• DocumentCode
    1958473
  • 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
  • Volume
    2
  • fYear
    2012
  • fDate
    20-21 Oct. 2012
  • Firstpage
    5
  • Lastpage
    8
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Management, Innovation Management and Industrial Engineering (ICIII), 2012 International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4673-1932-4
  • Type

    conf

  • DOI
    10.1109/ICIII.2012.6339764
  • Filename
    6339764