Reply FS Breakfast Sessions Series: Green Finance Summary

As part of the Reply FS Breakfast Series, Cortex Reply hosted a session focusing on ESG in the Financial Services Industry (FSI), highlighting the contributions of GreenOps and artificial intelligence within this domain.

We had industry experts across the regulatory, AI, and FinOps domains: Frank Contrepois (Co-host of “What’s new in Cloud FinOps”); Ferenc Domrose (Senior Consultant); Anthony Ma (Senior Manager), and Abi Wareing (Partner of Cortex Reply).

ESG stands for Environmental, Social, and Governance and is a framework used to assess the sustainability and ethical impact of a company's operations and investments. Whilst the acronym was referenced a lot throughout the panel discussion, our focus was on the E, environment.  The aim of the session was to explore how the industry can meet ESG sustainability goals while accelerating their digital transformation.

The session was split across three core themes:

·       Why is ESG important now?

·       In what ways can artificial intelligence support ESG initiatives?

·       What measures can be taken to ensure the sustainable use of AI within ESG processes?

This article will provide an overview of the key points discussed across the three themes, but for a shorter read, the core takeaways were:

·       ESG is now at the centre of financial services strategy - driven by investors, regulators, and public pressure, ESG is no longer a side issue.

·       When used responsibly, AI can improve ESG efficiency and accuracy,  allowing FS to successfully scale processes and adopt the increasing reporting requirements.

·       Adopt a dual lens: Accelerate ESG ambitions with Al while ensuring the technology itself embodies the sustainability principles it supports.

·       GreenOps is a practice you can leverage to improve your ESG initiatives as well as support the sustainable application of Al.

·       Organisational collaboration is essential; developing AI and technology strategies requires input from multiple stakeholders. In addition to core teams from business, technology, and security, it is important to involve ESG and sustainability teams to ensure sustainable alignment with overall business objectives.  

Why is ESG important now?

ESG is critical now due to shifting investor priorities, regulatory landscapes, and societal expectations, all of which shape the future of sustainable business practices.

Regulatory pressure:

·       Governments and regulatory bodies are implementing stricter regulations around sustainability and corporate responsibility, pushing companies to adopt ESG standards.

·       Such frameworks and regulations include; EU Sustainable Finance Disclosure Regulation (SFDR); Task Force on Climate-related Financial Disclosures (TCFD); International Financial Reporting Standards (IFRS) on Sustainability.

·       To support these new regulations, Green taxonomies and other guidelines are being produced to define what constitutes sustainable economic activities, guiding investors and companies toward environmentally friendly practices.

Public Pressure:

·       Increasing awareness of global issues like climate change means that businesses are being held accountable for their impact on society.

·       Consumers are becoming more conscious of the ethical implications of their purchases. Brands that align with ESG principles often enjoy enhanced loyalty and market share.

·       A strong ESG commitment can enhance a company's reputation, attracting talent and customers who prioritise sustainability and ethical governance.

·       Employees have more motivation to enhance the environmental impact of their work compared to improving the financial efficiency of their organisation.

Rapid Technology Adoption:

·       The rise of ESG’s importance is set against the backdrop of rapid technology advancements and adoption.

·       As the appetite for computational power grows, so too does the energy consumption required to fuel innovation.

·       AI not only presents opportunities for operational improvements but also amplifies the need for responsible governance and sustainable practices, making ESG a focal point for businesses leveraging these technologies.

Challenges to be aware of:

·       Greenwashing - Companies may overstate or misrepresent their ESG efforts, undermining trust and leading to increased scrutiny from regulators and stakeholders.

·       Regulatory Complexity and Fragmentation - The evolving landscape of ESG regulations varies widely by region and sector, creating compliance challenges and uncertainty for businesses

·      Data accessibility – data is scatted, lacks standardisation and there are concerns over measurement’s reliability

In what ways can artificial intelligence support ESG initiatives?

AI accelerates, enriches, and simplifies ESG processes by automating complex tasks, generating actionable insights, and enhancing communication and compliance.

Process Efficiency and Scalability

·       We are facing an unprecedented explosion in ESG related data. It's not just about volume but also the variety of data types and sources. 

·       AI is not just useful, but transformative. Traditional methods cannot keep up with the scale and complexity. AI, especially generative AI, can processes this vast diverse data rapidly and accurately.

Reporting and Communication

·     Interactive ESG dashboards provide real time data visualisation, allowing stakeholders to see up to date ESG performance metrics with capabilities to explore data in depth

·     AI enables tailored ESG reports and communications for different audiences (investors, regulators, customers), enhancing relevance and engagement.

·     Chatbots can provide insights and education around ESG reporting, fostering more engaged and informed stakeholders.

Challenges to consider:

·       Quality of Data - AI’s effectiveness depends on high-quality, comprehensive ESG data, which is often fragmented, incomplete, or inconsistent.

·       Bias -  AI models can inherit or amplify biases present in training data, particularly affecting social and governance aspects, potentially leading to unfair outcomes.

·       Environmental Impact - Training and running AI models consume substantial energy, potentially conflicting with environmental sustainability goals.

How do we ensure that we use AI in a sustainable way when leveraging it for ESG processes?

While GenAI holds promise for various applications, its environmental impacts warrant careful consideration and mitigation strategies to ensure sustainable practices in its development and deployment.

·       Collaboration is key - collaboration between AI and ESG teams is essential to integrate sustainability into AI strategies effectively, manage risks, and maximise positive impact.

·       GreenOps - GreenOps enhances AI sustainability by optimising energy use, leveraging cleaner power, managing resources efficiently, and providing transparency to reduce environmental impact.

In summary, the session emphasised ESG’s rising importance, AI’s transformative potential in ESG, and the need for sustainable, collaborative approaches supported by GreenOps to achieve lasting impact in the financial services industry.