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Abstract(s)
The assessment of financial credit risk is an important and challenging research
topic in the area of accounting and finance. Numerous efforts have been devoted into this field
since the first attempt last century. Today the study of financial credit risk assessment attracts
increasing attentions in the face of one of the most severe financial crisis ever observed in the
world. The accurate assessment of financial credit risk and prediction of business failure play
an essential role both on economics and society. For this reason, more and more methods
and algorithms were proposed in the past years. From this point, it is of crucial importance
to review the nowadays methods applied to financial credit risk assessment. In this paper,
we summarize the traditional statistical models and state-of-the-art intelligent methods for
financial distress forecasting, with the emphasis on the most recent achievements as the
promising trend in this area.
Description
Keywords
Financial credit risk assessment Business failure Ensemble computing Cost-sensitive learning Dimensionality reduction Subspace learning
Citation
Publisher
Springer Verlag