What we’re about
The Thalesians are a group of dedicated professionals with an interest in Artificial Intelligence (AI) / Machine Learning (ML), quantitative finance, economics, mathematics, physics and computer science, not necessarily in that order. We currently run events London, New York, Budapest, Frankfurt and Prague!
Please also visit our main Thalesians web page here too to learn more about us!
The Thalesians are a member of Level39 - Europe's largest technology accelerator for finance, retail, cyber-security and future cities technology companies.
We consult, train, and write software. Our offering can be found on http://ai.thalesians.com/
Our GitHub page contains our open source Python financial analysis library PyThalesians.
If you are a full-time student, between jobs, or for any other reason would struggle with our Meetup dues, please let us know and we'll mark you as exempt from them!
Upcoming events (1)
See all- Hybrid Event - Dr. Cristian Bravo, Deep Learning Multimodal Data Analysis140 W 62nd St, New York, NY
IAQF & Thalesians Seminar Series: Leveraging Deep Learning for Multimodal Data Analysis in Credit Risk Assessment. A Seminar by Dr. Cristián Bravo.
6:00 PM Seminar Begins
7:30 PM Reception
Hybrid Event:Fordham University
McNally Amphitheater
140 West 62nd Street
New York, NY 10023Free Registration!
For Virtual Attendees: Please email web@iaqf.org for the linkAbstract:
Credit risk assessment is a multifaceted process in which lenders employ various measures to evaluate the risk associated with borrowers, ranging from individual consumers to large-scale companies. To achieve a comprehensive understanding of credit risk, lenders extensively analyze a wide array of data sources, encompassing images, text, social networks, time series data, and traditional financial variables. Deep learning methodologies offer significant advantages in leveraging diverse data from multiple sources to generate accurate predictions and provide valuable insights into the complex relationships inherent in these inputs.
This presentation aims to explore different strategies for handling multimodal data in both consumer and corporate lending using deep learning techniques, with a particular emphasis on transformer models. The discussion will encompass the utilization of time series data, ego networks, and textual information, in conjunction with conventional financial variables. Real-world use cases will be presented to showcase the predictive gains obtained through multimodality and demonstrate the valuable insights that can be extracted from these diverse data sources.
Furthermore, the talk will address the challenges and solutions associated with deploying these models in credit risk assessment. It will shed light on the potential pitfalls that can arise when working with multimodal data and outline effective approaches to mitigate these issues. By the end of the presentation, participants will have a better understanding of the power of deep learning techniques in analyzing multimodal data in this space, enabling them to make informed decisions and enhance their lending practices.Bio:
Dr. Cristián Bravo is an Associate Professor and Canada Research Chair in Banking and Insurance Analytics at the University of Western Ontario, Canada. He also serves as the Director of the Banking Analytics Lab. His research lies at the intersection of data science, analytics, and credit risk, researching how techniques such as multimodal deep learning, causal inference, and social network analysis can be used to understand relations between consumers and financial institutions. He has over 75 academic works in high-impact journals and conferences in operational research, finance, and computer science. He serves as an editorial board member in Applied Soft Computing and the Journal of Business Analytics and is the co-author of the book “Profit Driven Business Analytics”, which has sold over 6,000 copies to date. Dr. Bravo has been quoted by The Wall Street Journal, WIRED, CTV, The Toronto Star, The Globe and Mail, and Global News. He is also a regular panelist at CBC News’ Weekend Business Panel where he discusses the latest news in Banking, Finance and Artificial Intelligence. He can be reached via LinkedIn, by Twitter @CrBravoR, or through his lab website at https://thebal.ai.
