TY - JOUR
T1 - Towards Automating the Identification of Sustainable Projects Seeking Financial Support
T2 - An AI-Powered Approach
AU - Behrooz, Hojat
AU - Lipizzi, Carlo
AU - Korfiatis, George
AU - Ilbeigi, Mohammad
AU - Powell, Martin
AU - Nouri, Mina
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/6
Y1 - 2023/6
N2 - The criticality of sustainable development to control the unprecedented consequences of climate change is clear. A vital element in launching sustainability projects is financing, especially for projects by small and medium enterprises. The first and crucial step to offering financing services for sustainable development is to identify and evaluate promising projects. The current practice to accomplish this step heavily depends on subject-matter expertise and professional networks. The current practice also involves extensive manual document reviews and subjective decisions. Therefore, existing methods are time-consuming, inefficient, and not scalable. This study proposes an automated system to identify potential sustainability projects for financing services using Artificial Intelligence (AI). The proposed method uses web crawlers and text mining solutions, including Natural Language Processing (NLP), to search the Internet, analyze text data, evaluate the information quantitatively, and identify potential sustainability projects for financing services. The proposed method was implemented and empirically assessed. The results indicate that the AI-enhanced system is able to identify and prioritize potential sustainability projects with 87% accuracy. The outcomes of this study will help financial experts and decision-makers take advantage of the information available on the Internet efficiently to improve the existing methods for identifying potential projects for financing services.
AB - The criticality of sustainable development to control the unprecedented consequences of climate change is clear. A vital element in launching sustainability projects is financing, especially for projects by small and medium enterprises. The first and crucial step to offering financing services for sustainable development is to identify and evaluate promising projects. The current practice to accomplish this step heavily depends on subject-matter expertise and professional networks. The current practice also involves extensive manual document reviews and subjective decisions. Therefore, existing methods are time-consuming, inefficient, and not scalable. This study proposes an automated system to identify potential sustainability projects for financing services using Artificial Intelligence (AI). The proposed method uses web crawlers and text mining solutions, including Natural Language Processing (NLP), to search the Internet, analyze text data, evaluate the information quantitatively, and identify potential sustainability projects for financing services. The proposed method was implemented and empirically assessed. The results indicate that the AI-enhanced system is able to identify and prioritize potential sustainability projects with 87% accuracy. The outcomes of this study will help financial experts and decision-makers take advantage of the information available on the Internet efficiently to improve the existing methods for identifying potential projects for financing services.
KW - artificial intelligence
KW - financing
KW - natural language processing
KW - sustainability projects
KW - web crawler
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U2 - 10.3390/su15129701
DO - 10.3390/su15129701
M3 - Article
AN - SCOPUS:85163997616
VL - 15
JO - Sustainability (Switzerland)
JF - Sustainability (Switzerland)
IS - 12
M1 - 9701
ER -