Empowering Sustainable Trade: AI-Driven ESG Monitoring and Fraud Prevention in Trade Finance

Leveraging AI and technology-driven solutions to drive positive change in ESG monitoring, trade finance digitization, and fraud prevention. In this 8-week challenge, you will join a collaborative team of 50 AI engineers from all around the world.

The problem

Why are we doing this?

We aim to improve how we assess company sustainability, expose misleading “green” claims, and make trade safer. Our project promises better decision-making, increased corporate honesty, and safer trade processes. Join us in shaping a future where businesses are transparent and responsible.

The Ultimate goal is to craft an AI-driven solution that brings transformative changes in three main areas:

1. ESG Monitoring: ESG stands for Environmental, Social, and Governance factors, often used to measure sustainability. Our goal from this project is to evaluate both big and small companies on these criteria, giving a broader view of their sustainable practices. The current focus on large public companies overlooks smaller entities, limiting a holistic understanding of sustainability impacts.

2. Greenwashing Detection: Some companies claim to be green without truly being sustainable, a practice called greenwashing. Our goal is to create a solution that will detect and highlight these misleading claims, promoting genuine transparency.

The project goals

Develop a tech-driven approach to elevate ESG monitoring, digitalize trade finance, and enhance fraud prevention. Our focus is to create tools and methodologies that will foster a more efficient and transparent business ecosystem.

1. Data Exploration and Collection:

Identify and integrate at least three new data sources beyond the initially suggested ones.

2. Aggregate Data & Assign ESG Scores:

Implement AI to process diverse datasets, and create algorithms that can assign ESG scores to at least 100 entities based on supply chains and manufacturing processes.

3. Combat Greenwashing:

Develop an AI model that achieves at least 85% accuracy in distinguishing genuine sustainability claims from deceptive ones.

4. Extract Financial & Sustainability Metrics:

Use NLP to derive actionable insights from text data, aiming to process and categorize a minimum of 10,000 textual data points.

Why join? The uniqueness of Omdena AI Innovation Challenges

A collaborative experience you never had in your working life! For the next eight weeks, you will not only build AI solutions to make a real-world impact but also go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.

Find more information on how an Omdena project works