The goal is to resolve how financial settings can adapt practices or propose solutions for designing green credit scoring models. This will facilitate improved access to investment and credit, thereby promoting fair and sustainable economic growth. You will be a member of the MSCA Industrial Doctoral Network on Digital Finance, a European Research and Training programme with several leading European universities and companies involved, such as the European Central Bank and the Bank for International Settlements. You will attend several European PhD courses and participate in extended research stays abroad.
You will join the Industrial Engineering and Business Information Systems (IEBIS) section of the High-tech Business & Entrepreneurship Department (HBE) at the Faculty of Behavioral Management and Social Sciences (BMS).
Background This PhD position is one four positions at the University of Twente (UT) and one of 19 positions in the context of the international Marie Sk?odowska-Curie Actions project DIGITAL. For the general description of DIGITAL, please check this page. Information about all other positions is available at EURAXESS, if you would be interested in any of the other positions as well, clearly state that in your cover letter.
DIGITAL' main goal? To significantly advance the methodologies and business models for Digital Finance through five interconnected research objectives:
- Ensure sufficient data quality to supply to the EU's efforts of building a single digital market for data
- Address deployment issues of complex artificial intelligence models for real-world financial problems
- Validate the utility of innovative explainable artificial intelligence (XAI) algorithms to financial applications and extend existing frameworks
- Design risk management tools concerning the applications of Blockchain technology in Finance
- Simulate financial markets and evaluate products with a sustainability component
The description here focuses on the specific position "Modelling green credit scores for a network of retail and business clients" (mainly included in objective #5), outlining the project's key takeaways and desired skills of future members of the network.
The challenge In an ever-evolving financial landscape where the process industry responds to the growing demand for sustainable business models, the significance of AI in shaping decision-making cannot be overstated. Using the power of Machine Learning (ML) models, our project will examine financial investments and credit risk indicators. While these AI techniques have found widespread application in traditional financial domains, a noticeable gap exists in addressing the unique dynamics of businesses. Existing financial models often overlook the environmental and social intricacies of credit risk models, elements that can significantly impact access to credit and thereby hamper economic growth.
This Ph.D. project is committed to a comprehensive exploration of the intersection between finance and sustainable business models, with a specific focus on credit risk assessment through the use of AI. Our goal is to provide innovative AI tools and models to businesses and society to promote sustainable financial strategies based on principles of sustainability, fairness, and transparent credit risk assessment. Are you prepared to reshape the financial sector by improving risk assessments and investment choices, all while advocating for sustainability and environmental stewardship? If this resonates with you, this position could be your ideal opportunity!