Put AI to work
June 26-27, 2017: Training
June 27-29, 2017: Tutorials & Conference
New York, NY

Schedule: Financial services sessions

Finance has a longer and more intertwined history with data and technology than perhaps any other industry. That trend continues today as AI is integrated into finance applications—from research and trading to wealth managing robo-advisors and automated contract analysis.

11:05am11:45am Wednesday, June 28, 2017
Implementing AI
Location: Gramercy East/West Level: Intermediate
Eric Greene (Think Big Analytics)
Average rating: **...
(2.67, 3 ratings)
Eric Greene compares different approaches to creating models that predict payment amounts, time, and recipient for recurring expenses such as rent, loans, utilities, and services, outlining the data requirements, feature modeling, and neural network architectures that work best, as well as common issues in training and deploying deep learning networks. Read more.
11:05am11:45am Wednesday, June 28, 2017
Implementing AI
Location: Sutton South/Regent Parlor
Jennifer Chu-Carroll (Elemental Cognition)
Average rating: ****.
(4.25, 4 ratings)
Why is reading comprehension hard? Jennifer Chu-Carroll offers an overview of current approaches, explaining where they fall short and what our ultimate expectations should be. Read more.
11:55am12:35pm Wednesday, June 28, 2017
Verticals and applications
Location: Gramercy East/West Level: Intermediate
Aida Mehonic (The Alan Turing Institute)
Average rating: ****.
(4.67, 3 ratings)
Deploying AI across business functions brings benefits that range from the prosaic to game changers, which in turn also depend on the overall digital and data maturity of the organization. Aida Mehonic shares a case study of an investment firm undergoing an AI transformation across several business units, including trading, reporting, and marketing. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Verticals and applications
Location: Gramercy East/West Level: Intermediate
Ron Bodkin (Google), Nadeem Gulzar (Danske Bank Group)
Average rating: ****.
(4.33, 3 ratings)
Fraud in banking is an arms race with criminals using machine learning to improve their attack effectiveness. Ron Bodkin and Nadeem Gulzar explore how Danske Bank uses deep learning for better fraud detection, covering model effectiveness, TensorFlow versus boosted decision trees, operational considerations in training and deploying models, and lessons learned along the way. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Impact of AI on business and society
Location: Beekman Level: Non-technical
Tim Estes (Digital Reasoning)
Average rating: ****.
(4.50, 2 ratings)
As AI moves from concept to reality, debates about ethics are evolving into excitement and the desire to learn more about AI and its promise of a better world. Tim Estes discusses two customer use cases: Nasdaq, which found a way to use AI to help safeguard financial markets, and Thorn, which found a way to use AI to combat human trafficking and rescue children. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Verticals and applications
Location: Sutton South/Regent Parlor Level: Beginner
Francisco Webber (Cortical.io)
Average rating: *****
(5.00, 1 rating)
Financial industries are under increased pressure due to regulations that demand extended information management capabilities. Information largely consists of text data, which forces companies to increase headcount to keep up with the growing workload. Francisco Webber demonstrates how Cortical.io’s semantic folding, a neuroscience-based approach to NLU, helps automate these uses cases. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Implementing AI
Location: Gramercy East/West Level: Intermediate
Thomas Wiecki (Quantopian)
Average rating: ***..
(3.67, 3 ratings)
Expressing neural networks as a Bayesian model naturally instills uncertainty in its predictions. Thomas Wiecki demonstrates how to embed deep learning in the probabilistic programming framework PyMC3 to address uncertainty and nonstationarity. Read more.