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Recorded Webinar: Embedding AI & Machine Learning into your trading operations

15 September 2020

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?

Listen to 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 


Vijay Bhandari, Technology Principal & Innovation Lead for Investment Bank, Deutsche Bank Innovation Labs

Yauheniya Shynkevich, Data Scientist, Clearstream Banking, Deutsche Börse Group

Fergal Toomey, Chief Scientist, PICO

Moderator: Andrew Delaney, Chief Content Officer,
A-Team Group

More about our speakers:

Vijay Bhandari
Technology Principal & Innovation Lead for Investment Bank
Deutsche Bank Innovation Labs

With over 20 years in financial technology across banks and on the vendor side, Vijay Bhandari is the Technology Principal for the Innovation Labs in NY and has coverage for the Investment Bank FIC Sales & Trading at Deutsche Bank. Vijay’s a strategic partner to senior stakeholders, driving innovation strategy, cultural change and keeping them abreast of industry technology trends. Prior to joining Deutsche Bank, Vijay has held multiple roles developing and delivering strategic technology initiatives at Citigroup, Goldman Sachs and Bloomberg.

Yauheniya Shynkevich
Data Scientist, Clearstream Banking
Deutsche Börse Group

Yauheniya’s main focus is on developing machine learning solutions for the financial industry. She uses AI and NLP to develop new products and improve internal processes within Clearstream Banking at Deutsche Boerse. Her goal is to deliver end-to-end data science solutions from data acquisition to model building to deployment. Since 2009 Dr Shynkevich worked for a broad spectrum of organizations ranging from large corporations to fin-tech start-ups to academic institutions. Yauheniya holds a PhD in Computer Science from Ulster University, UK, and is a Certified Financial Risk Manager (FRM) by GARP.

Fergal Toomey
Chief Scientist

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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