AI against Carbon Impact

🌆 About the Challenge

We’d all like to live the most sustainable life possible. But being mindful of our impact on the environment is only effective with a detailed understanding of the consequences of our actions. No measurement, no control. Luckily, we are living in a time where technology is rapidly evolving to help us gain that understanding.

In AI against Carbon Impact we are trying to build a machine learning model that estimates the carbon impact of people’s purchases through their bank transactions. Having such a tool means that, besides helping you make better financial decisions, your bank statements can also help you live more sustainably.

Yayzy has a carefully researched classification system to divide bank transactions up into about 90 categories. They also recognize transactions from over 30,000 retailers worldwide. Knowing the type of transaction, the amount of money transferred is multiplied with a weighing factor to determine carbon impact. The only trouble is: there’s much more than 30,000 retailers worldwide, so in some cases it’s necessary to estimate which category a transaction belongs to and you guessed it: that’s a task ideally suited to machine learning.

🎯 GOAL: Build an accurate and robust natural language model that can classify and predict the estimated carbon footprint of a single transaction.

By providing insight into consumer patterns we can help people make more sustainable choices. We will be using NLP to classify the type of transaction, eg. “Food & Dining”, “Shopping”. We use this information to predict the CO2 emissions.

In this challenge, we will