Chapter 1 Introduction

Within the accounting and audit profession, analytics has been around for several decades, under the concept of Computer Aided Auditing Techniques (CAATs). The software of choice was led by ACL and its ACL Analytics software. ACL Analytics was a significant audit enabler at the time, as it allowed direct access to analyze mainframe data and flat files that were otherwise inaccessible by mainstream software on the market. It enabled audit teams to obtain transparency in analysis, a rigorous audit trail, and even automation of scripts.

As computers, data analytic technology and accessibility of coding in the Accounting practice has become mainstream, there is an increasing number of options that enable auditors to become more powerful and self sufficient than ever before. Tools that are typically reserved for software engineers and statisticians have empowered financial auditors to expand their breadth and scope, enabling faster response and sustainability.

A traditional internal audit team would consider themselves to be consumers of information, limited by flat files sent by emails from their stakeholders. While most internal auditors have implemented data analytics in one way or another, the realm of possibilities and challenges have outpaced audit shop capabilities. The expectation now is for auditors to be fully integrated into the business, and contribute directly to the management of the financial and IT risks the company faces on a regular basis.

The most effective way to meet this new standard is to implement a current data analytics architecture and empower your team to leverage modern data analytics techniques.