Research Centre: Research Centre for Machine Learning
Speakers: Sylvia Smit, Ricardo Cruz, Khrystyna Andronova (Delta Capita)
Title: How Data Science is used at Delta Capita
1. Sylvia Smit - Head of Equity Markets Delivery at Delta Capita
Senior Financial Markets professional specialising in defining and driving Investment Banking organisations to deliver change and meet their tactical and strategic challenges. Significant experience in project management and business analysis translating business challenges into practical requirements and drive solutions and delivery working as part of the organisation rather than alongside it. Proven track record of global delivery of large and complex front to back business and technology transformations, cross-asset products and regulatory expertise
2. Ricardo Cruz - Senior Consultant at Delta Capita
Financial services professional with 10+ years’ experience driving project execution and supporting clients with the expertise required to address challenges presented by front-office technology, model risk management, machine learning/AI, digital wealth management and regulation. Entrepreneur and investor, with experience in assessing and leveraging. Fintech to address real world business cases. He thrives on challenges, thinks strategically while driving execution and firmly believes in team work built upon personal responsibility, accountability, ownership and strong work ethics.
3. Khrystyna Andronova - Consultant at Delta Capita Consulting
Financial Capital Markets professional with a proven track record in cross-asset front-office technology solutions and delivery, regulatory expertise, model risk management, artificial intelligence and wealth management.
Sylvia, Ricardo and Khrystyna will show how Data Science is used at Delta Capita and talk about the projects they are / have been working on.
1) Machine Learning Interpretability
Delta Capita has developed a Neural Network model to determine the likelihood of mortgage default given a set of information that represents an individual loan. The aim of the project is to develop knowledge extraction techniques which interpret the mortgage defaulting model
2) Market Impact Analysis - Predicting market impact to identify optimal trading schedules
Train a prediction model to forecast the market impact of a set of historical equity trades. Use the predictions to find the market impact minimising strategy from a set of existing (mathematically derived) trading strategies for a planned trade of a certain size in a specific instrument at a certain point in time.
3) Contagion Risk
To develop software that represents the UK banking system as a system of connected agents and model the risk of contagion by applying stress events in some part of the financial system, e.g. deposit withdrawals.
4) Voice Activation for Wealth Management
To develop a solution that will enable users to interact with CboeVest’s the wealth management platform through voice. A wealth Management Platform manager.
Slides for these talks can be found here.
Slides from this seminar can be found here.
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When and where
6.00pm - 7.00pmWednesday 31st October 2018