Call for participation

February 7th, 8:30am-6pm EST

NEW: Schedule & Invited talks

Goal of the bridge

The community of researchers at the intersection of AI and Finance has been growing steadily, but can benefit from increased exposure, especially at premier AI venues like AAAI.  Three years ago, a new conference was established with ACM: The ACM International Conference on AI in Finance (ICAIF). Since that time, ICAIF has been the major forum of discussion and exchange of research ideas in the use of AI in financial applications. Now, it is the right time for the whole AI community to consider addressing the open questions in the use of AI in this domain. 

The goal of this bridge is to bring together AI researchers and practitioners from industry and academia, to share technical advances and insights of the application of AI techniques to financial services in the private sector. The target audience is AI researchers that are actively working on the use of AI in financial private institutions as well as researchers that would like to explore the potential application of their work to this domain. From the industry side, we are open to the participation of researchers or professionals that would like to understand the potential application of AI to their business.

Note: This bridge aims to foster collaboration and a productive exchange of ideas and experiences among private entities with an economic role; conversely, if you work for a public financial institution, you will find a suitable forum in the companion AAAI-23 bridge titled “AI and Financial Institutions”, to which you are encouraged to submit.

Schedule

8:30 Welcome: Tucker Balch and Daniel Borrajo, J.P. Morgan AI Research

8:40 Invited talk: An overview of some strengths and limitations of AI/ML. Larry Wall, Federal Reserve Bank of Atlanta 

9:25 Tutorial. Deep Reinforcement Learning for Quantitative Trading. Bo An

10:25 Oral presentation. Visual Information in the Age of AI: Evidence from Corporate Executive Presentations. Meng Wang

10:40 Coffee break

11:10 Panel. Simulation and modelling. Meng Wang, Isaac Tamblyn, Tony Yin, Xiao-Yang Liu, Zhen Zeng

11:40 Tutorial. Multiagent Systems for Representing and Enacting Financial Contracts. Amit K. Chopra, Samuel H. Christie V, Munindar P. Singh

12:40 Lunch

13:40 Invited talk: Exploring the intersection of financial services and AI: opportunities and challenges. Andrea Stefanucci, J.P.Morgan AI Research

14:25 Oral presentation. PFPT: a Personal Finance Planning Tool by means of Heuristic Search. Kassiani Papasotiriou

14:40 Panel. Planning and Reinforcement Learning. Kassiani Papasotiriou, Berend J.D. Gort, Sunandita Patra

15:10 Oral presentation. StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series. Jean Lee

15:25 Coffee break

16:00 Invited talk: Detecting Market Manipulation and Protecting Investors Using ML/AI. Chi-Keung Chow, FINRA

16:45 Oral presentation. Managerial Risk Assessment and Fund Performance: Evidence from Textual Disclosure. Sean Cao

17:00 Panel. Natural Language Processing. Jean Lee, Sean Cao, Youngseok Moon, Jared Sharpe

17:30 Panel. Open challenges and increasing collaboration between AI and Financial Services. Vivek Agarwal, Bo An, Chi-Keung Chow, Amit Chopra

18:30 Closing remarks

Invited talks

Accepted papers

Evaluating Feature Attribution Methods for Credit Risk Assessment Models

Allan Anzagira (JPMorgan Chase), Saumitra Mishra (JPMorgan Chase), Freddy Lecue (JPMorgan Chase), Daniele Magazzeni (JPMorgan Chase)

An NFT Collectibles Recommender System with Content Features

Minjoo  Choi (UNIST); Seonmi Kim (UNIST); Yejin Kim (UNIST); Youngbin Lee (UNIST); Joohwan Hong (UNIST); Yongjae Lee (UNIST)*

Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting

Berend J.D. Gort (Columbia University); Xiao-Yang Liu (Columbia University); Jiechao Gao (University of Virginia); Shuaiyu Chen (Purdue University); Christina Dan  Wang (New York University Shanghai)

Massively Parallel Market Simulator for Financial Reinforcement Learning

Jiashu Han (Columbia university); Ziyi Xia (Columbia University); Xiao-Yang Liu (Columbia University); Chuheng Zhang (Microsoft Research); Zhaoran Wang (Northwestern U); Jian Guo (IDEA Research)

Stock Portfolio Management by Using Fuzzy Ensemble Deep Reinforcement Learning Algorithm

Zheng Hao (State University of New York at Oswego)

Index Tracking for Direct Indexing Services: A Deep Representation Learning Approach

Sohyeon Kwon (UNIST); Juchan Kim (UNIST); Seyoung Kim (UNIST); Junhyeong Lee (Ajou University); Yongjae Lee (UNIST)*

StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series

Jean Lee (The University of Sydney); Hoyoul Luis Youn (KPMG); Josiah Poon (The University of Sydney); Soyeon Han (University of Sydney)

Towards Asset Allocation Using Behavioural Cloning and Reinforcement Learning

Mahmoud Mahfouz (J.P. Morgan AI Research); Sriram Gopalakrishnan (J.P. Morgan AI Research ); Miguel Suau (TU Delft); Sunandita Patra (J P Morgan AI Research); Danilo P. Mandic ((Imperial College of London, UK)); Daniele Magazzeni (J.P. Morgan AI Research); Manuela Veloso (J.P. Morgan AI Research )

Machine Readership and Financial Reporting

Youngseok Moon (Georgia State University); Ying Liang (Georgia State University); Sean Cao (University of Maryland)

PFPT: a Personal Finance Planning Tool by means of Heuristic Search

Alberto Pozanco (JP Morgan); Kassiani Papasotiriou (JPMC); Daniel Borrajo (J.P. Morgan AI Research and Universidad Carlos III de Madrid)

Topic Analysis of SEC Letters for Initial Public Offerings

Jared Sharpe (University of Delaware); Keith Decker (University of Delaware)

fintech-kMC: Agent based simulations of financial platforms for design and testing of machine learning systems

Isaac Tamblyn (Block); Tengkai Yu (Block); Ian Benlolo (Block)

Online Prediction of Order Flow with Bayesian Change-Point Detection Methods

Ioanna-Yvonni Tsaknaki (Scuola Normale Superiore); Fabrizio Lillo (Università di Bologna); Piero Mazzarisi (Scuola Normale Superiore)

Visual Information in the Age of AI: Evidence from Corporate Executive Presentations

Sean Cao (Georgia State University), Yichen Cheng (Georgia State University), Meng Wang (Georgia State University), Yusen Xia (Georgia State University), Baozhong Yang (Georgia State University)

[Extended Abstract] FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning

Ziyi Xia (Columbia University); Xiao-Yang Liu (Columbia University); Jingyang Rui (The University of Hongkong); Jiechao Gao (University of Virginia); Hongyang Yang (Columbia University); Ming Zhu (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences); Christina Dan  Wang (New York University Shanghai); Zhaoran Wang (Northwestern University); Jian Guo (IDEA Research)

Limit Order Book Forecasting with Latent Dynamics

Tony Yin (JP Morgan); Yufei Wu (J.P. Morgan AI Research); Michael Cashmore (JP Morgan); Daniele Magazzeni (J.P. Morgan AI Research)

Financial Time Series Forecasting using CNN and Transformer

Zhen Zeng (J.P. Morgan AI Research); Rachneet Kaur (J.P. Morgan AI Research ); Suchetha Siddagangappa (J.P. Morgan AI Research); Saba Rahimi (J.P. Morgan AI Research); Tucker Balch (JP Morgan); Manuela Veloso (J.P. Morgan AI Research )

Managerial Risk Assessment and Fund Performance: Evidence from Textual Disclosure

Alan Zhang (Florida International University); Sean Cao (Univ of Maryland); Baozhong Yang (Georgia State University)

Submissions

The bridge would like to receive different types of submissions:

• Tutorials that introduce the main open problems within AI/financial applications. Send proposals of tutorials to daniel.borrajo@jpmchase.com. They should include

  • Topic of tutorial

  • Description of its contents

  • Names and short bios of presenters

  • Length (up to two hours)

• Original short papers that showcase the current state of the application on AI in financial services. They should be 4 pages long in AAAI format. We encourage students to submit their current work

• Papers published in other venues. We require authors to upload an extended abstract of 2 pages specifying in which venue the paper was accepted.

Papers will be reviewed using a double blind process. Please, remove any reference to authors in the paper. The page limits apply to the inclusion of any appendices or supplementary material to the paper which should be submitted in the same PDF.

Papers Format: https://www.aaai.org/Publications/Templates/AnonymousSubmission23.zip

Link to submissions: CMT platform (https://cmt3.research.microsoft.com/AIFinBridge2023/Submission/Index)

Important Dates

Submissions due: November 23, 2022

Notification to authors: December 16, 2022.

AAAI early registration deadline: January 5, 2023

Bridge at AAAI: February 7, 2023. 8:30am-6pm

Topics

All different types of submissions accept contents on topics that are relevant to general financial problems that may include but are not limited to:

• Generative models and data-driven simulation

• Planning, Search, Constraint-based Reasoning, Optimization, and Reinforcement learning

• Meta learning, federated learning, representation learning and transfer learning

• Natural language processing

• Time series prediction

• Validation and calibration of financial models

• Multi-agent systems and game-theoretic analysis of financial markets

• Explainability, ethics, and fairness of AI & ML systems

• Security, and privacy of AI & ML systems

• Computational regulation and compliance in finance

• Robustness and uncertainty quantification

Potential applications of interest may include but are not limited to:

• Fraud detection for credit cards and mortgages

• Early detection of firm defaults

• Blockchain and cryptocurrency

• Risk modelling and risk management

• Trading (e.g., optimal execution, market making, smart order routing and hedging)

• Pricing strategies

• Robot-advising and investment recommendations

• Forecasting of financial scenarios

• Financial time series analysis and factor models

• Chatbots, automated analysis of documents

Organizers

• Tucker Balch, Ph.D., Managing Director, J.P. Morgan AI Research, and Adjunct Professor, Georgia Institute of Technology, tucker.balch@jpmchase.com

• Daniel Borrajo, Ph.D., Executive Director,  J.P. Morgan AI Research, and Professor at Universidad Carlos III de Madrid, daniel.borrajo@jpmchase.com

• Julia Stoyanovich, Ph.D., Associate Professor, New York University, stoyanovich@nyu.edu

• Susan Tibbs, J.D., Vice President, Market Regulation, Financial Industry Regulatory Authority, Susan.Tibbs@finra.org

• Manuela Veloso, Ph.D., Managing Director, Head, J.P. Morgan AI Research, and Herbert A. Simon University Professor, Emerita, Carnegie Mellon University, manuela.veloso@jpmchase.com 

• Carmine Ventre, PhD., Professor Computer Science, King's College London, carmine.ventre@kcl.ac.uk

• Larry Wall, Ph.D., Executive Director, Center for Financial Innovation, Federal Reserve Bank of Atlanta, larry.wall@atl.frb.org