Personal credit risk evaluation method and evaluation system for large-scale unbalanced credit data

A risk assessment, large-scale technology, applied in the field of personal credit risk assessment methods and assessment systems, which can solve problems such as large-scale, high-dimensional, sparse, and highly class-imbalanced

Inactive Publication Date: 2018-09-18
SUNYARD SYST ENG CO LTD +1
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Problems solved by technology

[0006] The purpose of the present invention is to provide a personal credit risk assessment method and system for large-scale unbalanced credit data for lar

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  • Personal credit risk evaluation method and evaluation system for large-scale unbalanced credit data
  • Personal credit risk evaluation method and evaluation system for large-scale unbalanced credit data

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[0056] The present invention will be described in detail below according to the accompanying drawings and preferred embodiments, and the purpose and effect of the present invention will become clearer. The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0057] The personal credit risk assessment method for large-scale unbalanced credit data of the present invention, such as figure 2 shown, including the following steps:

[0058] Step 1: To obtain the collected original large-scale personal credit record data set, construct the sample data matrix X for model training and the category label vector Y corresponding to the sample data, where X=[x 1 ,x 2 ,...,x p ]∈R n×p It is a matrix composed of a set of personal historical credit records data contai...

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Abstract

The invention discloses a personal credit risk evaluation method and evaluation system for large-scale unbalanced credit data. The method comprises steps that firstly, according to the acquired high-dimensional large-scale unbalanced historical credit data, a training matrix X constructed by the acquired historical data set is constructed, and the adaptive elastic network characteristic selectionalgorithm is utilized to implement dimensional reduction for the given historical credit data set; and secondly, a training sample set after dimension reduction is divided into a few of sample classesand a plenty of sample classes, the membership degree of each sample is calculated according to the cluster-like centroid distance exponential attenuation function, a weight matrix W is constructed,relevant parameters are set, and an IWELM model is utilized to implement personal credit risk evaluation. The method is advantaged in that a high-degree unbalanced problem shown by the large-scale credit data is overcome, the speed and efficiency of personal credit risk evaluation are further improved, and reliability and credibility of the evaluation result are improved.

Description

technical field [0001] The invention relates to the field of data evaluation, in particular to a personal credit risk evaluation method and evaluation system for large-scale unbalanced credit investigation data. Background technique [0002] At present, personal credit risk assessment methods for multi-channel, fragmented, heterogeneous, semi-structured and unstructured credit data are increasingly valued by financial service institutions. Due to the large-scale, high-dimensional, sparse and highly class-imbalanced characteristics of the currently collected credit risk assessment data, it is required to reduce the corresponding attributes of the data before training the assessment model to improve the quality of the original data set and information density, so as to help establish a more effective personal credit risk assessment model. In this process, it is necessary to use the corresponding feature selection algorithm to reduce the dimensionality of the rough original dat...

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Application Information

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IPC IPC(8): G06Q40/02
CPCG06Q40/03
Inventor 徐达宇魏致善蓝倩施宇伦林路
Owner SUNYARD SYST ENG CO LTD
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