Conference Day Two: March 20 2019

7:45 am - 8:50 am Welcoming tea, coffee and registration


8:50 am - 9:00 am Chair's opening remarks

9:00 am - 9:25 am Case study: Creating an international top tier data science and AI team

  • Building a vision: understanding and defining the data requirements of a global investment bank
  • Selling the business case: do you need quick wins to sustain the long term vision?
  • In practice: Finding the top talent to build a team that will create an innovative all-encompassing platform that serves a multitude of asset classes and business functions
  • Growing and developing the functionality: refining, improving and scaling up

9:25 am - 10:00 am Panel discussion: How are investment banks leveraging their quant and data science teams to build new business models and add value to clients?

  • Building in recommender systems: identifying trade ideas your client hasn’t considered yet
  • Evaluating the benefits of flagging new or unusual activity
  • Leveraging the vast reams of historical data that banks have stored
  • Utilizing AI and data science to eliminate inefficiencies,  provide best execution and settlement for clients
  • Implementing AI and ML to help manage the regulatory burden

10:00 am - 10:30 am Panel Discussion: The BIG Data Trends Debate

  • Explore recent trends in data.
  • Hear these experts outline their vision for how data needs will change over the next 3-5 years
  • Ask your questions about the coming trends

10:30 am - 11:00 am Networking refreshment break in the exhibition area

11:00 am - 11:30 am Head to Head: Finding talent and how to build culture

  • Hear these hedge fund heavyweights share insights into the culture they created in their large international scale organizations
  • What are the most important features to find and retain the best talent?
  • Evaluating the pros and cons of different cultural approaches

11:30 am - 12:05 pm Panel discussion: The outlook for emerging quantitative concepts as a tool to find edge

  • Evaluating new and emerging strategies to maximise the alpha from a blended man and machine approach
  • Measuring effectiveness: understanding the ROI on your strategies – are they always practical and cost-effective to execute?
  • When and how will quant funds consistently outperform a traditional approach?
  • Understanding the risks of a market saturated with the systematic approach: when will the models fail?

12:05 pm - 12:30 pm Panel discussion: Maximizing your achievements in Data Science

  • Hear these leading data scientists discuss the latest techniques, concepts and trends
  • Evaluate where technology can take potential achievements in data science
  • Ask your questions to the esteemed panel for unique insights and takeaways

12:35 pm - 1:30 pm Networking lunch in the exhibition area



1:30 pm - 1:35 pm Effective Risk Management


1:35 pm - 1:55 pm Academic research presentations
Three of the top statistical and financial engineering academics  present their latest work


1:55 pm - 2:15 pm Academic research presentations
Three of the top statistical and financial engineering academics  present their latest work


2:15 pm - 2:35 pm Academic research presentations
Three of the top statistical and financial engineering academics  present their latest work

STREAM B: Quant Methods

1:30 pm - 1:35 pm Quant methods

STREAM B: Quant Methods

1:35 pm - 1:55 pm Setting the scene: Your algo’s are fit for current market conditions, but what regime change factors are you missing?
  • Evaluating the influence of macro factors on current market indicators: volume, momentum and structure
  • Preparing your model for current liquidity trends and changes like unwinding of QE
  • Identifying macro factors that your model may not have the historic knowledge of: How to recognize the next debt crisis?

STREAM B: Quant Methods

1:55 pm - 2:35 pm Panel discussion: Uncovering and assessing risk factors of a pure quant strategy
  • The issues of overfitting: how can you accurately predict in an undefined universe without overfitting?
  • Interpretability: Can you ever really trust a black box to make the right decisions without human understanding, and will the regulators agree?
  • Examining the success of your algorithm in different market conditions: have you correctly identified the relevant factors?
  • Coping with tail/extreme events: are you prepared for the unexpected?

STREAM C: The Future

1:30 pm - 1:35 pm The Future

STREAM C: The Future

1:35 pm - 2:35 pm Innovation spotlights: The next big opportunity
1. An insight into cryptocurrencies as an asset class and a model for trading alternatives
  • Challenges in launching a fund in a new and emerging alternative asset class 
  • Special handling of alt assets and custom systems that relate
  • Challenges of appropriate data for algorithms: evaluating proxies for factors including life span, quantities, volatility

2. How can blockchain enable certain asset classes to become tradeable?
  • Understanding the benefits of a natively digital trading technology to maximise data and analytical capabilities
  • Practical applications in new asset classes such as syndicated loans
  • Its application within algorithms: removing the interpretability issue

3. The very latest AI developments
  • Following a big focus on deep learning techniques, where might the use of AI techniques in finance go?

2:35 pm - 3:05 pm Networking refreshment break in the exhibition area

3:05 pm - 3:45 pm Panel discussion: Understanding, managing and effectively mitigating the hidden risks associated with AI

  • The risks of the person behind the AI/model: how to remove bias?
  • Coping with tail risks: have your models been effectively tested under extreme/unusual circumstances?
  • Can you ever model all circumstances in an undefinable and constantly moving market?
  • How can AI measure a risk it hasn’t seen yet?
  • Balancing the compliance and risk demands of creating human understanding of complex models with thousands of parameters with trust for the system you have created that follows the parameters you have put in place
  • Overfitting: Have you applied diversification in your quant strategies? A variety of asset classes? Appropriate algorithm choices?
  • Would a failure of model or liquidity mean you have inappropriate risk management in place?

3:45 pm - 4:05 pm Presentation: The critical issues of interpretability: understanding what it really means?

Underspecified and unclear: have you appropriately defined your model and the properties it satisfies?
  • Understanding causal structure: validating the decisions your machine made
- How can you explain why a model did something? Why did the ML choose a certain course of action?
  • Resilience and robustness: The importance of factoring in domain adaptation and distribution shift
  • Anomaly detection: quantifying and actively compensating by modifying your beliefs and constraints

3:05 pm - 4:05 pm Roundtables

Delegates will have the opportunity to sit in small discussion groups and talk in a confidential and unreported setting on two of the following 30 minute discussion groups

1. Self-learning neural networks: playing with AI methodology to achieve the best outputs
2. Quantitative Methods: which algo suits your strategy best?
3. Data Sourcing Pitfalls
4. Accurate risk management: 
5. Selecting the most appropriate analytics interface
6. The skills toolkit: How to create the best data science team

3:05 pm - 3:25 pm Technology: The journey to the cloud

As acceptance for cloud increases, the questions become how to use and implement it.
  • Understanding the benefits of a cloud based infrastructure: scalability with flexibility
  • Data and storage improvements and forecasts
  • The disruptor’s take on cloud for AI: enabling David to compete with Goliath
  • Implementing cloud in your company and systems: pitfalls to be avoided

3:25 pm - 3:45 pm The open source culture: why is the industry and this fund embracing a new age of openness?

  • The merits of open source: culture: attracting talent, efficiencies and the hive mind
  • Considering the impact on your internal procedures
  • Is there a downside and how can this be mitigated?

3:45 pm - 4:05 pm Emerging technologies and methodologies that can generate profit

  • Evaluate this lineup of new and emerging technologies for their use and longevity
  • Understanding the features that make an emerging technology here for the long run


4:05 pm - 4:35 pm Panel discussion: Quantum computing: Closer than ever – understanding the landscape, risks and opportunities

  • How and why quantum computing will change the world of finance as we know it: can you trust the liquidity of your system should its very foundations change?
  • What is the current state of quantum computing and how is finance adopting the technology?
  • What will be the area of biggest impact within capital markets once quantum computing becomes a reality?
  • As a highly automated sector, how can finance prepare for the changes?

4:35 pm - 4:55 pm Closing keynote: A vision of success for 2020

  • Hear this inspirational mind from the investment  world outline their vision for the coming year
  • Evaluate the most important factors for success and growth in the coming months
  • Preparing for the inevitable changes to the foundations of finance

4:55 pm - 4:55 pm Closing summary

5:00 pm - 5:00 pm Close of conference