Finance & Economics Tracks > Track 10: AI, Machine Learning and Deep Learning in Finance & Economics - Unveiling New Frontiers for Research and Practice

Track Chairs:

  • Dr. AbdelKader EL ALAOUI, Rabat Business School, International University of Rabat, Morocco, abdelkader.elalaoui@uir.ac.ma  
  • Dr. Boujemâa ACHCHAB, Hassan 1st University, Berrechid, Morocco

 

The field of AI has a wide range of applications in Finance & Economics and is expanding very rapidly as a subset of computer science. As the amount of data available continues to grow, these techniques are more likely to constitute an essential discipline by shaping the future of Economics and financial system. Its innovative aspect is attracting interest of researchers who may suggest new horizons by exploring its multifaceted dimensions.

Within The RBS 2024 conference, this track will provide an opportunity for researchers, PhD students and experts to present their innovative research, exchange ideas, and foster collaboration on critical applications and issues pertaining to AI and their implications for financial and economic aspects.

We invite researchers to contribute with papers focusing on different aspects and applications of AI, conversational AI in finance, Machine Learning and Deep Learning in Finance & Economics by unveiling new frontiers for research and practice in the field, fostering both theoretical and empirical contributions.

 Papers may address, but are not limited to, the following list of potential topics:

  • Machine and deep learning algorithms in the price predictions in financial markets.
  • Machine learning algorithms applied to risk management.
  • Managing credit risk by using AI techniques
  • Detection of fraudulent activities in financial transactions using ML/DL
  • Trading strategies and automated trading systems based on financial data analysis using DL/ML
  • Portfolio management and optimization based on ML/DL
  • Efficient allocation of assets (equities/Bonds/derivatives) using AI algorithms
  • Natural Language Processing (NLP) applied identify trends and sentiment related to financial markets and individual companies by analyzing news articles, social media posts, and other sources of text data.
  • Using AI to Identify anomalies in credit card transactions or detect patterns of suspicious activity in banking accounts.
  • Role of Generative AI – GAI - (such as ChatGPT, Google Bard, Chinchilla, Adam, Wessel, Benlian and their Emerging competitors) in the field of Finance
  • Impact of GAI on business and investors behavior
  • Effect of GAI on wealth management, investment recommendations and personal finance
  • Risk management and financial planning using GAI,
  • Financial applications and Innovations of GAI
  • Regulation and legal framework of GAI versus its ethicality in finance, business, and economics
  • GAI in banking and finance: theories, state of art and future directions for research
  • Interactions between blockchain, big data and GAI
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