Green Finance Speaker Series (Session 3): See a Problem, Measure It and Fix It

Get the latest knowledge of Green Finance development!

About this course

About the Speakers Series
The Speakers Series aims at providing latest knowledge of Green Finance development, from historic development of international policies and regulations, the recent development in Asia and Hong Kong especially amid the Pandemic Era, to the recognized successful case studies from some European countries with the integration of technology.
Who Should Join
Financial Industry Practitioners, Tech Start-ups, and University Students

What To Learn
1.      Development of Green Finance
2.      Future of Green Finance in Asia and Hong Kong especially amid the Pandemic Era
3.      European case studies of integration of Green Finance with technology.
Date: 19 Aug 2021
Time: 15:00 – 16:30
Format: Online
Language: English

1.      Mr Arnaud Picut [Head of Global Risk Management Practice, Finastra]
2.      Dr Leonid Bogachev [Reader in Probability (Associate Professor), University of Leeds]

Mike Fung and Gabrielle Fung (HKUST MPhil Programme in Technology Leadership and Entrepreneurship Students)
Course Fee: Free of charge


FinTech, Smart Living
Under 2 hours, Self-paced
No credit


Deadline: 20 Aug 2025

By the end of this course, you will learn:


Part 1: See a problem, measure it and fix it leveraging modern modelling technics


Part 2: Emerging from “Mother Nature”


Part 3: Using blockchain for supply chain traceability



Head of Global Risk Management Practice, Finastra
Master in Mathematic & Computer Science in Paris. More than 25 years in risk management, starting his carrier as entrepreneur to deliver first generation of analytics combining risk & finance in a single platform before recently launching the next generation of AI/ML-base predictive analytics helping to make the right decision when it comes to greener the balance-sheet and give access to vital tailored and affordable funding to the underserved population (Empower MSME to generate sustainable growth). 


Reader in Probability (Associate Professor), Department of Statistics, School of Mathematics, University of Leeds
BSc/MSc Mathematics (Distinction), PhD Probability/Statistics (Moscow State University). Expertise: Probability, Statistical Physics, Statistics (extreme value theory). Over 50 peer-reviewed papers. Associate Editor, Statistics & Probability Letters. Awards: Royal Society Fellowship; Leverhulme Research Fellowship; ZiF Research Group; PI on NTI grant “Scalable Machine Learning for Data Stream Forecasting of Extreme Values”.