating environmental, social and governance (ESG) considerations in investment research and portfolio construction has become a business imperative.

 

However, this is easier said than done.

 

Multiple metrics across the E, S and G pillars, dynamic regulations and paucity of universal standards can make the integration process onerous. Moreover, ESG itself is in a state of constant evolution - we can expect new biodiversity indicators to be part of standard ESG taxonomy going forward.

 

Actionable data, therefore, is the fulcrum of the ESG paradigm.

 

And herein lies the challenge - the ability to manage and analyze large volumes of time-series data in an efficient manner. We also note that accurate and up to date ESG metrics are equally relevant for other functions including compliance, client reporting, etc., in addition to portfolio construction.

 

Hence, we must ask: How can effective ESG data management enhance the value proposition for asset management firms?

ESG Data Management

 

Multiple key ESG use cases have emerged within the asset management space in day-to-day operations.

 

 

ESG scorecard reporting:

 

Automate scoring process and dashboards reporting at sector, company, climate, region, and country levels; simulate ESG scores based on customized configurations.

 

ESG audit trail:

 

Create a traceable workflow of ESG documentation with backups and fail safes in place to ensure quick access to relevant evidence in response to regulatory requirements.

 

Financing models:

 

Utilize analytical models to identify ESG asset impact, recognize funding opportunities to achieve sustainability targets and the target return on investment for firms.

 

Sustainability analysis: 

 

Conduct pre-investment due diligence across the coverage universe to ensure alignment with the portfolios’ sustainability mandate.

 

ESG workflows: 

 

Unify structured and unstructured ESG data with quantitative and cloud-hosted machine learning techniques and create streamlined ESG pipelines to service clients.

 

ESG taxonomy creation:  

 

Connect data management tools with business-friendly semantics to create libraries, definitions and governance structures for ESG workflows.

 

 

However, asset managers are facing challenges in effectively collecting and utilizing ESG data

 

With the soaring importance of ESG, the data associated with these considerations has become voluminous, diverse and complex. Asset managers find themselves grappling with the task of collecting, analyzing and interpreting unwieldy ESG-related information to make informed investment decisions.

 

Difficulties related to data quality loom large

 

Data quality is a major concern for asset managers navigating ESG data. According to a BNP Paribas1 survey, a noteworthy 71% of institutional investors identify 'inconsistent and incomplete' data as the primary obstacle to ESG investing. High-quality ESG data is indispensable for effective benchmarking, informed investment decision-making and the development of tailored benchmarks. Furthermore, data inaccuracy is a major problem in vendor reporting, leading to significant risk for asset managers who may base their decisions on incorrect information.

 

Diverse and fragmented legacy systems are a hurdle

 

Asset managers grapple with a major challenge in handling diverse and fragmented ESG data due to outdated infrastructure. This limits accessibility to critical sustainability analytics, such as ESG disclosure, climate risk models and emissions data. The presence of multiple data providers with proprietary methodologies complicates integration, even as the lack of data format standardization hinders its use in investment decisions. The absence of a common format and diverse reporting methods further compound this issue. Recognizing the need for a disciplined approach, asset managers are urged to adopt a more standardized and transparent ESG data framework to meet stakeholder demands and facilitate informed and sustainable investment decisions.

 

Lack of current and periodic data makes assessment challenging

 

The challenge faced by asset management companies extends to the absence of up-to-date and periodic ESG data. This deficiency impedes the thoroughness of risk assessments and the capacity of asset managers to take informed investment decisions. The lack of recent ESG information also hampers the accurate evaluation of the long-term sustainability of potential investments. Additionally, for precise performance analysis, asset managers depend on periodic data to facilitate comparisons of portfolio company performance over time. This information gap not only undermines the efficacy of the decision-making processes but also heightens the risk of overlooking emerging ESG-related issues.

 

Use of estimations carries the inherent risk of compromising data precision

 

Asset managers heavily rely on accurate ESG data for informed decision-making and risk assessment. However, data providers are forced to estimate data in the absence of the latest numbers. Such inexact data becomes a challenge for asset managers since it introduces the potential for inaccuracies in assessing the sustainability performance of companies and directing and monitoring investment. Therefore, asset managers may be unable to trust and confidently integrate ESG metrics into their investment strategies.

 

Evolving regulatory requirements heighten complexity

 

The regulatory environment surrounding ESG issues is in a state of constant flux, posing significant challenges for asset managers. Ongoing changes in ESG regulations, exemplified by initiatives such as the EU Corporate Sustainability Reporting Directive, introduce complexities in ensuring compliance and maintaining data consistency. The constant evolution of ESG regulations, alongside challenges in accessing the latest ESG data and navigating diverse regulatory frameworks, adds further intricacy to the integration of ESG considerations.

 

Here's how we can untangle the complexities

 

While asset managers confront challenges in ESG data management, various strategies can be adopted to overcome obstacles and elevate sustainable investing practices. Early adopters should target specific ESG capabilities that span the data lifecycle, from data ingestion to consumption and reporting, based on the maturity and unique characteristics of the firm.

 

Drawing from our experience working with asset management companies, we have identified effective strategies for managing and leveraging ESG data:

 

Managing and Leveraging ESG data

 

With ESG data becoming ever more crucial for investment decisions, asset managers are central to navigating challenges in this evolving landscape. Despite issues with diverse data, data quality and changing regulations, it is essential to adopt strategic approaches.

 

 At CRISIL, we have been engaging with asset managers, helping them leverage effective data ingestion and sourcing techniques to streamline sustainability strategy implementation, ensuring access to high-quality datasets. We have also implemented customized data taxonomies and metadata to promote efficient data governance, facilitating compliance with regulations. We have been integrating ESG data into systems and processes through advanced data architectures.

 

Despite complexities, these strategies will forge a way forward for asset managers to overcome challenges, embrace ESG considerations and contribute to a more sustainable and rewarding investment landscape.

 

In the next blog in this ESG data management series, we will delve into data ingestion and how it can benefit stakeholders handling ESG data. 

 

1ESG Global Survey Report, BNP Paribas