Abstract
Credit risk management based on portfolio theory becomes popular in recent Japanese financial industry. But consideration and modeling of chain reaction bankruptcy effect in credit portfolio analysis leave much room for improvement. That is mainly because method for grasping relations among companies with limited data is underdeveloped. In this article, chance discovery method with directed KeyGraph is applied to estimate industrial relations that are to include companies’ relations that transmit chain reaction of bankruptcy. The steps for the data analysis are introduced and result of example analysis with default data in Kyushu, Japan, 2005 is presented.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Saunders, A.: Credit Risk Measurement (Japanese). Kinyu Zaisei Jijo Press (2001)
FISC: Working Report on Risk Management Model (1999)
Nakabayashi, A., Sasaki, M.: Models for credit risk measurement and its application to Japanese bank. FRI Review 2(2) (1998)
Torii, H.: Portfolio based credit risk management models – its effectiveness and limit. Weekly Kinyu Zaisei Jijo Magazine (June 1998)
Goda, S., Ohsawa, Y.: Chance Discovery in Credit Risk Management – Estimation of chain reaction bankruptcy structure by chance discovery method. In: Proceedings of the 2006 IEEE International Conference on Systems, Man, and Cybernetics, vol. 6 (October 8–11, 2006)
Ohsawa, Y.: Discovering risky subduction zones of earthquake. Information Technology for Chance Discovery, pp. 314–325. Tokyo-Denki University Press (2005)
Ohsawa, Y.: Visualizing relations between chances and surrounding events. Information Technology for Chance Discovery, pp. 121–153. Tokyo-Denki University Press (2005)
Shigematsu, K., Ueno, M., Motomura, Y.: An Introduction to Bayesian Networks, Baifukan (2006)
Motomura, Y.: Modeling with large scale data by Bayesian networks. JSAI Technical Report SIG-CII-9707-04 (1997)
Motomura, Y.: Bayesian Network that Learns Conditional Probabilities by Neural Networks. In: Workshop on Information-Based Induction Sciences(IBIS) (1998)
Cooper, G., Herskovits, E.: A Bayesian methods for the induction of probabilistic Networks from data. Machine Learning 9, 309–347 (1992)
Mathematical Systems, Inc.: BayoNet 4.0 manual, http://www.msi.co.jp/BAYONET/files/manual.pdf
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Goda, S., Ohsawa, Y. (2007). Chance Discovery in Credit Risk Management. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_89
Download citation
DOI: https://doi.org/10.1007/978-3-540-73325-6_89
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73322-5
Online ISBN: 978-3-540-73325-6
eBook Packages: Computer ScienceComputer Science (R0)