Upcoming Webinar: Embedding AI & Machine Learning into your trading operations15 September 2020
Date: 15 September 2020
Time: 10:00am ET / 3:00pm London / 4:00pm CET
It’s no secret that AI and Machine Learning are changing the landscape of the trading industry. As these tools and techniques become more mainstream, their availability to even the smallest of financial firms is becoming a more viable proposition.
From speech recognition and natural language processing (NLP) to deep learning algorithms and predictive analytics, these technologies allow firms to identify complex trading patterns on a massive scale across multiple markets in real time. By adopting AI and ML, firms can expect to enjoy faster, more effective remediation of identified errors, reduced burden of exception management and automated reconciliation processes.
Embedding AI and Machine Learning into your firms’ trading operations allows ongoing risk monitoring, saves traders time searching through conversations and financial data, and can predict the performance of financial instruments and portfolios.
But how can you leverage these tools and technologies to gain efficiency and reduce costs? And how can you convince senior management of their value for middle- and back-office functions?
Register for this webinar to learn more about:
- An overview of AI & Machine Learning capabilities across the firm
- Cost savings and efficiency benefits
- How to develop new investment strategies using these tools
- Specific AI and Machine Learning tools and technologies available
Current speakers below, more topic-specialist speakers will be announced soon.
Fergal Toomey, Chief Scientist, PICO
Moderator: Andrew Delaney, Chief Content Officer,
More about our speakers:
Fergal has been using mathematics and data science to solve problems in computer and network operations for over 20 years, and currently leads the Data Science team at Pico. Previously he was Chief Scientist and a founder of Corvil, where he made many contributions to Corvil’s portfolio of analytics for electronic trading. Fergal holds a Ph.D. in Applied Probability from Trinity College, Dublin.
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