The future of Financial Services is open with data and AI at its core.
Welcome data teams and executives in Financial Services! This year’s Data + AI Summit is jam-packed with talks, demos and discussions on how Financial Services leaders are harnessing the power of data and analytics to digitally transform, minimize risk, accelerate time to market and drive sustainable value creation
To help you take full advantage of the Financial Services industry experience at Summit, we’ve curated all the programs in one place.
Highlights at this year’s Summit:
- Financial Services Industry Forum: Our flagship event for Financial Services attendees at Summit featuring keynotes and panel discussions with ADP, Northwestern Mutual, Point72 Asset Management, S&P Global and EY, followed by networking. More details in the agenda below.
- Financial Services Lounge: Stop by our lounge located outside the Expo floor to meet with Databricks’ industry experts and see solutions from our partners including Accenture, Avanade, Deloitte and others.
- Session Talks: Over 15 technical talks and demos on topics including hyper-personalization, AI-fueled forecasting, enterprise analytics in cloud, scaling privacy and cybersecurity, MLOps in cryptocurrency, ethical credit scoring and more.
The full list of Financial Services sessions, talks and demos can be found in the agenda below
In this session, Douglas Hamilton (AVP, Machine Intelligence Lab) and Michael O’Rourke (SVP, Engineering & AI/ML) will show attendees how Nasdaq is building dynamic microstructures that reduce the inherent frictions associated with trading, and give insights into their app...
Time series forecasting has a wide range of applications: finance, retail, healthcare, IoT, etc. Recently deep learning models such as ESRNN or N-BEATS have proven to have state-of-the-art performance in these tasks. Nixtlats is a python library that we have developed to facilitate the use of these state-of-the-art models to data scientists and developers, so that they can use them...
Our journey with Databricks:
- Building a cross functional ML team
- Scoping business problems to get executive buy in
- Conveying a strategic vision for ML at your organization
- Operationalizing ML & Data Science to solve business challenges
- Building clear business objectives for your ML Projects
• Leveraging open source technologies, like Databricks' Delta Sharing, in combination with a flexible data management stack, can allow organizations to be more nimble in testing and deploying more strategies
• Live demonstration of Del...
This session will focus on how Capital One HR Team built a Low Cost Data movement Ecosystem that can source data, transform at scale and build the data storage (Red...