Other parts of this series:
In my last blog post, I outlined the challenges and opportunities ahead for sustainable banking. With this post, I’m joined by my colleague Prithika Priyanshi, Senior Principal from the Center for Data & Insights at Accenture, who specializes in AI-powered sustainability.
Just as digital did ten years ago, sustainability now impacts every part of the bank—from the C-suite to the front office, from product development to risk management and compliance, from finance accounting to supply chain. Banks are at a green inflection point and the time is right to make big, bold moves to execute a sustainability agenda.
The world is moving fast. Pressure is building for banks to show that they meet increasingly rigorous environmental, social and governance (ESG) regulation targets. Recently published directives give guidance on calculating and disclosing ESG-related information. One example is the European Banking Authority’s proposal that banks be obliged to report their green asset ratio (GAR). This key performance indicator shows the extent to which a bank’s activities—loans and advances, debt securities and equity instruments (trading books excluded)—are environmentally sustainable and in alignment with the EU’s Taxonomy Regulations.
Banks will need to manage ESG data on the client, product and even financial instrument level. But to demonstrate compliance with these regulations, banks need trusted data.
Accenture surveyed 100 executives across the 50 largest U.S. banks and found that more than one-third (35 percent) think that the availability and granularity of ESG data is insufficient to assess both climate risk and financial risk in evaluating lending decisions. More than one-third (35 percent) do not have a defined approach to measure and assess the potential impacts to their financial results due to the transition risks from mitigating climate change.
In a digital landscape, good data is the foundation for all good decision-making. Yet the banking industry’s secret—one that doesn’t make it into annual reports—is that in its current form, ESG data reporting isn’t very useful. In fact, the challenges associated with proper data collection and processing may be skewing results, misleading stakeholders, wasting resources and leading to poor decisions.
In a digital landscape, good data is the foundation for good decision-making.
Currently, the ESG data market could be worth $1 billion in annual revenues, but what does this mean? And is the available data supply the only answer to banks´ ESG data challenge?
Other large corporations looking to green their supply chains are also dependent on ESG scores for decision-making. On the surface, this makes sense. Companies with good ESG ratings should be performing better when it comes to sustainable business practices, and should be making less of a negative environmental impact than those with lower scores. But there’s a problem: The data doesn’t correlate. MIT’s Sloan School of Management looked at ratings from various ESG vendors and found that the correlation was, on average, just 0.61. That means the ESG rating outcomes of different companies are not sufficiently comparable to measure factors like their carbon footprint or working conditions.
Key challenges to ESG data gathering and processing include:
- Only larger public companies are required to report ESG data, which is published in their annual reports. This limits the data pool to what these companies self-disclose.
- The lack of a single regulatory framework, although various guidelines exist.
- The lack of consensus on terminology and definitions.
- The lack of auditing, which limits the reliability of disclosure reports; there is no universal system to verify reported data, and public reports tend to highlight positive contributions to ESG and underplay or omit less flattering reporting (also known as greenwashing).
- ESG scores are a black box; there is no regulation on how sustainability needs and performance are assessed, and every ESG rating agency has its own methodology which evolves over time. Reliance on ESG scores becomes questionable when underlying metrics are not revealed.
We expect some regulatory actions to improve the quality and reliability of self-published ESG information. The recently proposed update from the European Commission on the NFRD (non-financial reporting directive; now called the Corporate Sustainability Reporting Directive or CSRD) expands the scope of non-financial reporting and enforces more reporting rigor regarding net zero strategies. It also introduces new mandatory reporting standards that will include five times the number of companies. More companies mean more clients, and more clients mean more data. This will allow banks to feed their own ESG data models with reliable, publicly available company information.
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The current ESG data landscape is inconsistent and contradictory. For banks to meet its challenges and navigate its complexities, they must be able to track their sustainability progress accurately and measure it against that of their competitors.
Meaningful and lasting global impact may be beyond the reach of any individual bank at the moment. But just because we can’t change everything, doesn’t mean we shouldn’t do something. Now is the time for banks to make wise and strategic investments in ESG data gathering, reporting and infrastructure, with bespoke sustainable solutions and intelligent insights. Banks that collect, validate and analyze ESG data, in the same way that they do with financial information from their clients, will set themselves apart, not only from a reporting perspective but also in terms of their future business.
Many believe that more standardization and regulation is the only way forward. We caution against this approach—we can’t regulate our way out of this challenge. Much like the digital transformation that came before it, the sustainability transformation will require a re-imagining of how a business is run. Banks will need to leverage intelligent sustainable technologies and smart ecosystem partnerships to make sure they’re getting the greatest insights from the best available data.
These four strategies can transform the way a bank gathers, reports and analyzes data:
1. Define a target operating model for ESG data:
Some banks try to nurture sustainability use cases with ‘fit for purpose’ ESG data feeds, but this results in vertical data silos. A horizontal, internal ESG data utility and service addresses inconsistencies and reduces the need to data-manage future ESG use cases from all parts of the bank. Integration with other non-financial data and the client/product perimeter is key.
2. Harmonize reporting standards and simplify disclosure requirements:
Multiple guidelines and their enhancements over the years have only complicated the ESG disclosure ecosystem. A harmonized, universal, simplified and industry-specific list of screening factors, and a disclosures and measurement methodology, will help banking move forward. Look for ecosystem partners that can provide support and leverage best practice use cases.
3. Scale with AI:
Advanced AI allows banks to build robust in-house ESG data capabilities. It can, with a high degree of accuracy, extract, structure and synthesize text, tables and charts from unstructured disclosure reports at speed and scale. By applying a custom natural language processing (NLP) pipeline and its self-learning algorithms, data from industry reports, home pages and other digital sources can be translated into meaningful binary key performance indicators. Natural language generation (NLG)/NLP identifies and summarizes best practices and other relevant insights, reducing manual effort by nearly 60 percent.
4. Partner with alternative data sources:
Enlist partners with deep data-gathering expertise, as well as banking industry knowledge, to enable ESG data gathering where it is not readily available and to validate the authenticity of the reported data. An example of this would be using weather data to assess air pollution at a manufacturing unit or construction site.
Banks have accepted their pivotal role in financing the sustainability agenda. Forty-three world-leading banks recently joined the Glasgow Financial Alliance for Net Zero. The industry is now at an intersection and needs to start planning for execution.
Accenture can help you design and manage your ESG data collection and processing. Download our Challenges in ESG data gathering brochure to find out more or contact us here.
Christof Innig’s next post will explore ESG in the banking supply chain. In the meantime, read more about sustainable banking in our latest report, “Optimizing the risks and returns of climate change for banks” here.READ MORE