Engineering Carbon Credits Towards A Responsible FinTech Era: The Practices, Implications, and Future
Not on the map. Why?
Abstract (arXiv)
Carbon emissions significantly contribute to climate change, and carbon credits have emerged as a key tool for mitigating environmental damage and helping organizations manage their carbon footprint. Despite their growing importance across sectors, fully leveraging carbon credits remains challenging. This study explores engineering practices and fintech solutions to enhance carbon emission management. We first review the negative impacts of carbon emission non-disclosure, revealing its adverse effects on financial stability and market value. Organizations are encouraged to actively manage emissions and disclose relevant data to mitigate risks. Next, we analyze factors influencing carbon prices and review advanced prediction algorithms that optimize carbon credit purchasing strategies, reducing costs and improving efficiency. Additionally, we examine corporate carbon emission prediction models, which offer accurate performance assessments and aid in planning future carbon credit needs. By integrating carbon price and emission predictions, we propose research directions, including corporate carbon management cost forecasting. This study provides a foundation for future quantitative research on the financial and market impacts of carbon management practices and is the first systematic review focusing on computing solutions and engineering practices for carbon credits.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 124 references that are in the map. First posted on arXiv 22 Dec 2024.
Builds on
4 of 124 references.
References · 4
- 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166
- 2015Structured Pruning of Deep Convolutional Neural Networkscited by 149
- 2020Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Casecited by 129
- 2024Empirical wavelet transformcited by 6
Built on by
Not cited yet.