Financial services firms are always trying to understand and improve their sustainability position. Building a scalable and future-proof ESG data framework is vital to achieving this. Not only can it support organisations in navigating an evolving and complex landscape, but it can also help to overcome challenges and produce firm-wide benefits – if implemented correctly.
The build is a difficult task, however, requiring the correct framework and tailored processes to be effective. Getting the most from it requires a range of expertise that provides the ability to collect, interpret and use complex information, as well as deliver a fit-for-purpose technical solution.
Because ESG data has significantly evolved in the digital age, it's more important than ever to be able to identify, validate and deliver strong ESG metrics. These seven critical steps will help you build an ESG data framework that supports your firm's sustainability goals.
1 ESG data strategy
The first step is to outline the firm's ESG data strategy to determine sustainability requirements. A cost-effective and scalable ESG data strategy should provide a consistent and coherent approach that covers both internal and external data sources. It should also be at an enterprise level and align with the group-wide overall data strategy to be most effective.
2 ESG data vendor assessment and selection
Some ESG metrics need to be sourced from market data vendors. Firms must prioritise the ability to search, shortlist and undertake due diligence to select the best data providers and platforms that align with specific regulatory disclosure and board commitments.
3 ESG book of record
Developing an ESG data book of record is fundamental. It captures how the firm will meet its commitments, aligned to the risk exposure and the specific data attributes, and measures it selects to articulate ESG. Each firm is unique and has its own set of goals; the ESG focus therefore also varies greatly. Having a taxonomy in place will allow you to collect the most appropriate forms of ESG data metrics, benchmark data, reference data, as well as individual baselines for target setting and tracing.
4 ESG data model
Building a secure ESG data pipeline requires designing and constructing data products from use cases through a common data model, aligned to source data. These range from regulatory and customer use cases to overall shareholder relations and should be aligned to house both internal and external data. You should also ensure there is appropriate data quality and data lineage in this process.
Regtech: automating regulatory change compliance
5 ESG data and analytics platform
The next step is to gain visibility over your ESG metrics and scores by developing an end-to-end ESG data and analytics tool. Building this tool provides the ability to demonstrate a variety of use cases (regulatory disclosures, executive committee and board visibility, end customer and shareholder communications). It will also allow you to compare a set of benchmarks from different providers to find commonalities and outliers in order to provide as much useful information as possible.
6 Building an effective ESG data and technology vendor ecosystem
You can accelerate your firm's ESG journey by combining value-added collaborations with ESG data and technology vendors on a range of topics. These include emissions, supply chains inclusion and diversity (I&D) and net zero. Having respectable vendors on board can help ensure that you meet the quantitative requirements of digital platforms and data input in a way that's reliable and transparent.
7 ESG data assurance
Independent assurance of a firm's approach to satisfying ESG regulatory requirements is essential. As with other pillars of regulatory reporting, you must show that you've taken steps to ensure your submitted information is accurate and prevents greenwashing risk. Strong data assurance mechanisms will help ensure that information is being disclosed correctly.
Building an ESG data platform for financial services
How to start your ESG data journey
Adopting a good ESG data framework is an ongoing process – requiring a constant focus on improving tools, data strategies and the overall data ecosystem. It also offers financial services firms a dynamic and forward-looking approach to ESG frameworks and ensures that ESG data is robust and reliable enough to improve sustainability and collect strong information.
You can begin this journey by mapping and understanding your overall ESG data to support an organisational shift. Building a tailored ESG data solution will then ensure you meet both the needs of the organisation – and its current and future sustainability objectives.
