Detection of Financial Reporting Fraud Based on Clustering Algorithm of Automatic Gained Parameter K Value

Abstract

Listed companies' financial reporting fraud has been a major problem in the research history of accounting . It produces an extremely bad and wide range of influence on the development o f securities market . With the continuous development and progress of the stock market, the requirements for strict ly control ling and prevent ing financial reporting fraud are also increasing ly high . There have been a lot of studies of finan cial fraud at home and abroad . They are usually a bout motivations, means , identification and control ling of financial fraud . Financial fraud recognition is usually divided into signal judgment and model identification . However, the existing recognition mod el s’ acc uracy is generally not hig h. T here i s a large room for improvement and the models are not applicable enough . In addition, in the era of knowledge economy , with the continuous deve lopment of information networks , computer network technology is more and more generally applied in the field of finance. Especially the us e of computers in financial reporting fraud investigation can greatly reduce the manpower and resources as well as improv e the efficiency of identification. But it is not known that what kind of method combined with computer technology can better identify financial reporting fraud . In this case , the paper aims at establishing an accurate financial reporting fraud recognition model based clustering method .