At the recent Cypher 2023 conference, a trio of experts from MathWorks—Prashant Rao, Arpit Narain, and Rahul Krishnan—delved into the intricate world of Quant Modeling, AI, and Model Governance. The session was a deep dive into how these technologies are shaping the financial landscape, with a particular focus on Environmental, Social, and Governance (ESG) factors.
The Importance of ESG
The speakers emphasized the critical role of ESG in today’s financial world. They discussed how ESG is not just a buzzword but a necessity, impacting everything from climate change to social responsibility. The team argued that working on ESG is impactful and should be considered a priority, not just from an ethical standpoint but also from an investor’s perspective.
Collaboration is Key
One of the key takeaways from the session was the importance of collaboration. The speakers pointed out that solving ESG problems requires a multi-disciplinary approach, involving not just financial experts but also climate scientists, philosophers, and more. This collaborative effort is essential both at the industry level and within organizations.
Model Monitoring in ESG
When it comes to model monitoring, especially in the context of ESG, the speakers highlighted several key parameters. These include data and performance drift for AI models, volatility impact for market risk in trading models, and regime shifts for low-frequency models. The idea is to have a comprehensive monitoring system that can adapt to the specific needs and challenges of ESG modeling.
The Role of Technology
The MathWorks team also discussed the role of apps and tools as enablers in this journey. While technology can facilitate the process, the real change comes from a shift in perspective. The speakers emphasized that technology should be seen as a means to an end, helping to drive both monetary benefits and meaningful change.
The session concluded with an interactive Q&A, where the speakers addressed various technical and industry-specific questions. Overall, the talk provided valuable insights into the complexities and opportunities in leveraging Quant Modeling and AI for better model governance, particularly in the realm of ESG.