Abstract:
Within recent years,Financial Credit Risk Assessment(FCRA) has become an increasingly important issuewithin the financial industry.Therefore,the search for features that can predict the credit risk of an organizationhasincreased. Using multiple statistical techniques,a variance of features hasbeen proposed. Applying a structured literature review,238 papers have been selected. From the selected papers,700 features have been identified. The features have been analyzed with respect to the type of feature, the information sources needed and thetype of organization that appliesthe features. Based on the resultsof the analysis,the features have been plotted in the FCRAModel. The results show that most features focus on hard information from a transactional source,based on official information with a high latency. The main contribution of this paper is the FCRAModelcombined with the plotted results, indicating multiple questions for further research.

Authors:
Eric Mantelaers;
Martijn Zoet.

APA Reference:
Mantelaers, E. & Zoet, M. (2018) A New Explorative Model to Assess the Financial Credit Risk Assessment. Proceedings of the Tenth International Conference on Information, Process, and Knowledge Management, Rome.