Committee Meeting, Free for Members, Group Meeting, Interest Group, Interest Group Meetings, Quantitative Investing, Virtual Events & Programming

Quantitative Investing Group Meeting

Friday, May 7 | 12:00 PM - 1:30 PM

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Cvent Transition Guide

Overview

The impact of “AI/ML” in capital markets is growing. However, pure outperformance requirements have expanded to include more robust, explainable, trustworthy, sustainable, efficient, transparent, and simply larger AI/ML models that open a new era of model building. New algorithms, approaches, risk management techniques, governance and infrastructures can help address this.

Jochen will give an overview and present some use cases, one of which is based on a project with Munich Re Markets on robust accelerated portfolio construction and market data generators, recently published in the Journal of Financial Data Science. Another use case targets explainable, trustworthy AI with an application in credit scoring. Jochen will also present the underlying energy-efficient enterprise platform for high-performance computing and AI/ML at scale, as well as some related open-source initiatives to democratize AI supercomputing.

Last, Jochen will describe some sustainable/green finance technologies such as GeoAI and ESG-NLP.

Quantitative Investing Group

Guest Speaker

Dr. Jochen Papenbrock

Based in Frankfurt, Germany, Jochen has spent the last 15 years in various roles on the topic of AI in Financial Services, as a thought leader, implementer, researcher and ecosystem shaper.

He is a financial data scientist and received his degree and PhD from the Karlsruhe Institute of Technology (KIT). As a consultant, entrepreneur and researcher he worked with well-known asset managers, banks, insurance companies and central banks. He is a manager at NVIDIA and works with partners, communities, and developers in financial services in Europe and also in some global teams.

Jochen is board member of the EU Horizon 2020 project ‘FIN-TECH’, specialty chief co-editor (Co) at Frontiers ‘AI in Finance’, and project leader in GAIA-X. He has published on AI and quantitative finance in Journal of Financial Data Science, Journal of Investment Strategies, Financial Markets and Portfolio Management, Quantitative Finance, Applied Financial Economics, Frontiers Journal of AI in Finance and Journal of Network Theory in Finance.