Top 3 Reasons Why the Audit Command Language Is Best for Audit Analytics
One of the fastest evolving service industry is the field of data analytics. It has gone from being a general profile to predict or validate data points to serving specific purposes depending on a companies goals. Some firms prefer performing analytics within the firms. Others tend to look for skill outside the firm. As a consequence, analytics has found its way into different domains. Financial audit is one such domain. The Audit Command Language tool was designed to cater this particular area specifically. Listed below are reasons why it is appropriate to this service line
1. Realtime Logs – In the domain of audit analytics, it is imperative that all steps performed to transform the client data that is under audit are proven appropriately. These logs can form the basis of further substantiating any inquiries with the client regarding the data captured. This practice is specifically required for journal entry testing, revenue testing, payroll testing etc. All such data are sensitive in character and consequently logs provide indemnification to all involved parties to carry out a thorough audit.
2. Easy UI – The Audit Command Language has a rare for a tool built for data analytics. The user interface is not very intimidating. chiefly this is so because it is meant to be used by folks who are in the audit domain. Most professionals in this domain do not have technical backgrounds in scripting or coding. An easy interface makes it functional for existing professionals to carry out their responsibilities with very limited training on the part of the organisations. The user interface also allows for all procedures performed using the GUI, to be recorded as logs. This is also a quick way for professionals to learn the tool to automate certain responsibilities, which are repetitive in character.
3. Infrastructure – Unlike some other tools in the market place, the ACL Audit Command Language doesn’t require a great deal of investment in terms of infrastructure. for example, to set up the SAS enterprise guide, it would require a server to be setup to house the data sets in a certain schema or already SQL based tools like MS SQL server to require another tools like Excel to prepare and format the findings from the databases outputs. The Audit Command Language can be easily run on the users’ desktop or set up on far away servers, where each project is executed independently.
Having mentioned the advantages of the Audit Command Language, it should be noted that this tool does have some limitations that sometimes hinders the work that needs to be performed already in the audit domain. However, with its chief features serving the main purposes, it is strong foundation for audit firms to include analytics into their practices.