Gang Chen* | Qing Feng | Jinpeng Liang
OPEN ACCESS
The paper researchs on the intelligent problem of guarantee system. For traditional guarantee system, because of low efficiency in risk control and mining customer value, increased risk of Guarantee Corporation oans and too long approval cycle results in serious loss of customers. To solve the above problem, put forward a new risk control method based on rough set neural network mode, and use Analytic Hierarchy Process and Activity Based Classification model to achieve customer segmentation. To do simulation with the sample data of 2005-2015 offered by Shenzhen Surety Association. The rough set and Back Propagation to be used in control risk, and the credit approval time is significantly reduce, and with the Analytic Hierarchy Process and Activity Based Classification model is to be achieved customer segmentation, that result in the company profit significantly increases. So the technique presented effectively in this paper.
Risk Control, Rough Set, Neural Network, Analytic Hierarchy Process.
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