Full metadata
Title
A Case Study of Credit Risk Analysis and Modeling for SMEs -In an Internet Finance Setting
Description
In the last two years, China’s booming of Internet Finance Platform made significant impacts on three dimensions. Compared with the conventional market, Internet Finance is asserted to open a revolutionary pathway of lending where by small and mid-sized companies may overcome the financing dilemma on credit accessibility and high cost. In other words, Internet Finance is hyped to be able to reduce information asymmetry, enhance allocation efficiency of resources, and promote product and process innovations for the financial institutions. However, the core essence of Internet Finance rests on risk assessment and control – a fundamental element applies to all forms of financing. Most current practice of internet finance on risk assessment and control remains unchanged from the mindset of traditional banking practices for small and medium sized firms. Hence, the same problems persisted and may only become even worse under the internet finance platform if no innovations take place.
In this thesis, the author proposed and tested a credit risk assessment model using data analytics techniques through an in-depth cases study with actual transaction data. Specifically, based on the 30,000 observations collected from actual transactional data from small and medium size firms of China’s home furnishing industry. The preliminary results are promising in spite of the limitations. The thesis concludes with the findings of relevance to improve the current practices and suggests areas of future research.
In this thesis, the author proposed and tested a credit risk assessment model using data analytics techniques through an in-depth cases study with actual transaction data. Specifically, based on the 30,000 observations collected from actual transactional data from small and medium size firms of China’s home furnishing industry. The preliminary results are promising in spite of the limitations. The thesis concludes with the findings of relevance to improve the current practices and suggests areas of future research.
Date Created
2016
Contributors
- Zhang, Qi (Author)
- Pei, Ker-Wei (Thesis advisor)
- Gu, Bin (Thesis advisor)
- Cui, Haitao (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
114 pages
Language
chi
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.38436
Level of coding
minimal
Note
Doctoral Dissertation Business Administration 2016
System Created
- 2016-06-01 08:05:46
System Modified
- 2021-08-30 01:24:31
- 3 years 2 months ago
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