Towards Automating the Identification of Sustainable Projects Seeking Financial Support: An AI-Powered Approach

Author:

Behrooz Hojat1ORCID,Lipizzi Carlo2ORCID,Korfiatis George1,Ilbeigi Mohammad1ORCID,Powell Martin3,Nouri Mina1ORCID

Affiliation:

1. Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, 1 Castle Point on Hudson, Hoboken, NJ 07030, USA

2. School of Systems and Enterprises, Stevens Institute of Technology, 1 Castle Point on Hudson, Hoboken, NJ 07030, USA

3. Siemens Financial Services, Iselin, NJ 08830, USA

Abstract

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.

Funder

Siemens Financial Services

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

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1. Exploring students’ perspectives on Generative AI-assisted academic writing;Education and Information Technologies;2024-07-31

2. Utilization of Artificial Intelligence in Academic Writing Class: L2 Learners Perspective;2023 IEEE 15th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM);2023-11-19

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