Abstract
In recent years, online lending platforms have emerged a lot of insecurity events. How to judge the security state and health degree of the online lending platforms are becoming the most concerned problems for the investors and supervision departments. In this paper, we’ve adopted the massive data acquisition technology. Spark distributed computing, machine learning and other bigdata technologies to analyze the risks of the online lending platform. Then, a risk early warning model based on factor analysis method was proposed. Practice has proved that the model can help to improve the accuracy of the risk prediction to online lending platforms.
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