AI solution to understand the investment strategy from the ESG expertise team and help our clients systematically integrate ESG criteria in their fundamental analysis, valuations and recommendations.

Societe Generale welcomes you to participate in a cutting-edge opportunity that challenges your skills and creativity in the field of artificial intelligence and problem-solving. The ESG Assistant is a cutting-edge AI solution that empowers investment professionals to make more informed, sustainable, and socially responsible investment decisions. By seamlessly integrating the expertise of ESG professionals with advanced data analytics, this tool facilitates a deeper understanding of ESG factors and their impact on investment strategies, ultimately driving better financial outcomes while aligning with ethical and sustainability goals.

Theme: The ESG Assistant is an innovative AI-powered solution designed to enhance the understanding of investment strategies within the context of Environmental, Social, and Governance (ESG) criteria. This tool serves as a valuable resource for financial institutions and investment firms by leveraging the expertise of ESG professionals and facilitating the systematic integration of ESG considerations into their fundamental analysis, valuations, and investment recommendations.

Problem Statement: Participants will be tasked with two pivotal objectives:

Comprehensive ESG Data Integration: A critical objective is to ensure the seamless integration of a wide range of ESG data from diverse sources. This includes environmental impact data, social responsibility metrics, corporate governance practices, and sustainability indicators. By consolidating and standardizing this data, the ESG Assistant can provide a holistic view of ESG performance for companies and investments, allowing for accurate analysis and informed decision-making.

AI-Driven Decision Support: Another key objective is to leverage artificial intelligence and machine learning to develop an advanced decision support system. The ESG Assistant should be capable of processing and analyzing vast amounts of ESG data to extract meaningful insights. It should help investment professionals identify correlations between ESG factors and financial performance, assess ESG-related risks and opportunities, and provide personalized investment recommendations. The AI-driven system should continually learn and adapt to evolving ESG trends and client preferences, ensuring that it remains a valuable resource for making informed investment decisions.

Submission Requirements: Participants are expected to submit the following components:

Approach Note: A comprehensive document outlining the approach taken, methodologies used, and the thought process behind the solution.

Solution Video: A video presentation providing an overview of the solution, including its features, functionality, and the role of AI as ESG Assistant

GIT Repository File: A repository containing the source code, documentation, and any other relevant materials that showcase the implementation of the solution.

Presentation File: A presentation slide deck that concisely communicates the architecture, technology frameworks, technical stacks, core concepts, design, functionalities, and outcomes of the solution.

Note to Participants: Participants are encouraged to leverage any technology, framework, or open-source resources as required to craft their solutions. The emphasis lies on innovative problem-solving and practical application.