From Compliance to Competitive Edge: The Role of Sustainability in Shaping the Future of Corporate and Investment Banking

In recent months, regulators have intensified their focus on incorporating sustainability into risk management frameworks for banks. For example, on January 8, 2025, the European Banking Authority (EBA) published comprehensive guidelines urging banks to integrate ESG risks into their decision-making processes.¹

Similarly, Switzerland’s FINMA has introduced requirements that place a spotlight on nature-related risks, signalling a growing emphasis on biodiversity and environmental dependencies.

These developments represent an important evolution in how corporate and investment banking (CIB) divisions approach risk management, emphasizing the integration of sustainability into traditional frameworks.

The challenges of risk management have always been at the core of CIB divisions, driving decisions about which corporations to lend to, which deals to underwrite, and how to optimize capital allocation. Now, the challenge is evolving: sustainability considerations must become an integral part of these frameworks.

The implementation of such considerations is far from straightforward. ESG risk assessments hinge on two critical factors: the availability of robust data and the ability to contextualize it effectively. Without both, the integration of sustainability into risk management will remain incomplete.

Solving the Data Availability Puzzle

A critical component of integrating ESG risks into risk management frameworks is ensuring the availability of high-quality, reliable data. For banks, this requires robust internal data collection processes and the integration of external ESG data sources.

Global Frameworks Driving Standardization

Though banks have historically found it difficult to access the data required to draw actionable insights, the picture is improving. This is partly due to efforts by regulators and standard setters that bring greater consistency and improve data availability.

The EU Taxonomy, for example, has become a blueprint for companies to report how their activities align with environmental objectives, such as Climate Change Mitigation and Adaptation. This framework has inspired similar initiatives in other regions.

Within the EU, the Corporate Sustainability Reporting Directive (CSRD) and the associated European Sustainability Reporting Standards (ESRS) are further driving the standardization of data and the increase of data availability. By next year, the CSRD’s scope will expand from around 3,000 corporations to over 40,000, exponentially increasing the pool of standardized data.

Outside of the EU, global initiatives are gaining traction. The International Sustainability Standards Board (ISSB) published its IFRS S1 and S2 guidelines for sustainability and climate-related reporting. Many jurisdictions globally are implementing the ISSB standards. For example, the Chinese Ministry of Finance (MOF) recently released the Sustainability Disclosure Standards for Business Enterprises – Basic Standard, based on the S1 standard.

The Challenge of Scalability

Despite these advancements, the sheer volume of data and the need for efficient collection present ongoing challenges. Advances in data analysis, natural language processing, and estimation methods are improving data coverage and quality. Additionally, innovative software tools are helping banks fill data gaps by enabling them to gather their own data in a methodologically sound and scalable way.

Transforming Raw Data into Actionable Insights

Data alone is not wisdom. For corporate and investment banks, making decisions based on ESG data requires transforming raw figures into actionable insights by placing them in the right context.

Turning Data into Wisdom

The DIKW hierarchy (Data, Information, Knowledge, Wisdom) illustrates this journey. Data must first be interpreted to form information, enriched by understanding to create knowledge, and finally distilled into wisdom to guide decisions.

Figure 1. The DIKW Hierarchy

Take, for example, a CIB division evaluating a company with significant CO2 emissions. To determine whether the company poses too great a risk to work with, the bank may need to know:

• What sector does the company operate in?
• What is its carbon intensity (i.e., are the emissions proportionate to its size)?
• How has the company’s carbon intensity changed over time?
• What is the nature of the business relationship? Is the company raising funds to invest in a green project? Is it looking to divest a highly polluting subsidiary? Is it trying to acquire a better-performing one?

Without answers to these questions, the data alone is insufficient for making informed decisions.

The Old Way: Manual Analysis

Traditionally, ESG analysts in CIB divisions relied on manual processes to answer such questions. They would pull out the annual report of the company, log in to their ESG data provider, and start reading, taking notes, and drafting a report or recommendation. These reports were then presented to risk committees for a final decision—a time-intensive process that limited the scope and depth of analysis.

The New Way: AI-Driven Contextualization

Today, advances in generative AI have made it possible to convert these reports and data into Retrieval-Augmented Generation (RAG) systems. These tools convert text into meaning and allow analysts to ask questions and find the right context.

The result is that an ESG analyst can now cover more companies or make deeper analyses of a given company in the same time frame. Concerns about hallucinations are addressed when the system is integrated into an existing sustainability database, as it can ring-fence, or isolate, the data it reads from, provide links to the source, and validate the insights itself.

Sustainability as a Strategic Advantage for Corporate and Investment Banking

Thanks to recent advancements in technology, complying with new regulations has become more manageable. By addressing challenges in ESG data availability and with the help of generative AI, banks are turning regulatory obligations into opportunities for innovation and value creation.

With reliable data and AI-driven tools, analysts can evaluate client risk profiles more precisely. These advancements enable smarter lending decisions that align with both regulatory requirements and long-term strategic goals.
In addition, these tools allow banks to proactively support their clients in their sustainability journeys, forming partnerships with businesses that demonstrate strong ESG performance. They also help identify and mitigate risks in environmentally sensitive or high-emitting sectors, ensuring a balanced approach to sustainable finance.

Integrating sustainability assessments into risk management is no longer just about compliance—it is now a strategic advantage for banks to drive long-term resilience and growth.