Finagri Research

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More data, more storage, more processing power

◆In 2017, it was estimated that 90% of world data had been created in the past two years alone

 

◆This data flood is expected to increase the accumulated digital universe of data from 4.4 zettabytes (or trillion gigabytes) in late 2015 to 44 zettabytes by 2020 (Internet of Things, Satellites...)

 

◆By 2020, one-third of all data will either live in or pass through the cloud

 

◆Shared access of remotely placed resources has dramatically diminished the barriers to entry for accomplishing large-scale data processing and analytics

 

◆There have been significant developments in the field of pattern recognition and function approximation (uncovering relationship between variables)

–Classical Machine Learning

–Deep Learning

–Reinforcement learning

 

◆While there is a lot of hype around Big Data and Machine Learning, researchers estimate that just 0.5% of the data produced is currently being analyzed.

Data Science and Green Finance to solve the “green crisis”

◆It has been clearly stipulated by world leaders both in the context of the 2030 Development Agenda and the Paris Agreement that in order to reach the goals that have been set out by the global community, data generation, acquisition, processing and analysis will be essential

 

◆Data processing and analysis already plays a central role in financial research, and Data Science methods are already used and being developed rapidly amongst practitioners and academics of the field

 

◆The post-2015 era will be not only be that of Big Data and Machine Learning, but also that of the constitution of massive sets of sustainability-related data that will provide unprecedented insight on the relationship between sustainability, business and financial performance, both useful for academics and professionals alike

 

◆In order to be able to best interpret these datasets, analysts and researchers will have to develop increasingly specific technical skill sets in Data Science, Statistics and Modeling as well as a deep understanding of the workings of financial markets, corporations and macro/micro-level sustainability-related issues and opportunities.

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The academic research process for deep modern challenges

◆The post-2015 era is one where

 

1.Fundamental understanding of financial markets, businesses and their relationship with a wide array of specific sustainability issues needs to deepen

2.Researchers and analysts need to keep up with technology that is constantly providing better tools to create, find, treat and analyse new data

 

◆More than simply a demand for individuals and teams that can go through this entire process efficiently, there increasingly seems to be a need for it.

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Collaboration, better data and monitoring concrete investment

◆Much like it has been stipulated by the United Nations General Assembly when establishing the Sustainable Development Goals and the Paris Agreements in 2015/2016, meeting any sustainability related goal by 2030 at national and international scales will necessitate (1) collaboration, (2) better data and monitoring, (3) concrete investment

 

◆The FINAGRI Research Chair has been conceptualized to allow for:

•Strong collaboration between:

–public and private actors

–practitioners and academics

–field and market professionals

 

•Scientific data collection and monitoring originating directly from the field

 

•Financial innovation for Sustainability and Agriculture allowing to tap into the financing potentiel of Capital Markets

 

◆Through the synergy between its operational and research branch, the Chair will be able to provide insights as this innovative operation develops, on various subjects related to Sustainable Finance, Green and Sustainable Bonds, Public-Private Partnerships for Sustainability, Green Data, Financing and Investing in Sustainable Agriculture, and many other subjects that are linked to the operation