Discover advances in AI & machine learning tools and techniques from the world's leading innovators across industry, research and the financial sector.

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The MIT-IBM Watson AI Lab will carry out fundamental AI research and seek to propel scientific breakthroughs that unlock the potential of AI. The collaboration aims to advance AI hardware, software, and algorithms related to deep learning and other areas; increase AI’s impact on industries and explore the economic and ethical implications of AI on society.

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In my view, the main differences stem from differences in data. In finance, data are (very) noisy, and often non-stationary. “Signals” cannot be split from “noise” in any unique way, as a matter of principle. This is very different from, say, image processing, where the level of noise can be controlled, at least in principle.

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Godin is using tools from machine learning and artificial intelligence (AI) to help investment firms and other financial institutions reduce their exposure to risk. "My main area of research consists of designing procedures and algorithms to allow financial institutions such as banks and insurers to measure, valuate and manage the risk they face in the best possible way."

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RealityEngines.AI has been focused on dataset augmentation. Dataset augmentation can be particularly helpful, for instance, with banks that are trying to stop certain fraud cases but only have a few examples of past instances for AI models to learn from.

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Why Attend

Speakers

Extraordinary Speakers

Discover advances in machine learning tools and techniques from the world's leading innovators across industry, academia and the financial sector. Speakers will share insights into recent breakthroughs in technical advancements and fintech applications including financial forecasting & compliance.

Tech

Discover Emerging Trends

Learn about machine learning applications in the financial sector from algorithms to forecast financial data, to tools used for data mining & pattern recognition in financial time series, to scaling predictive models, to stock market prediction, to using blockchain technology.

Network

Expand Your Network

A unique opportunity to interact with industry leaders, influential technologists, data scientists & founders leading the machine learning revolution. Learn from & connect with 400+ industry innovators sharing best practices to improve regulations, security and risk in the financial sector.

Who

Who Should Attend

  • Data Scientists
  • Data Engineers
  • Financial Regulators
  • CTOs, CFOs, CEOs
  • Founders
  • Directors of Innovation
  • Digital Finance Analysis Managers
  • Venture Capitalists
Speechbubbles

Join the discussion

  • 60 speakers
  • 400 leading technologists & innovators
  • Group brainstorming sessions
  • Interactive workshops
  • 12+ hours of networking
  • Access to all the filmed presentations
  • Discover technology shaping the future
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Topics we cover

Insurance
Insurance
Investment
Investment
FinTech
FinTech
Financial Compliance
Financial Compliance
Financial Forecasting
Financial Forecasting
Fraud Detection
Fraud Detection
Deep Learning Algorithms
Deep Learning Algorithms
AI
AI

Confirmed Attendees include:

HSBC
NAFCU
Euro Investment Fund
CFPB
Microsoft
Nasdaq
Ford
TD Insurance
Square
Capital One
ING Bank
Morgan Stanley
wells fargo
Vanguard
BBVA
Bank OZK
Salesforce
USAA
Scotiabank
Office of the Comptroller of the Currency
one main financial
Intact Financial
State Street
IBM
Deutsche Bank
Barclays
Fidelity Investments
New York University
Carnegie Mellon University
First Republic Bank
American Express
Korean Standard Associat
Old Mutual
FDIC
Market Financial Solutions
NEC America

Sponsors Include

Exhibitors & Startup Showcase

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