Agenda

Agenda

Agenda: AI Innovation in Risk Management, online course

This course will be delivered live remotely via an online platform

Agenda timing is in GMT
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Session one - 2pm GMT / 9am EST
Session two - 3.15pm GMT / 10.15am EST
End - 4.15pm GMT / 11.15am EST
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Day one

14:0015:00

Identifying use cases for AI

14:00 - 15:00

  • In what areas is AI most effective 

  • Stress testing, early warning capability 

  • Assessing the availability and types of data 

  • Regulatory incidence associated with a particular area 

  • Is the data usable? 

Sebastian Ptasznik

Principal

Parker Fitzgerald

Sebastian leads the Credit Risk Methodology team within firm’s Quantitative Advisory Services. He specialises in quantitative analytics, credit risk modelling, macroeconomic forecasting, machine learning and data analytics.​  He has 11 years’ of quantitative analytics experience working for top tier UK and global banks, aerospace and defence, telecommunication and technology companies.​ Sebastian worked in credit risk modelling, model validation, and stress testing across retail and wholesale banking, as well as delivered a large scale data mining and machine learning projects.

15:0015:15

Break

15:00 - 15:15

15:1516:15

AI and operational risk

15:15 - 16:15

  • Current operational risk challenges 
  • NLP in incident categorisation 

  • Building risk taxonomies for risk libraries 

  • Digitisation 

  • Potential operational risks associated with AI tools 

Jos Gheerardyn

Co-founder and CEO

Yields.io

Jos is the co-founder and CEO of Yields.io. Prior to his current role he has been active in quantitative finance both as a manager and as an analyst. Over the past 15 years he has been working with leading international investment banks as well as with award winning start-up companies. He is the author of multiple patents applying quantitative risk management techniques to imbalance markets. Jos holds a PhD in superstring theory from the University of Leuven (Belgium).

16:1516:15

End of day one

16:15 - 16:16

Day two

14:0015:00

Preparing your data for AI and ML

14:00 - 15:00

  • Mitigating bias and error 

  • Developing an appropriate data foundation for AI 

  • Continual maintenance of data quality 

  • Ethical considerations 

  • Finding the right sources of data 

Ivan Sergienko

Chief Product Officer

Riskfuel

Prior to joining Riskfuel, Ivan was Head of Capital Markets Products at Element AI. He has worked at Scotiabank and Oak Ridge National Laboratory, has completed a Ph.D. in Physics and earned a CFA designation.

15:0015:15

Break

15:00 - 15:15

15:1516:15

Creating a culture that supports AI innovation

15:15 - 16:15

  • In a period of increased cost how can you still encourage innovation 

  • Structures and working groups that encourage innovation 

  • Common mistakes 

Arpit Narain

Global head of financial solutions

MathWorks

Arpit is the global head of financial solutions at MathWorks. He is responsible for the global expansion of firm's financial services business in the areas of quantitative modeling and AI / Machine Learning.

He has 12 years of experience in quantitative finance domain working with consulting firms, risk product development firm, and Investment bank. He has led large and complex quant engagements for top investment banks, commercial banks, hedge funds, insurance firms, and other capital market firms in the Americas, Europe, and APAC regions. He also established Quant Risk Modeling & Derivatives Valuations group at KPMG Global Services (India).

He has expertise in Market Risk, Counterparty Credit Risk (CVA, DVA), Capital (FRTB, BASEL 2.5), LIBOR Transition, Predictive Analytics, Stress Testing, Risk Margin (ISDA SIMM), Portfolio Valuations & Risk Analytics, Treasury Analytics, Asset Liability Management, Hedge fund trading strategy, and Model Risk (Fed SR 11-7, EU TRIM).

He has advised top leaders at JP Morgan, Goldman Sachs, Morgan Stanley, BAML, Deutsche, HSBC, UBS, Credit Suisse, Citi, Barclays, BNPP, Santander, Capital One, SunTrust, MUFG, Fidelity, TD Ameritrade, Oppenheimer, S&P, Prudential, Bermudan Monetary Authority, etc.

Naresh Malhotra

Director, financial risk advisory

KPMG LLP

Naresh Malhotra is U.S. Lead Director for Trading Book Capital and associated initiatives at KPMG. His interests span across market risk, counterparty credit risk, model risk, and ML/AI applications in the financial industry. Naresh brings 15+ years of experience in trading and risk management of fixed income portfolios, and considered a recognized market expert in market risk measures, risk capital, and margin related regulations.

Prior to joining KPMG, Naresh worked as a portfolio manager at Diamond Notch (a hedge fund based in New York) where he managed a US and European credit strategies centric portfolio. Previously, Naresh served as co-head of US credit exotics trading at Merrill Lynch, and as senior credit trader at UBS, Barclays, and Commerzbank AG.

Naresh has a PhD in Engineering and Applied Math from University of Illinois (Urbana-Champaign), and a BS in Aerospace Engineering from IIT-Kanpur (India). The academic preparation was followed by a research faculty position in Engineering & Applied Sciences at Caltech (Pasadena).

16:1516:15

End of day two

16:15 - 16:16

Day three

14:0015:00

AI implementation roadmap

14:00 - 15:00

  • Identify the use case 

  • Match to process 

  • Implementation project 

  • Scaling across 

  • Identifying any skill shortages 

  • Creating a holistic AI strategy 

Jesús Calderón

Managing director

Maclear Data Solutions

Jesús Calderón advises Canadian and international clients in the financial services and energy industries on the implementation of data-driven solutions for risk management in  banking, insurance, capital markets, and energy trading, as well as anti-money laundering and regulatory activities. Jesús has over twelve years of experience in risk management, internal audit, and fraud investigations, where he has specialized in the application of data science and machine learning methods to optimize risk control activities and examinations.

15:0015:15

Break

15:00 - 15:15

15:1516:15

AI - innovating with confidence

14:00 - 15:00

  • AI target operating models
  • AI model validation
  • Risk & control frameworks
  • Ethical AI
Alexander Denev

Head of AI - financial services, risk advisory

Deloitte LLP

Alexander Denev has more than 15 years of experience in finance, financial modelling and machine learning and he is the former lead of the Advanced Analytics & Quantitative Research at IHS Markit. He has written several papers and two books on topics ranging from stress testing and scenario analysis to asset allocation. He is currently writing his third book on Alternative Data in Trading&Investing. Alexander Denev attained his Master of Science degree in Physics with a focus on Artificial Intelligence from the University of Rome, and he holds a degree in Mathematical Finance from the University of Oxford, where he continues as a visiting lecturer.

16:1516:15

End of day three

16:15 - 16:16

Day four

14:0015:00

AI and regulation

14:00 - 15:00

  • Opacity of the black box 

  • Use of AI in areas of high regulation 

  • Is this uncertainty inhibiting innovation? 

  • Council of Europe guideline for AI and data protection 

  • Leveraging historical data 

Fabrizio Russo

Head Of Data Science

4most

15:0015:15

Break

15:00 - 15:15

15:1516:15

Case study: portfolio optimisation tools

15:15 - 16:15

  • Standard portfolio optimisation analytic techniques 

  • Automated and semi-automated advisory activity 

  • AI across the rest of the AI value chain 

16:1516:15

End of course

16:15 - 16:16