Method for identifying medical insurance fraud based on principal component analysis algorithm

Abstract

The invention provides a method for identifying a medical insurance fraud based on a principal component analysis algorithm. The method comprises the following steps: acquiring medical insurance basic data and generating a medical insurance structural data set; performing standard treatment on various data, thereby generating a standard matrix; calculating a covariance matrix of the standard matrix, solving a characteristic equation of the covariance matrix of the sample and confirming principal components; converting the standard index variable into principal component scores; respectively calculating the average value and the standard difference of the principal component scores; calculating an abnormal threshold value under each principal component dimension according to the chebyshev law; taking each principal component as a coordinate, drawing a two-dimensional space scatter diagram, representing a practical medical insurance account by each scatter point and regarding a medical insurance reimbursement account with the value which is more than the abnormal threshold value in step S5 as an abnormal account. According to the invention, the medical insurance data is cleaned and settled; a principal component analysis method is adopted for performing feature dimension reduction on the variable related to the fraud; the abnormal threshold value is calculated according to a statistic method; and the high risk in medical insurance fraud can be identified.

Description

Technical field [0001] The present invention relates to the technical field of computer applications, in particular to a method for identifying medical insurance fraud based on a principal component analysis algorithm. Background technique [0002] With the development of society and economy, the state has made better and better medical insurance policies in order to provide a better medical insurance environment for the people. However, some people fraudulently obtain medical insurance through various means, resulting in an unreasonable loss of medical insurance funds. On the other hand, since the supervision model of the agency is mainly based on manual review and supervision, data screening methods based on simple rules are often used to carry out fund risk management work in terms of medical fund income and expenditure monitoring, simple indicator early warning, etc., which is not only slow , The labor cost is high, and it is difficult to ensure the accuracy of the identific...

AI Technical Summary

Problems solved by technology

This method artificially divides continuous variables into segments, which loses data information, and ignores the possible correlation between variables, which makes the total abnormal score lose accuracy.

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