The Role of Artificial Intelligence, Financial and Non-Financial Data in Credit Risk Prediction: Literature Review

Abstract

Small and medium-sized enterprises (SMEs) are of major importance in world economies and job creation. Financing is one of the key issues for SME development since SMEs are often considered riskier than large companies. It is argued in the literature that artificial intelligence (AI) and non-financial data could increase the financial inclusion of disadvantaged groups, such as SMEs. This article presents an overview of selected studies on credit risk prediction from the 1960s to 2022, covering topics of research work applying classical statistical methods, studies using AI methods on traditional financial data and studies applying AI methods on non-financial data. Literature overview results showed that the inclusion of non-financial data in credit risk prediction models could increase credit risk prediction performance, while AI methods can enable the inclusion of non-financial data. Since non-financial data potentially could be used as alternative data in credit prediction models, AI and non-financial data could help to increase access to finance for SMEs