Title :
Financial fraudulence identification: Based on the data mining technology
Author :
Yuxin, Ning ; Wei Rong
Author_Institution :
Econ. & Manage. Sch., Xi´´an Petrol Univ., Xi´´an, China
Abstract :
In this paper,we firstly use orthogonal factor model to deal with relative variables and obtain independent factor characteristics,subsequently use the Naive Bayes method to build NBFA model (Naive Bayesian based on Factor Analysis). Based on this model we build the framework of the listed companies´ financial fraud identification. In experimental analysis section we identify the model 65 companies promulgated by the SEC fraud and 65 control group of non-fraud companies financial fraud,and the correct recognition rate achieves 90.77%, so we can see that the NBFA model can recognise the listed companies´ financial fraud effectively.
Keywords :
Bayes methods; data mining; financial data processing; fraud; NBFA model; SEC fraud; data mining technology; factor analysis; financial fraudulence identification; naive Bayes method; orthogonal factor model; Analytical models; Character recognition; Naive Bayesian classifier; class conditional independence; financial fraud identification; orthogonal factor model;
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering (ICIII), 2012 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-1932-4
DOI :
10.1109/ICIII.2012.6339764