Series: Data Bites
Speakers from Delta Capita, and City students who interned with them last summer, will be talking about two projects; DC COMPRESSION and DC MINT.
DC COMPRESSION helps to produce models which are significantly smaller in both memory and computations requirement and run faster with minimal impact on accuracy
- Highly accurate machine learning models rely on ‘millions’ to ‘billions’ of internal model parameters and must be trained over very long periods of time
- These qualities enable a much wider deployment of machine learning models including:
- Real-time applications, like high-frequency trading algorithms credit decisions and fraud detection where speed is important
- Deployment on smaller devices with limited computational resources
Your algorithm can be right 100% of the time, but, if the result is received past the action point, then it was useless.
DC MINT helps to unlock machine learning and AI
- Machine learning models show better accuracy than traditional models, but users are unable to explain how the system made the decision e.g. why a specific loan or mortgage application is rejected/accepted
- Regulations like SR11-7 and GDPR Article 22 require an explanation as to how the models made the decision
- Understanding how machine learning models work can help improve models and decision-making as well as keeping the regulators happy
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.
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.
Khrystyna Andronova – Senior Consultant at Delta Capita
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.
Edward Adcock – Data Science Consultant at Delta Capita
Ed Adcock joined ‘Delta Capita Ltd’ in early 2018 as the Lead Data Science Consultant. Delta Capita Ltd is a financial services consultancy/management firm with head office in London, UK. He is responsible for the inception, development and deployment of machine learning and data science solutions within the financial services sector including tier 1 banks. Previously, he has worked in the financial services industry for over 15 years in London, UK, working for various stockbrokers, asset managers and financial advisers.
Alexander Klemm – Data Science Consultant at Delta Capita
Finance-focused data science consultant with several years of front-office experience in capital markets, consulting, and fintech. Project lead on several successful strategy and technology projects in the retail brokerage and automated investment space. Current focus on prototyping machine learning products (machine learning explainability, model compression) for financial sector applications.
Thuy Dung Nguyen - Data Science Consultant at Delta Capita
A machine learning specialist who keens on projects to explore data and develop understanding and models which improve or automate processes. Strong statistical modelling and data analysis skills. Prior experience in market research and customer relation management.
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When and where
6.00pm - 7.00pmThursday 31st October 2019