ICAIF’21 shows how artificial intelligence is transforming finance
ACM International Conference on AI in Financial Returns by Popular Demand
New York, NY, October 26, 2021 (GLOBE NEWSWIRE) – ACM, the Association for Computing Machinery, will be hosting the 2sd ACM International Conference on AI in Finance (ICAIF’21), virtually November 3-5, 2021. Over 950 people have registered for the inaugural conference, held in 2020.
Advances in artificial intelligence (AI), including machine learning (ML), are being felt across society and the global economy, with some of the biggest impacts occurring in finance: including the markets finance, financial services and the global financial system in general. The ICAIF aims to bring together researchers from various disciplines to share technical advances and insights into the effects of AI and ML on the world of finance.
ICAIF’21 invites high quality articles on theoretical, empirical or experimental research from industry, academia, government and non-profit organizations. Topics explored at ICAIF include financial systems as multi-agent systems; AI techniques for the simulation of markets and economies; computational analysis of financial scenario game theory; ethics and equity of AI in finance; and machine learning for pricing, trading and portfolio management.
This year’s program includes four lectures, six workshops and tutorials, and numerous research presentations.
ICAIF Strong points
Visit here to explore the full ICAIF ’21 program.
“AI in finance: challenges and solutions”
Manuela Veloso, JP Morgan AI Research & Carnegie Mellon University
Veloso will deepen his understanding of the challenges and solutions of combining the fields of AI and finance. It will address issues related to data, learning from experience, business impact, and values, such as the fairness and explainability of AI. She will also share details of specific research and development projects being carried out by her AI research team at JPMorgan Chase.
“The Best New World of Too Much Data: Using Enterprise-Level Microdata to Model the Global Economy”
George Axtell, George Mason University and the Santa Fe Institute
Axtell will first describe dozens of regularities and raw patterns in economic and financial data sets that make it difficult to explain the data. Then, he will propose a new approach to analyze large areas of data using large-scale multi-agent systems. Axtell’s resulting computer model for all U.S. private sector companies is a starting point for understanding the economy as a whole, even if significant amounts of data fall outside of the model yet.
“The biases of learning machines in finance: some examples”
Charles-Albert Lehalle, Imperial College London and Abu Dhabi Investment Authority
Lehalle will examine the role of biases in machine learning algorithms applied to finance applications. He will list the different ways in which AI experts compensate for such biases, drawing on recent research on “AI ethics”. He will conclude by examining the scope of stochastic control: eg what kinds of biases are learned controllers subject to?
“Strength in depth?” Deep learning for finance »
Stephen Roberts, University of Oxford
Roberts will examine some of the concepts behind the advancements in deep learning and highlight his recent work using deep learning for limit order books, dynamic trading, portfolios and execution strategies. , among others.
Thaleia Zariphopoulou, University of Texas at Austin
Zariphopoulou’s area of expertise is financial mathematics and stochastic optimization. She has published extensively in the fields of investing and valuing in incomplete markets and has introduced new approaches to valuing dynamic risk indifference and preferences.
Main Title (to be determined)
WORKSHOP & TUTORIALS
Women in AI and Finance
Time series in finance: representations and learning
AI in Africa for sustainable economic development
Governance, compliance and security of AI in financial services
Natural language processing and network analysis in financial applications
Explainable AI in Finance (XAI)
Contact Jim Ormond at [email protected] for media registration and related inquiries.
ACM, the Association for Computer Machinery, is the world’s largest educational and scientific computing company, bringing together educators, researchers and IT professionals to inspire dialogue, share resources, and address challenges in the field. ACM strengthens the collective voice of the IT profession through strong leadership, the promotion of the highest standards and the recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for lifelong learning, career development and professional networking.
CONTACT: Jim Ormond Association for Computing Machinery (212) 626-0505 [email protected]