Technology best practices with
pre-scripted analytics
By Karen Kronauge, CIA, MBA
Product management consultant, ACL Services Ltd.
Audit and finance professionals consistently report in industry surveys that they understand the benefits of audit analytics. The vast majority of these audit pros realize that employing analytic-enabled audits is a matter of best practice. But despite this widespread awareness, many organizations struggle to implement sophisticated data analysis and continuous auditing and monitoring programs.
Companies often begin seeking more powerful technology solutions because they’re unable to hit internal targets. In fact, a 2009 State of the internal audit profession study by PricewaterhouseCoopers revealed that 86 percent of all organizations don’t complete their annual audit plans. So how can audit departments work smarter, more efficiently and achieve greater results with fewer resources? Taking advantage of both data analysis and professionally scripted analytics can be the missing link between planning and delivery.
However, creating analytic-enabled audit programs is not an easy task. There can be frustrating hurdles and a significant learning curve to overcome. In a busy audit shop when resources are increasingly stretched, it can also be difficult – especially for less technically proficient auditors – to carve time away from daily responsibilities to develop a smart, appropriate and effective data analysis program.
Where organizations commonly hit roadblocks
Even when an organization has the time and the intention to implement analytic-enabled audits, many hit common stumbling blocks. Automating data analysis is not just a matter of replacing a manual task with an automated test; rarely is it simply a one-for-one exchange. In fact, auditors can miss serious problems if they merely attempt to automate testing that was done previously. For example, a common task that auditors perform is manually checking a system’s settings. When attempting to automate this test, the auditor is best served by using analytics to review the population of transactions – and this transaction data is much more compelling proof of the appropriateness of that system setting actually working as expected.
Compounding this situation, many auditors struggle to recognize how analytics can apply to audit steps that have historically been performed through more traditional ways. Certain types of tests, such as checking for duplicates, are commonly understood. However, many auditors are unfamiliar with more advanced testing techniques, such as stratification, trending or statistical analysis, and thus do not even consider them when designing the audit automation program. Organizations that struggle with the concept of where to apply analytics within their standard audit programs can never fully recognize the value of analytics and often give up before they even get started. Using the assistance of experienced professionals can be invaluable to making what can seem like a daunting concept much more manageable from the outset.
Another challenge arises when auditors do not fully understand their audit data – which is critical to achieve accurate and meaningful results. In many cases, auditors will obtain transaction data, choose an analytic, run them together and receive unexpected results that could be interpreted as the analytic not working properly. Instead, unusual results often indicate that the auditor didn’t truly understand the data set that was acquired in the first place. This misunderstanding can arise from a variety of factors. Data frequently originates from an outside group (IT or another department) in an unfamiliar format, for example, and auditors might receive far more or less data than they requested. Confusion can be caused by the inclusion of reversing entries, special processing codes, irregular transaction types, or even additional columns. Applying analytics should require auditors to dig deeper into the data acquisition process. Ultimately, this gives them far better knowledge of their data and its potential deficiencies and control weaknesses. However, many organizations are unable to invest the time required to complete this process.
Effective implementation involves acquiring the necessary data, familiarizing oneself with the audit data, finding the appropriate analytic or group of analytics, identifying relevant sets of transactions, ensuring the analytics are performing as expected and, if necessary, further investigating the data or process that is being audited.
Overcoming challenges with professionally scripted analytics
For audit departments just beginning to explore data analysis technology, a library of pre-scripted analytics, such as ACL Services’ AX Accelerators, can significantly minimize lead-time and eliminate the hassle and expense of developing the needed audit tests. These tried-and-true analytics have been implemented in thousands of diverse companies across every possible industry. They are built with a user-friendly interface that walks auditors through a step-by-step process written in easy-to-understand language. Each of the Accelerators comes with plain language documentation outlining the logic used by the application, as well as reports that detail the analytic’s results in graphical representation.
While pre-scripted analytics can effectively serve a wide variety of organizations, each company also has specific needs or performs niche work that requires unique analytics. This is when implementation assistance is especially invaluable. For example, ACL’s expert consultants can either modify the pre-existing analytics, or build new custom tests from scratch. They are extremely skilled at creating client solutions that are highly usable, repeatable and sustainable. This kind of expert support can also anticipate snags, expedite the analytic implementation process, and help the audit department to consider key issues before they become problematic – such as understanding the data and building a monitoring program that fulfills the objectives of the annual audit plan.
AX Accelerators can also provide a benchmark that serves the audit department well into the future. The audit team can pick up analytics from a previous year, then review and adjust them for current use. Over time, these analytics provide familiar routines tailored specifically to the company’s needs, data types and processes.
Getting the most for your efforts
When the team is ready to progress beyond standard tests, pre-scripted analytics easily support additional ways to monitor specific data sets. Many companies begin analytic-enabled audits by looking for nitty-gritty details such as control weaknesses, exceptions and material weaknesses. Clearly, this is a valuable – and often financially lucrative – way to begin. But audit departments can provide even more business insight and value to their organizations by looking at process optimizations.
Running a transaction volume summary, for example, might reveal that an abnormally high number of transactions occur each Friday. This type of auxiliary test can lead to interesting findings and can help to uncover opportunities to save money, add value, and even pinpoint fraud.
Professionally scripted analytics can also be rolled out effectively to other internal departments, such as accounts payable or finance. Audit teams can help to schedule key analytics that run at desired intervals, or can be used as needed for one-off testing. AX Accelerators have built-in reports that visually represent the results in bar graphs, pie charts, and other easily understood formats. It’s an excellent way to link Audit with the entire organization and promote effective reporting to senior management – a collaborative scenario that many audit teams are striving to realize.
Getting there: Best practices in action
As audit groups work to establish repeatable, sustainable processes, it’s critical to consider how to apply analytics and house information. All audit data – including tests, write-ups, assumptions, conclusions and results – should be organized and appropriately labeled in a secure repository. It’s simply the best way to avoid replication errors, over-writing issues, lost data and other security problems. A comprehensive platform will give the audit department direct access to all their information without having to depend exclusively on IT.
Audit departments that apply targeted analytics and develop a secure library of effective tests will enjoy higher efficiency, better results and a stronger sense of independence. The barriers to implementing an analytic-enabled audit program can be daunting, but leveraging pre-scripted analytics can significantly reduce the investment of time and resources, while ensuring companies realize the full benefits of their technological investment.
When auditors can perform detailed investigations on complete data sets and use technology to follow a well-honed hunch, they will deliver greater value to the entire organization. That’s using audit analytics as a real best practice.
Karen Kronauge, CIA, MBA
Karen Kronauge is the President and founder of ConnectInt Solutions, a consulting company that rapidly implements intelligent solutions to improve business insight and managerial effectiveness. Before founding ConnectInt Solutions, Ms. Kronauge was responsible for the software division of a multinational consulting firm; acted as a Vice President for a regional investment company; and began her career as an Auditor in a global public accounting firm. She is a Certified Internal Auditor and has been a speaker at dozens of seminars and training sessions on subjects including knowledge management, corporate governance, internal controls, and compliance with the Sarbanes-Oxley Act and Bill 198.
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