Background: In the face of climate change and the increasing demand for corporate accountability, efficiently evaluating the sustainability information disclosed in annual reports is becoming an urgent need. The challenge is to create an AI-supported tool that can parse through complex data and pinpoint ESG metrics, particularly greenhouse gas emissions, in order to highlight unsustainable practices and enhance the decision-making process for investors and policymakers.

Objective: The goal is to develop an AI-based software that automates the analysis of annual financial statements, extracting and evaluating ESG data to provide a clearer picture of corporate sustainability, with a particular focus on the European context. Moreover, sustainable and smart mobility solutions should be proposed to the analyzed companies.

Challenge Statement: Participants are challenged to conceive an AI system that not only extracts precise ESG-related data but also verifies and evaluates it against sustainability benchmarks. The system should feature an intuitive user interface allowing diverse user groups to efficiently categorize and assess ESG criteria, with the long-term adaptability to handle growing data volumes.

Data Set: Participants will work with a collection of sample annual reports, ESG reports, and relevant CSV files containing sustainability data from European companies.

Expected Deliverables:

• A working prototype for analyzing financial statements and identifying key ESG metrics.

• Documentation of AI and ML methodologies, algorithmic processes, and technological implementation details.

• A functional user interface designed for diverse target audience needs.

• A scalability and development roadmap, offering a vision for further software advancement.

• A pitch presentation outlining potential applications, long-term vision, and the tool’s contribution to sustainable business practices.

Criteria for Evaluation:

• The accuracy and precision of ESG data extraction, with a focus on greenhouse gas emissions.

• The robustness of data verification and sustainability evaluation mechanism implemented.

• The usability and functionality of the user interface for different stakeholders.

• The ability of the software tool to manage large data sets and incorporate new data effectively.

• Consideration of ethical data use and compliance with European data protection standards.

• The depth of documentation and clarity of the pitch, including demonstration of potential use cases for the software.

Resources: Participants will have access to:

• A curated set of financial and ESG reports from European companies in various industry sectors.

• A software development kit (SDK) with AI and ML frameworks tailored for data analysis.

• A virtual environment replicating European data protection compliance requirements