Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/68716
Authors: 
Schwarz, Alexandra
Year of Publication: 
2011
Series/Report no.: 
Schumpeter Discussion Papers 2011-004
Abstract: 
The statistical techniques which cover the process of modeling and evaluating consumer credit risk have become widely accepted instruments in risk management. In contrast, we find only few and vague statements on how to define the default event, i. e. on the concrete circumstances that lead to the decision of identifying a certain credit as defaulted. Based on a unique data set of individual payment histories this paper proposes a definition of default which is based on the time due amounts are outstanding and the resulting profitability of the receivables portfolio. Furthermore, to assess the individual payment performance during the credit period, indicators for monitoring and forecasting default events are derived. The empirical results show that these indicators generate valuable information which can be used by the creditor to improve his credit and collection policy and hence, to improve cash flows and reduce bad debt loss.
Subjects: 
Credit Risk Analysis
Credit Default
Risk Management
Accounts Receivable Management
Performance Measurement
JEL: 
C44
G32
M21
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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