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AuditNet® Audit-news::Articles::Learnings-from-a-retrospective-in-analytic-auditing-by-rich-lanza

Rich Grant ThorntonGt Logo

Learnings from a Retrospective in Analytic Auditing

by Rich Lanza

This article was adapted from the provided chapter in Data Analysis for Internal Controls, Fraud Detection Monitoring and Audit published by Dave Coderre and available at https://caats.ca/

This article is a reflection of my personal journey of how computer technology impacted my life and 25+ year career in analytics. As you read further, I hope that you will see how technology can augment our life, or rather, biology with electronics. The word bionic itself is the combination of these two words by simply taking the first three and last four letters of these words. More on this letter technique will be explained later in the article.

Early Life Impacts

My career in computers started in high school with a TRS-80 computer and learning to make dots run across a screen in a variety of directions. Computer games we purchased were installed with an audio tape player as it fed instructions to the TRS-80 and displayed results on a TV we hooked up to the computer board. My greatest achievement was turning the “F” word into a 300 font printout on my dot matrix printer which hung on my wall when my parents weren’t looking. Little did I know that 25 years later, I would be chasing a different “F” word (fraud) throughout company databases.

College and Public Accounting Years

As I entered college, I studied public accounting and quickly lost all knowledge of computers and how they could impact the audit process. While we had a computer lab, it was mainly used by engineering students and we were handed a variety of colored pencils and green paper to document our work efforts. Thankfully, I was employed as an accounting intern at Coopers & Lybrand where I daily made use of Lotus 123, the precursor to Excel. If Malcolm Gladwell’s theory on 10,000 hours to become proficient in anything holds true, I had completed at least 2,000 hours in spreadsheets before leaving college. A head start on my counterparts who may not even know such a program existed in 1989.
My luck followed me from that internship to KPMG Peat Marwick who audited a technology company named Apple and, with Steve Jobs at the helm, was miles ahead of the competition in PC development. While we carried around large bags for our Apple PCs and monitors, I was able to continue amassing hours in spreadsheet and other PC applications when most auditors were using the paper-based platform. I quickly adopted any new technology being provided like Monetary Unit Sampling or automated workpapers, to name a couple.

The Internal Audit Years

After two years of public accounting and my CPA license requirements met, I decided to take a position one traffic light away from my home, as an internal auditor. Serendipity followed as in my first week, the audit manager pointed to a software box on the shelf and remarked, “See what you can do with the shelf-ware”. That software was ACL Desktop DOS edition and in my workings with the product, it was a complete eye-opener to my career and to the company who benefitted from the efforts. My perspective changed through the additional layer of data that we could now apply to every audited business process.

At that company, each location worked on a DEC-VAX accounting system that was connected via an online network, allowing anyone with clearance to access the business process databases like inventory or accounts payable. While this may sound common in today’s world, in 1992, this was complete magic given Emails were barely used and online communication resorted to fax machines. Through the use of the DEC-VAX system, I could identify audit findings from a central location and send them to the audit client in advance of our meetings. This led to more valuable discussion and insights when we made field visits since much of the rote testwork and follow up was completed via phone meetings prior to our arrival. Over time, we decided to “audit from afar” versus attending location audits and in person meetings became a way of passing results. One such set of results was integrating the purchases from all of our locations by supplier to help the central procurement department assess “buying power”.   

In another internal audit role, within my first few weeks of being hired, I identified over $100 million in vendor credits that again was in the procurement area (for more information, please see https://www.acl.com/2013/07/my-best-money-saving-audit-finding-ever/). While this discovery created much frustration for the Finance team, those same personnel recommended me for additional analysis in other company areas. It seemed that “finding” concerns more proactively was better than the alternative; being surprised by issues years later.

Starting My Own Firm

While working internally for companies, I had an outside life of writing books such as 101 ACL Applications: A Toolkit for Today’s Auditor, writing articles like “Take My Manual Audit Please” and speaking about my constant journey with data analytics. This led over time to independently working with consulting, as well as, cost recovery firms to help improve auditor efficiency while creating value, respectively.
In applying cost recovery, I learned that there is an easy way to get hired by any company. Simply show up and state that you will save them money using their useless data files. Once savings were created and only after cash was in their bank account would they need to pay us for our efforts. It sold like a form of magic or alchemy, to be more precise, which saved companies hundreds of millions of dollars over the past decade. Regardless which area of cost recovery applied, from basic vendor statement to advanced vendor audits, it all started with gaining access to data files that generally were never unlocked for their true value.

What owning my own company also did for me was to provide me a public presence, allowing me to work with a variety of clients in a short period of time. It also opened me to a world of other experts for collaborative efforts. One of my most beneficial relationships was working with Mark Nigrini and learning more of his “Benford’s Law” efforts. Mark needed someone to help automate his digital analysis into ACL Software and so we spent days stitching together ACL code with his Excel graphing macros to develop DATAS for ACL. This add-on to ACL and Excel allowed auditors to run a variety of digital analysis in a few mouse clicks and sold successfully through the early 2000s.

Transitioning From Numbers to Letters

Big Data has become the big talk these days and while to some may be yet another buzzword to throw around, it is not going away. Data is exponentially growing and no place could it more be true than in the world of text. As auditors, we have been trained to follow the money which equates to numbers yet text makes up over 50% of data files. Don’t believe me? Just consider an accounts payable file that will have more characters in the file devoted to source codes, descriptions and vendor names than it does to dates and amounts in that file.
The problem with text is that it needs to be summarized which means summarizing the component words in each description or name field, calculating frequencies of word occurrences and then applying statistical rules. To many auditors that are just getting started with numeric stratifications, these textual techniques can be daunting to deploy. If I had not listened to the great words of wisdom of Dr. Nigrini, I may have never realized that such text analytics could be simplified.

As explained further in research briefs (http://bit.ly/1jFD87b) and articles (http://bit.ly/1TGwvPS and http://bit.ly/21mEbsU), the first and last few letters of words could be summarized on to gain much of the benefits of textual analytics. In explaining the concept in the most expedient way possible, if we summarize on the first two and last two characters of words, we are looking at over 80% of the text in those words. Therefore, the same concepts in “Benford’s Law” that simplify numbers to 9 first and 99 first two digits could be applied to words using the first 26 letters and first two 702 letters. By framing data in this manner, we have been able to wrangle textual analytics into a much smaller frame of reference to simplify the approach and facilitate comparisons over time and to peer group data. 

Concluding Thoughts

With cheaper computing power by the day, analytics are not only here to stay but ready for a major advancement in the coming decade. Some concluding thoughts:
• Collaboration – We need more people using computers and data analytics to collaborate as it is in that feedback channel that new ideas are born, revolutionizing the ones of old.
• Differentiation – Throughout my career, I have used technology as a differentiator. One humorous example was I used to walk around with an Apple Newton device (https://en.wikipedia.org/wiki/Apple_Newton) in the late 1990s to take notes, mainly to show everyone in the room that I had avoided paper in every area. It was not the best at handwriting recognition but I marveled at what it accomplished nearly 20 years ago.
• Turn the F Word into the R Word - Use analytics to shine a light on business processes. In my youth as an amateur magician, nothing was more rewarding than watching someone realize you found or could predict “which hand it’s in”. Findings and fraud need not be the “F” word at companies. Rather, they can be fun to find recoveries of cash to the company’s bottom line. 

Bio

Rich Lanza CFE, CGMA, The Data Magician, has 25 years of audit and fraud detection experience with specialization in data analytics and cost recovery efforts. He currently is a Director of Data Analytics with Grant Thornton, LLP, where he is weaving analytics into their audit and advisory practices. Rich wrote the first book on practical applications of using data analytics in an audit environment titled 101 ACL Applications: A Toolkit for Today’s Auditor, in addition to authoring or co-authoring 18 more publications and having over 50 articles to his credit. Rich is proficient and consults in the practical use of analytic software including ACL, ActiveData for Excel, Arbutus Analyzer, IDEA, TeamMate Analytics and auditing with Microsoft Excel techniques. Rich has been awarded by the Association of Certified Fraud Examiners for his research on proactive fraud reporting.
To contact Rich, please Email him at rich.lanza@us.gt.com and to learn more about Grant Thornton’s audit analytic capabilities, Lumen, please see:
https://www.grantthornton.com/services/audit-services/audit-data-analytics.aspx  

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