Data Mining: A New Direction for the Talent Training in Audit Informatization

Abstract

The development of big data and cloud computing technology has brought new changes to the mode of production and operation in various industries, mainly reflected both in the more automated and informatized production process, and in the massively generated and well stored business data and financial data. And these changes are also a great challenge to the audit industry. For instance, over the last 20 years, computer-aided auditing based on SQL queries has witnessed enormous popularity in the government audit in China. Nevertheless, more and more experienced auditors have found that some frauds can be easily discovered through database queries, while others cannot. Taking the medicine makeup rate in China’s public hospital as an example, in the past, the rate can be easily calculated by retrieving the purchase price and sales price of various medicines from database, and audit conclusion can be obtained by referring to the regulations. However, with the enhancement of control mechanism of information system, such direct and blatant violations of the government price policy become increasingly rare. Nowadays, circumstances have become more obscure and the traditional method of querying has become more ineffective. For instance, doctors who received illegitimate funding from pharmaceutical companies would have the tendency to make improper treatment programs. Besides, problems like “large prescriptions”, over treatment, abuse of health insurance funds, inefficient using of medical equipment would not result in obvious frauds, which can be easily examined through simple SQL queries in database. However, employing various data mining algorithms, valuable audit clues might be captured.