About a-team Marketing Services

A-Team Insight Blogs

ESG Data. A New Master?

Subscribe to our newsletter

By Mark Davies, Partner, element22.

Master data management has long been an unsung hero. Understood by a handful of technologists and passionate data evangelists, while delivering consistency and control across complex organisations.

Regardless of industry, those organisations that invest in mastering the data that really matters to their organisation reap substantial ongoing dividends. It is never the most eye-catching project for a board-level funding discussion, and invariably the investment in skilled people, processes and policies is just as important as the technology choice.

In the financial services industry, master data is well understood, but not always well executed. Mastering legal entity (primarily customer) data and financial product data is critical to linking information across hundreds of internal systems, but it’s also dirty work.

Traditionally, the smartest graduates dreamt of a life on the trading floor and entertaining clients, not crunching through settlement fails and resolving missing data in the back office. It has not been hard to recruit into data teams as finance pays well, but it has been hard to retain that knowledge and expertise. The reality is that master data teams quickly develop a working knowledge of the end-to-end trade flow, from client onboarding through to settlement, regulatory reporting and offboarding, so the knowledge moves on.

This picture is replicated across industries. The data that is most critical to an organisation’s mission may differ, but approaches, technologies and skills retention challenges are common.

But that may be about to change

Environmental, Social and Governance (ESG) data is fast becoming the next critical data set that large organisations need to consolidate and master. The simple truth is that societal pressure has catapulted this information from an afterthought to become critical to all major organisations.

The impact of this is extremely broad and it increasingly feels as though every team is touched by this new demand – from procurement teams screening service providers for anti-slavery policies, to research and investment teams needing a much broader set of information on employee diversity and pay ratios, regulatory compliance teams needing a deep understanding of environmental impacts across their own organisation and supply chain for mandatory reporting.

Whether companies vehemently support the principles of sustainability and live the values every day, see ESG as a way to compete, or just pay lip service, the reality is that every large organisation is impacted.

This brings us back to master data. When content becomes as pervasive as ESG data is fast becoming – everybody’s side of the desk job, mission critical but managed in spreadsheets, needed by everybody but owned by nobody – it’s time for organisations to take a step back.

Mastering ESG data well is difficult. Standards are constantly evolving and rarely aligned, data sources have questionable quality and opaque methodologies, there are huge gaps in what is being reported and little or no international consistency. In short, the ESG data landscape is a mess.

But that is exactly why now is the time to start mastering this content.

Mandatory reporting requirements for corporates and financial institutions will continue to grow, with hundreds of regulations in draft form or working their way through the quagmire of lawmaking globally. Importantly, many of these draft reporting requirements require look-through to third-party companies. It will no longer be sufficient to just understand the ESG metrics that relate to your own organisation or group, but also ESG data about your supply chain, your investments, your financing activities, your risk exposure.

Have you identified your exposure to areas of high water stress, floodplains, rising sea levels, rising temperatures? Do you have assets that could become uninvestable stranded assets because the industry sector is too controversial? The simple truth is that very few organisations manage this data well across the board, but excellence is developing in pockets. Those that do are starting to see significant overlaps in what data needs to be collected once and managed well, and are serving multiple teams and use cases.

Scope 1 and 2 greenhouse gas emissions, board gender diversity, water consumption and waste – there are a handful of common metrics that are the bedrock of ESG analysis and reporting. Combining these with existing master data including company identifiers, industry sectors and company locations provides a foundation on which to scale a central resource.

So more dirty work ahead, but there is also plenty of good news. The next generation of graduates are passionate about our planet and highly data literate.

Time for the new masters to shine.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Real world data governance – Practical strategies for data ownership

The theories of data governance and ownership are well rehearsed. Essentially, data governance includes rules and processes that make data accurate, compliant and accessible, ensuring the right users can access trusted data as and when they need it. Data ownership assigns responsibility and accountability for a specific dataset to an individual or team that can...

BLOG

DTIF Partners DLC Distributed Ledger Consulting to Add Crypto Risk Metrics to Digital Token Identifiers

The Digital Token Identifier Foundation (DTIF), created by Etrading Software to provide ISO standard identifiers for digital assets based on open data principles, has reached agreement with DLC Distributed Ledger Consulting to display a crypto risk metrics score on Digital Token Identifiers (DTIs) for commonly traded tokens. The metric score, combined with the DTI standard,...

EVENT

AI in Capital Markets Summit London

The AI in Capital Markets Summit will explore current and emerging trends in AI, the potential of Generative AI and LLMs and how AI can be applied for efficiencies and business value across a number of use cases, in the front and back office of financial institutions. The agenda will explore the risks and challenges of adopting AI and the foundational technologies and data management capabilities that underpin successful deployment.

GUIDE

Regulatory Data Handbook 2023 – Eleventh Edition

Welcome to the eleventh edition of A-Team Group’s Regulatory Data Handbook, a popular publication that covers new regulations in capital markets, tracks regulatory change, and provides advice on the data, data management and implementation requirements of more than 30 regulations across UK, European, US and Asia-Pacific capital markets. This edition of the handbook includes new...