25881 AI-integrated Sustainable Finance6cp
Requisite(s): 24 credit points of completed study in spk(s): C04048 Master of Finance OR 24 credit points of completed study in spk(s): C04258 Master of Finance (Extension) OR 24 credit points of completed study in spk(s): C07021 Graduate Diploma Finance OR 24 credit points of completed study in 24Credit Points spk(s): MAJ08984 c 36cp Finance Major MBA
The lower case 'c' after the subject code indicates that the subject is a corequisite. See definitions for details.
These requisites may not apply to students in certain courses. See access conditions.
With the advent of climate change, health crises, and global pollution there is a global trend and need for responsible investing and sustainable finance practices. Artificial Intelligence (AI) has tremendous potential to accelerate and industrialise evidence-based, data-driven sustainable finance, ESG-related decision making, and climate risk management. Natural language processing (NLP) and spatial AI have become leading technologies in this area, as have simulations, digital twins, virtual worlds, and omniverse. Asset managers, asset owners, banks, insurance companies, regulators, and central banks are increasingly applying ESG criteria as part of their analysis process to identify material risks and growth opportunities. Developments in AI and machine learning have led to the creation of a new type of ESG data that do not necessarily rely on information provided by companies. In this subject we review the use of AI in the ESG field: textual analysis to measure firms’ incidents or verify the credibility of companies’ concrete commitments, satellite and sensor data to analyse companies’ environmental impact or estimate physical risk exposures, machine learning to fill missing corporate data (e.g., greenhouse gas emissions). We discuss potential challenges, in terms of transparency, manipulation risks and costs associated with these new data and tools.
Detailed subject description.