How to solve the ESG data puzzle across the investment lifecycle
Investors’ appetite for high returns has not abated but strong outcomes must also meet sustainability demands. Indeed, reputation is now competing with return and risk considerations in ESG investing, even for the most conservative of institutions.
Firms that want to stay competitive and attract new business as well as talent are expected to prove that they are taking net-zero and other ESG commitments seriously across their whole portfolio.
Ultimately, this means fully integrating ESG considerations across strategies and processes with consistent data across investments.
Solving the ESG data puzzle
ESG data is unique and has its own taxonomy. Because most companies are not subject to mandatory reporting, the onus is on fund operators to manage ESG data.
One of the biggest challenges stems from a lack of data standardisation and the inability to feed non-standardised ESG data into investment operations. Added complexity comes not only from the lack of consistency and comparability but also from the myriad of data vendors with their own scoring methodologies, sources and coverage.
Faced with the daunting task of standardising all the different categorisations of ESG data, many investment managers are turning to manual processes. From acquisition to normalisation, cleansing and reporting, investment managers are arduously piecing together this patchwork of unstructured data in various formats.
However, this non-standardised data and the manual and error-prone workflows associated with it means that the insights gained are questionable and so are the decisions that follow.
Fortunately, there is another way of safeguarding these insights without having to go through the trouble of acquiring and managing the data yourself – Data as a Service (Daas).
ESG data sourcing and management
ESG is the perfect use case for DaaS. Fund operators can benefit from a wide variety of data sources, without the hassle and risk of collecting and processing data internally. DaaS does this by fully automating the in-bound ESG data received from multiple parties, ensuring its validity and creating a single source of truth for the entire organisation.
At its core, this managed data service enables investment managers to retain 100% control of their data, proprietary insights and governance, while taking the operational burden out of the process. Importantly, this frees up internal resources to focus on value-added activities.
Moreover, these services do not just add transparency; they also provide a specialist advisory service through industry experts. This can help investment managers navigate and implement future regulations, including the looming Sustainable Finance Disclosure Regulation (SFDR) deadline later this year.
ESG data processing throughout the investment lifecycle
The first step to successful ESG investing is access to reliable data. But getting data into the system is just the first part of the journey. It must then be robustly managed and governed, and optimally processed across the entire investment value chain.
Key to this process is the consolidation of ESG data and analytics into the core investment process with rigorously applied investment analysis and optimisation as well as sophisticated compliance and risk management.
In the long run, all investment managers will be expected to include ESG factors across all asset classes in public/private markets, not just those specifically designed as ESG products to better manage risks and improve returns.
This means ESG analytics must be integrated with other data metrics in a common Investment ‘Book of Record’ to achieve a holistic view across all instruments with real-time positions, performance and risk analytics as well as sophisticated pre- and post-trade compliance.
Meeting the growing client need for reporting on ESG factors requires a strategic approach to communication. Firms need an automated, workflow-driven client reporting platform with seamless integration of all the required ESG data sources.
The ability to flex and pivot those data sources as they become available, or as regulations change, to inform clients in the most relevant and timely manner will be the key differentiator.
Given the fragmented nature of investment processes prevalent today without a holistic view of all asset classes, many organisations still rely on ESG data for specific products rather than ensuring it is used enterprise wide.
This lack of cross-referencing of ESG datasets with those in the investment lifecycle, means data from multiple systems must be manually pieced together to generate ESG insights at the portfolio level.
This introduces a number of inefficiencies, weakens data governance and limits scalability in the reporting process – not to mention the inability to tailor the prioritisation of different ESG factors within the reports, the real value-add for clients.
Fund operators must be able to capture the full impact of ESG metrics on investment decisions, compliance, performance attribution and risk.
Consistency and innovation are key. Once an ESG strategy has been adopted, investment managers must ensure that it is applied consistently across all business areas – from the chosen datasets to the communications with end-investors.
To achieve that ultimate objective, firms must carefully choose a technology partner with a platform that allows ESG integration front-to-back in a single system which also offers the optionality to outsource non-core operations, such as DaaS.
Forward-looking firms will also seek partners with open platforms that offer them the ability to tap into innovative fintech technologies that create enriched perspectives on ESG and impact.
As the ESG investment landscape evolves, savvy managers that have invested in an open system and flexible framework that can adapt quickly to combine ESG with high returns, new regulations and changing demands from their investors, will leap ahead.
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