Enhancing Climate Risk Forecasting in Financial Markets through Advanced - Data Engineering Techniques
Abstract: As climate change introduces uncertainties into financial markets, forecasting climate - related risks has become essential for financial institutions. This paper explores how data engineering techniques can improve climate risk forecasting by integrating environmental and financial datasets, building scalable data pipelines, ensuring data quality, and adopting security measures. These strategies enhance prediction accuracy, enabling financial institutions to mitigate climate - related financial risks effectively. The study highlights the critical role of data engineering in strengthening financial resilience and fostering sustainable financial practices in an era of growing environmental uncertainty.
Keywords: Climate Risk Forecasting, Data Engineering, Financial Market Stability, Data Governance, Predictive Analytics
How to Cite?: Rohit Nimmala, Jagrut Nimmala, "Enhancing Climate Risk Forecasting in Financial Markets through Advanced - Data Engineering Techniques", Volume 14 Issue 2, February 2025, International Journal of Science and Research (IJSR), Pages: 70-74, https://www.ijsr.net/getabstract.php?paperid=SR25130032204, DOI: https://dx.doi.org/10.21275/SR25130032204