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Abstract
Global consumer lending has seen a compound annual growth rate (CAGR) of 4.8 per cent forecasted to 2020. The financial system is once again at risk; it is a decade since the credit crunch, yet the causes have not been solved; however, globally, the outstanding amount of credit doubled compared to the lending volume of 2008. Also, increasingly more credit decisions are being taken today. Furthermore, millennials’ service expectations drive transformation from traditional lending into digital lending. The CAGR for digital lending is 53 per cent until 2025. Therefore, in this growing information age, new methods for credit risk scoring could form the central pillar for the continuity of a financial institution and the stability of the global financial system. This paper contains research from across the UK and the Netherlands: two advanced lending markets, selected because of their advancements in digital lending, to examine to what extent lenders can advance their credit decisions with individual risk assessments with artificial intelligence (AI). The research has applied supervised learning and has been performed on 133,152 mortgage and credit card customers in prime, near prime and sub-prime lending segments of three European lenders across the UK and the Netherlands during the period January 2016 to July 2017. As candidate models, we chose neural nets and random forests, as they are the most popular supervised learning methods in credit risk for their benefit of applying both structured and unstructured data. The research describes three experiments that develop the AI probability of default models and compares the model quality with the quality of the traditional applied logistic probability of default (PD) models. In all experiments, AI models performed better than the traditional models. Scalable automated credit risk solutions can therefore build on AI in their risk scoring.
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Author's Biography
Diederick Van Thiel is an European FinTech entrepreneur and PhD candidate, as well as founder and CEO of AdviceRobo. He also works as non-executive director at Ikea’s bank, Ikano. Diederick is a recognised visionary entrepreneur (FinTech CEO of the year 2018 in London) and a global specialist in robo-advice and visual assisting. On the latter, he expects to finish a PhD in 2019. Previously, he has been on the board of ING Retail, KPN Mobile and Vodafone The Netherlands.
Willem Frederik (Fred) Van Raaij is a Dutch psychologist and professor. Fred was previously a professor at Erasmus University Rotterdam (1979–2000) and Tilburg University (from 2000). His field of study is economic psychology with specialisation in (marketing) communication and the financial behaviour of consumers. He is the founder (1981) and first editor of the Journal of Economic Psychology. In 2006, he received an honorary doctorate from the Helsinki School of Economics, Finland.
Citation
Van Thiel, Diederick and Van Raaij, Willem Frederik (Fred) (2019, June 1). Artificial intelligence credit risk prediction: An empirical study of analytical artificial intelligence tools for credit risk prediction in a digital era. In the Journal of Risk Management in Financial Institutions, Volume 12, Issue 3. https://doi.org/10.69554/NLZL1152.Publications LLP