[IMGCAP(1)](Continued from Part 1)

The younger generation of tech-savvy professionals is eager to apply technology to glean more from data and deliver deeper insights, if given the opportunity.

Unfortunately, their enthusiasm turns to discouragement when they approach management about using purpose-built data analytics tools. The objections are common across all industries. Educating management often falls on young professionals who make some valid points, if given the opportunity to be heard.

Getting the data is too difficult, plus we’ll have to rely more on IT, and they are already overloaded.

More than ever, organizations are dependent on information systems, and as data capacities swell, fraudulent activity is more difficult to detect. To keep pace with both data and fraudsters, professionals must use more advanced techniques and tools to prevent and detect fraud.

However, data comes in various formats, from different systems and sources, and is typically not provided in analysis-ready format. If you can’t access the data, you’re most likely missing opportunities to find and prevent fraud, and identify potential errors.

Where professional data analytics tools really pull their weight is their ability to bring in data from different sources and file types into a single tool for analysis. Today’s advanced analytics tools have the ability to import even the most challenging file types such as print reports and PDFs with minimal effort. With each new release, data analytics tools become increasingly easy to use and many include point-and-click buttons to further simplify commonly used applications. Bringing in data from different sources allows you to analyze 100 percent of available information from different angles to get deeper insights into what is transpiring throughout the organization. Data analysis technologies also enable auditors to access and query data without reliance on busy IT personnel.

Data security is a top concern of IT. When using a data analytics tool, the data is imported in read-only format, which prevents errors and manipulation. Data is safeguarded against changes, whether intentional or by mistake, which is critical when presenting evidence to stakeholders, or in financial statements. They provide an extra layer of security and assurance that the data has not been altered. This also helps professionals obtain better evidence for formulating audit opinions and understanding the root causes of findings.

We really don’t have the budget for new software right now.

True, budgets are tight and everyone is searching for cost-saving measures. Have you calculated the potential cost of not taking action?  Have you considered the potential ROI data analytics can provide?

Time is money, and when auditors are spending more time than needed to complete routine tasks, the audit lifecycle takes longer than necessary. This also prevents auditors from spending ample time investigating anomalies and exceptions, something that could be easily avoided by using sophisticated technology.

While management is comfortable having staff use the software that comes with Microsoft Office, the auditor or investigator is at a disadvantage when it comes to performing comprehensive and complex data analysis.

According to a recent report issued by Forrester Research, most companies only analyze about 12 percent of their data. What’s hiding in the 88 percent should keep management up at night. There is simply no way to manually sort through thousands, and in some cases millions, of records to find anomalies. Sampling a percentage of the population fails to provide broad enough coverage if they are looking for sufficient evidence to make sound business decisions. Data analysis tools assist auditors and forensic investigators in detecting patterns and relationships within large data sets by allowing them to look at the data from different perspectives, and providing 100 percent data coverage.

Technology gives users the ability to compare and contrast data from different sources. For example, you can compare an employee master file against an approved vendor database to look for potential conflicts or phantom vendors. Or, with just a few clicks, uncover duplicate payments that often uncover thousands of dollars in overpayments. Rapid ROI is achieved by looking at key areas where fraud and errors occur most often such as travel and entertainment, accounts payable, payroll, etc.

In terms of cost, the initial investment for a single-user license is $2,000 or less and includes a full year of support and maintenance. Some offer a perpetual license, and annual renewals are a quarter of the initial cost. Most data analytics users recoup the cost of the software within their first year of use either through efficiency or recovered overpayments.

As a consultant, I worked with a client who was approached by the Department of Justice with an allegation they wanted them to investigate. We used data analytics to import and analyze five years of data to present our findings. The client was so impressed with its ability to take in and examine large amounts of data to provide complete findings that they bought a few licenses for the audit department.  Eventually, the client increased the number of licenses given the added value of using data analysis software on audits.

The proof is in the results of what you’re able to achieve, and your ability to achieve the objectives. There’s no need to fumble with long, complex formulas or equations when a professional tool can do the same work in just a few minutes.  

Do we really need to use data analytics technology?

Yes! Regulatory requirements have shifted from “recommending” and “suggesting” the use of technology to conduct thorough audits to a “must,” mainly addressing growing data volumes, a mix of structured and unstructured data that must be analyzed and the ever-present risk of fraud that is not easily uncovered when using manual techniques. Utilization of technology gives management a deeper, more comprehensive view of what is transpiring in the organization. That alone is well-worth the investment.

Inventor Charles Kettering once said, “The world hates change, yet it is the only thing that has brought progress.” It’s time for change and progress. In my experience as a professor, students are drawn to the process of using tools in their audit work and investigations because they see the time savings, data access and coverage, and task automation capabilities it offers. Giving professionals the tools they need has an added benefit; it demonstrates an investment in their work. Some of the top reasons employees leave an organization include lack of professional growth opportunities, feeling underutilized and lacking the support to do their jobs well. Auditors who feel valued will not only stay put, but take a personal interest in helping the company achieve its goals.

Managers who put tools into the hands of young professionals reap the benefits. With a minimal amount of cost and training, data mining and analysis tools can be put to work to help companies assess risk and impact the bottom line.

Attributes of Data Analysis Software for Audit

[Source: The Institute of Internal Auditors (IIA) Global Technology Audit Guide (GTAG®) 16]

  • Able to analyze entire data populations covering the scope of the audit engagement.
  • Makes data imports easy to accomplish and preserves data integrity.
  • Allows for accessing, joining, relating and comparing data from multiple sources.
  • Provides commands and functions that support the scope and type of analysis needed in audit procedures.
  • Generates an audit trail of analysis conducted that is maintained to facilitate peer review and the context of the audit findings.
  • Supports centralized access, processing, and management of data analysis.
  • Requires minimum IT support for data access or analysis to ensure auditor independence.
  • Provides the ability to automate audit tasks to increase audit efficiency, repeatability, and support for continuous auditing.

Author Anthony Cecil has taught accounting, audit and finance students attending Utica College for the past decade. He is an experienced consultant, author and mentor. Cecil is an active member of the IDEA Academic Partnership, which provides technology and resources to students at no cost to help them develop critical thinking skills and data analytics techniques through hands-on instruction. 

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