1. At present, the application of big data in auditing is imperative. With the rapid development of informationization and paperless office, paper vouchers have gradually disappeared, and the traditional way of browsing paper vouchers has been unable to continue. At the same time, with the high application of business system, the simple violation of discipline can no longer continue, and the means of violation of discipline become more hidden.
2, the traditional single information access has been unable to find violations. At the same time, the country's requirements for full coverage are getting higher and higher, but the number of our (experienced) auditors is extremely limited. In some places, even large group enterprises with tens of billions of output value have only more than 20 internal auditors, but they need to cover nearly 200 subordinate enterprises at the second and third levels.
3. In the case of hundreds of internal audit projects every year, in such a working scenario, it is almost impossible to achieve full audit coverage by manpower alone, and the application of big data has become a necessity to complete the audit work. With the maturity of policies, big data technology, information environment and many other conditions, it is timely to implement big data audit.
4. From the policy guidance of national ministries and local governments to the internal audit (internal control) requirements put forward by front-line entities such as schools and enterprises to improve their management and business governance capabilities, it provides an important guarantee for the successful implementation of big data audit from the policy and demand. At present, the foundation of informatization construction has begun to take shape among the business entities that need to realize internal audit.
A large number of precipitated data provide rich data raw materials for big data audit.
1. At present, the big data technology for consulting and analyzing massive data is very mature. Because of the particularity of the audit process, it is often necessary to analyze the most original data, rather than the data that has been summarized many times. Before the big data technology is mature, it takes time to analyze tens of billions of data in real time by using traditional technologies such as relational databases.
2, and the computing power is unbearable for the internal audit department. With the maturity of big data technology, the computing power (corresponding cost) and time required for real-time analysis of PB-level data are greatly reduced, and it is not difficult to realize millisecond access of over 10 billion data. For internal audit, the audited object is relatively fixed, which means that the audit ideas and methods can be relatively solidified.