NOTIFY ME AS SOON AS REGISTRATION OPENS

Over two days, the Ai4 Finance conference brings together business leaders and data practitioners to facilitate the adoption of artificial intelligence and machine learning technologies.

With a use-case oriented approach to content, our goal is to deliver actionable insights from those working on the frontlines of AI in the enterprise. We try to provide a common framework for thinking about what AI means to the financial services industry and to deliver content that progresses understanding at any stage of an organization’s AI journey. Welcome to our community!                     

     AI FOCUSED

     APPLICATION ONLY

     FINANCE SPECIFIC 

     USE CASE DRIVEN

Over two days, the Ai4 Finance conference brings together business leaders and data practitioners to facilitate the adoption of artificial intelligence and machine learning technologies.

With a use-case oriented approach to content, our goal is to deliver actionable insights from those working on the frontlines of AI in the enterprise. We trie to provide a common framework for thinking about what AI means to the financial services industry and to deliver content that progresses understanding at any stage of an organization’s AI journey. Welcome to our community!                     

     AI FOCUSED

     FINANCE SPECIFIC 

     APPLICATION ONLY

     USE CASE DRIVEN

Hear top use cases for AI in finance. Presentations range from high level insights to highly specific solutions. We focus on covering the industry’s most pressing problems through use cases from business execs and technical leaders who have solved them. See below for a diagram of topics covered.

2 DAYS                                 

Every major application of AI in finance will be covered.

2 TRACKS

Explore the specifics behind the model in a technical talk or the business implications in a non-technical talk.

40+ TALKS

Speakers from the world’s largest banks and from cutting edge startups will take stage.

20+ HOURS OF CONTENT

You’ll have plenty of choices to make sure you’re learning what you need.

Hear top use cases for AI in finance. Presentations range from high level insights to highly specific solutions. We focus on covering the industry’s most pressing problems through use cases from business execs and technical leaders who have solved them. See below for a diagram of topics covered.

2 DAYS 

Every major application of AI in finance will be covered.

40+ TALKS

Speakers from the world’s largest banks and from cutting edge startups will take stage.

2 TRACKS

Explore the specifics behind the model in a technical talk or the business implications in a non-technical talk.

20+ HOURS OF CONTENT

You’ll have plenty of choices to make sure you’re learning what you need.

This year, we’re offering two distinct tracks that differentiate between technical and non-technical discussions. See below to determine which track best fits your interests and goals.

Both tracks will cover all topics listed above either from the perspective of the business exec (Business Track) or data practitioner (Data Track).

TRACK 1                             TRACK 2                            

DATA TRACK

This track was designed for our technical audience. You can expect a deep dive into the specifics of the machine learning models. Most talks during this track will be in a longer 50-minute format. Hear topics including:

  • Scaling to Big Data
  • Model Interpretability
  • Data Privacy and Security
  • Dealing with Biased Data Sets
  • Productionizing Your Model
  • Cloud v Local Environment
  • Unstructured Data
  • Deep Learning
  • Dealing with Legacy Systems
  • Reinforcement Learning
  • And More!

BUSINESS TRACK

This track was designed for attendees holding non-technical and hybrid job functions seeking to understand the business value of specific AI projects. Most talks during this track will be in a 30-minute format. No technical expertise required. Hear topics including:

  • Understanding AI Capabilities
  • Top Use Cases For AI & ML
  • Scoping Your Project
  • Automation vs Augmentation
  • Compliance & AI
  • Infrastructure Needs
  • Building vs Buying
  • Pilot Programs & Proof of Concept
  • Building Your Data Science Team
  • ROI & Measuring Success
  • And More!

This year, we’re offering two distinct tracks that differentiate between technical and non-technical discussions. See below to determine which track best fits your interests and goals.

Both tracks will cover all topics listed above either from the perspective of the business exec (Business Track) or data practitioner (Data Track).

TRACK 1                            

DATA TRACK

This track was designed for our technical audience. You can expect a deep dive into the specifics of the machine learning models. Most talks during this track will be in a longer 50-minute format. Hear topics including:

  • Scaling to Big Data
  • Model Interpretability
  • Data Privacy and Security
  • Dealing with Biased Data Sets
  • Productionizing Your Model
  • Cloud v Local Environment
  • Unstructured Data
  • Deep Learning
  • Dealing with Legacy Systems
  • Reinforcement Learning
  • And More!

TRACK 2                            

BUSINESS TRACK

This track was designed for attendees holding non-technical and hybrid job functions seeking to understand the business value of specific AI projects. Most talks during this track will be in a 30-minute format. No technical expertise required. Hear topics including:

  • Understanding AI Capabilities
  • Top Use Cases For AI & ML
  • Scoping Your Project
  • Automation vs Augmentation
  • Compliance & AI
  • Infrastructure Needs
  • Building vs Buying
  • Pilot Programs & Proof of Concept
  • Building Your Data Science Team
  • ROI & Measuring Success
  • And More!

Make connections with people who can help. As attendance is by application only, we maintain low rates of service providers to reduce sales pitches and increase quality dialogue. Use our mobile networking app to connect with other conference attendees through 1:1 meeting scheduling. Click here to download the 2019 attendee list.

     1:1 MEETING SCHEDULING                             

      EXECUTIVE LEVEL CONNECTIONS                                    

Attending organizations include:

Make connections with people who can help. As attendance is by application only, we maintain low rates of service providers to reduce sales pitches and increase quality dialogue. Use our mobile networking app to connect with other conference attendees through 1:1 meeting scheduling. Click here to download the 2019 attendee list.

 1:1 MEETING SCHEDULING

 EXECUTIVE CONNECTIONS

Attending organizations include:

45+ speakers from leading financial institutions, fintechs, and AI platforms will take stage over the two days to share their AI initiatives.

Below are confirmed speakers. Please note that in the event of a speaker cancellation, we will do our best to find a suitable replacement. Refunds will not be granted for speaker cancellations.

null

Arvind Rajan

Managing Director - Head of Global and Macro, PGIM Fixed Income
null

Yan-Zhu Wu

Senior Data Scientist, Credit Suisse
null

Matthias Feiler

Head of Asset Allocation, LGT Capital Partners
null

Che Guan

Principal Data Scientist, Raymond James
null

Ruchi Gupta

VP - Credit Risk, HSBC
null

SriSatish Ambati

CEO & Co-Founder, H2O.ai
null

Richard Mathieson

Managing Director, BlackRock
null

Victor Martinez

MD & Lead Data Scientist, State Street
null

Gordon Liu

EVP - US Head of Global Risk Analytics, HSBC
null

Michael Grant

Director - Technical Consulting, Anaconda
null

Thibaut Ajdler

Senior Quantitative Analyst, LGT Capital Partners
null

Scott Clark

Co-Founder & CEO, SigOpt
null

James Bell

Head of AI & Machine Learning, Dow Jones
null

Derek Singh

SVP, Quant Modeling Treasury, US Bank
null

Dr. Jordan Brandt

CEO & Co-founder, Inpher
null

Tilky Xu

Vice President - Quant Research/Data Scientist, JPMorgan
null

Jun Kim

Director - Finance Decision Science, American Express
null

James Brusseau

Director of Data Ethics Site, Pace University
null

Mike Galvin

Executive Director - Corporate Training, Metis
null

Yun Zheng

VP - Innovation Lead, HSBC
null

David Robinson

Chief Data Scientist, DataCamp
null

Roderick Powell

SVP and Head of Model Risk Management, Ameris Bank
null

David Koppe

Director of Information Strategy, MongoDB
null

Andrew Rudd

CEO, Advisor Software
null

Jay Budzik

Chief Technology Officer, ZestFinance
null

Ioana Boier

Head of Quantitative Portfolio Solutions, Alphadyne Asset Management
null

Rajeev Sambyal

Director of Data Science, Advanced Digital Solutions, BNY Mellon
null

Andy Zhou

Data Scientist, Aetna
null

Ryohei Fujimaki

Founder & CEO, dotData
null

Ben Rudin

Commercial Business Lead, Orbital Insight
null

Salah Khawaja

Managing Director - Automation/Global Risk, Bank of America
null

Hongfei Li

Co-Head of Analytics, Point72 Asset Management
null

David Magerman

Managing Partner, Differential Ventures
null

Chris Butler

Chief Product Architect, IPsoft
null

Mark Ferrari

Research Scientist, Advisor Software
null

Patrick Nussbaumer

Enablement Program Director, DataRobot
null

Chris Kovel

MD & Head of Intelligence and Data Analytics Tech for Wealth Management, Morgan Stanley
null

Wendy Callaghan

Chief Innovation Legal Officer, AIG
null

Kevin Dewalt

Co-Founder & CEO, Prolego
null

Zeeshan Ali

SVP - Head of Financial Services, Beyond Limits
null

Sharon Liebowitz

Director of Innovation & Strategy, S&P Dow Jones Indices
null

Ravi Bhatia

Head of Global Credit Risk Oversight, Paypal
null

Nico Smuts

Investment Data Scientist, Investec Asset Management
null

Nathan Hall

VP of Systems Engineering, Pure Storage
null

Charles Post

Managing Counsel & Director, Head of Legal Data Management & Advisory, BNY Mellon
null

Seth Weidman

Senior Data Scientist, Facebook
null

Rohit Rana

SVP, SunTrust Bank
null

Chris Osmond

Chief Investment Officer, Prime Capital Investment Advisors
null

Artit ‘Art’ Wangperawong

Distinguished Engineer, U.S. Bank
null

Andrew Comas

Digital Advisor, Microsoft
null

Iulian Cotoi

Head of Analytics, Axioma
null

Wayne Shoumaker

SVP, Quantitative Analytics Manager, Wells Fargo

About

Artificial intelligence could be the last invention that humankind needs to make. As such, we think it’s pretty important we get it right. In 2019, Ai4 conferences will educate 1500+ top executives & data practitioners at the world’s largest companies about how they can responsibly leverage AI today. Confusion is still commonplace when discussing AI for the enterprise; from basic definitions all the way to implementation. Through our conferences and content, we aim to provide a common understanding for what AI means to the enterprise. Visit our homepage to learn about each of our conferences: Ai4 Finance, Ai4 Healthcare, Ai4 Cybersecurity, and Ai4 Retail.