Senior Vice President, Quantitative Development Manager , US Bank
Please tell us a little about the topic you will be speaking on at the upcoming event?
Applications of reinforcement learning (semi-supervised, rewards based machine learning) to algorithmic trading and hedging
Can you tell us a little bit about your background, and how you ended up in your current role?
I spent the first half of my career working for an investment bank as a trading desk quant in derivatives pricing and risk management.
For the second half of my career I have worked in consulting and senior leadership roles for commercial banks in the treasury department, leading statistical, econometric s, and derivatives modelling teams.
What is the biggest challenge you face within your role today, and how are you looking to tackle it?
The biggest challenge is really execution. We have a lot of interesting projects and great ideas within our team, but delivering quality work that meets and exceeds expectations takes a lot of time, resources, effort, and attention. So that necessarily impacts the volume of work that we can deliver at that high level of quality.
Biggest success you achieved for 2018/ 2019 so far?
Our team delivered the first suite of integrated CCAR and business use models for our deposit product base. This is a notable achievement towards our larger goal of delivering integrated models for multiple use cases (i.e. regulatory modelling, risk management, pricing, optimization, etc.).
What are your Key Objectives for attending the upcoming event?
1. Learn more about current and emerging trends in AI & Emerging Tech.
2. Network and make some connections in AI & Emerging Tech in the financial industry.
3. Participate and stay engaged throughout the event.
What are you currently most inspired about in regards to AI & Emerging Tech for Finance?
Deep hedging and similar applications of deep reinforcement learning techniques.