I am an auditor in public accounting. According to a study by Emolument, accounting jobs ranked in the upper half of the world’s ten most boring careers (Young). I might be biased, but I think this is a stretch.
Sure, maybe the old style-accounting could have been bestowed that title, but a lot has changed since CPAs around the world punched away on their ten keys while they took breaks from ticking and tying. The profession that protects the integrity of the capital market is, dare I say it, quite exciting.
I have spent the last year of my life auditing some industry-leading companies, and boring would not be a word I’d use to describe this experience. Most of the excitement can be credited to improvements in technology which have allowed me to spend my time handling more complex and interesting things, even in an entry level position.
On a very basic scale, instead of sorting through invoices to find the ones that match some expense selections, auditors are able to simply upload all the company’s invoices and the computer does the sorting and tying. In fact, artificial intelligence can even highlight unusual items and suggests testing. The concept, like with all big data and AI, is that with more data, comes more accuracy and ability. Luckily for auditors, there is no shortage of data.
Instead of trying to understand and review millions of journal entries (which would be impossible), auditors can feed the entire journal entry data through a processor. Auditors can then run reports that highlight unexpected anomalies, find entries using keywords that suggest fraud, and even perform correlation analyses between accounts to analyze the percent of correlation, which can be used to trace sales to cash receipt (Sidhu).
AI can even sort through trial balance data and categorize accounts as being low or high risk, giving the auditors a head start on their analysis (Bowling).
Auditors are able to use AI to understand a business in a more complete picture, as it enables them to summarize and present data like never before. This is a win-win for both the auditors and their clients — clients are able to spend less time pulling support and auditors can spend their time on value-added procedures.
Why this matters
Auditing, while boring to many (and I’m honestly impressed if you’ve read this far), is the backbone of the capital market. Auditors validate the financial statements that people around the world rely on to make investments with their hard-earned money. Auditors give the public the reassurance that they need and independently say whether the financial statements are presented fairly. They also comment on how effective a company’s internal controls are and point out potential areas of importance (i.e. will this company you want to invest in likely even exist in a year).
AI is thus indirectly giving you the ability to have more faith in a company’s reported financials, as it is reducing the potential for human error and oversight.
Excitingly, this is only the beginning. According to Jeanne Boillet, an Innovation Leader at EY,
The audit is set to be further transformed by deep learning, a form of AI that can analyze unstructured data such as emails, social media posts and conference call audio files (Boillet).
The future potential is really endless. Researchers, engineers, and accountants are testing the ability to use machine learning in interviews to detect fraud by recognizing facial cues for deception and verbal cues like hedging and hesitation.
Satellite imagery can be used to correlate revenue numbers with cars in a parking lot. (Dickey, Blanke, & Seaton). Inventory can be counted using drones and warehouses can be searched using robots.
Like with all machine learning and artificial intelligence uses, with the potential benefits come potential problems. Auditors will now have to determine what data is meaningful. They will have to assess their ability to properly interpret this newfound abundance of data. The skill set of the auditor will have to adapt. It is hard to say it, but the future of auditing is almost exciting.