Abstract

At present, more and more cases of economic fraud are based on false bank accounts. Due to the limitation of the bank’s technology and ability to verify the true identity of customers, the online verification system of banks can only check the authenticity of the ID card, while the consistent verification of people and cards can only be completed manually by bank tellers. It is easy to produce errors if the consistency is judged by the teller’s manual naked eye. In this paper was proposed a method of constructing a naive Bayesian network classification model by automatically detect the authenticity of bank accounts to avoid the problem of economic fraud of false bank accounts, and verified the feasibility of this method through specific examples. The experimental results show that the method which has certain theoretical and practical significance, and provides reference for the detection of other false accounts.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.