Journal of Risk Analysis and Crisis Response

Volume 3, Issue 1, May 2013, Pages 44 - 51

Types of Credit Risks and Strategies to Improve Risk Identification by Internet of Intelligences

Authors
Chongfu Huang
Corresponding Author
Chongfu Huang
Available Online 1 May 2013.
DOI
10.2991/jrarc.2013.3.1.6How to use a DOI?
Keywords
Credit risk; Customer; Bank; Government; Internet of intelligences
Abstract

Today, people mainly consider credit risks from view of powerful players. The role of the Internet in the credit risk management is not fully. In this paper, we have a comprehensive look at the credit risks, so that, suggest two concepts: binary credit risk and triad credit risk. The Internet of intelligences is introduced to improve the recognition of credit risk. This paper shows the intensions of three binary credit risks, respectively, as well as overviews the main methods to analyze them. The study shows that, the bank’s customer credit risk is a simple credit risk. The indirect feeling strategy in internet of intelligences can improve the recognition of credit risk that would be seriously affected by changes in the political, economic and social environment.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Risk Analysis and Crisis Response
Volume-Issue
3 - 1
Pages
44 - 51
Publication Date
2013/05/01
ISSN (Online)
2210-8505
ISSN (Print)
2210-8491
DOI
10.2991/jrarc.2013.3.1.6How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Chongfu Huang
PY  - 2013
DA  - 2013/05/01
TI  - Types of Credit Risks and Strategies to Improve Risk Identification by Internet of Intelligences
JO  - Journal of Risk Analysis and Crisis Response
SP  - 44
EP  - 51
VL  - 3
IS  - 1
SN  - 2210-8505
UR  - https://doi.org/10.2991/jrarc.2013.3.1.6
DO  - 10.2991/jrarc.2013.3.1.6
ID  - Huang2013
ER  -