Publication type: Conference paper
Type of review: No review
Title: Accelerated data science, AI and GeoAI for sustainable finance in central banking and supervision
Authors: Papenbrock, Jochen
Ashley, John
Schwendner, Peter
et. al: No
Conference details: International Conference on "Statistics for Sustainable Finance", Paris, France, 14-15 September 2021
Issue Date: 15-Sep-2022
Language: English
Subjects: Spatial finance; Environmental exposure; Sustainable finance; Data processing; Explainable AI; RAPIDS; ESG
Subject (DDC): 006: Special computer methods
332: Financial economics
Abstract: Sustainable finance – the umbrella term for investing based on Environmental, Social, and Governance (ESG) considerations – requires the analysis and integration of massive amounts of complex data – including but not limited to geospatial terrain and elevation data, climate data, company news, market data, regulatory filings, supply chains & logistics. Traditional analytic techniques will not suffice. Here, we lay out the argument for computing platforms and strategies derived from scientific and industrial high-performance computing (HPC) and the emerging field of Artificial Intelligence (AI). We highlight some of the critical considerations in building such systems to support the data analytics and, equally importantly, the controls required to build supervisory systems for sustainable finance. Lessons learned from leading HPC, and AI systems point to GPU accelerated compute as being a key feature of these systems, along with data-centric system design. We also highlight the role of explainable and trustworthy AI as catalysts for accelerated computing and their challenges. Finally, we propose a concrete use case: a cross-regional, shared system that integrates geospatial data with economic and market data to illustrate the benefits of accelerated computing in building these systems.
URI: https://www.bis.org/ifc/publ/ifcb56_23.pdf
https://digitalcollection.zhaw.ch/handle/11475/25435
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Management and Law
Organisational Unit: Institute of Wealth & Asset Management (IWA)
Appears in collections:Publikationen School of Management and Law

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