Is AI accounting all smoke and mirrors?

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The buzz around artificial intelligence (AI) and machine learning may have subsided, but the arguments are still taking place within accountancy. John Stokdyk and Francois Badenhorst assess how these technologies are currently affecting the profession.

AI pushed itself to the top of accountancy’s agenda during the bot-fest of 2016-17, when every specialist software developer was touting its accounts assistant bot or the machine learning capabilities of its automatic coding algorithms.

Richard and Daniel Susskind crystallised the key debates around AI in their 2016 book, The Future of the Professions, which predicted that within just a few years, AI would sweep aside many of the attitudes and jobs of status quo accountants. The percentage estimates vary, but it is not uncommon to hear how accountancy is one of the most vulnerable professions, with 80-90% of its workload open to automation.

The promise of AI

Before giving into the “bots are coming” apocalypse, it’s worth looking more closely at the portfolio of concepts and processes surrounding AI to develop a better understanding of the changes that are taking place.

At one end of the spectrum are the natural language processing (NLP) tools that drive communications bots – interpreting the varied syntax of human speech and text and formulating an appropriate response. This was a fundamental element of mathematician Alan Turing’s famous test of machine intelligence: in his view a computer could be said to possess artificial intelligence if could mimic human responses under specific conditions.

Unit4’s Wanda, Sage's PeggQB Assistant and thousands of bots on public websites are proving that some chat interfaces are now able to pass the Turing test, but in the words of one banking executive at last year’s FinTech Connect event, “Chatbots are really bad at service.”

The other end of the AI spectrum lies deep within the world’s burgeoning data mines, where self-learning algorithms are used to determine usual patterns within the data and then spot uncharacteristic outliers. As Mindbridge’s John Colthart explained recently, these tools can help auditors discover material misstatements within accounting ledger data.

The ultimate example of “unsupervised learning” AI is Google’s AlphaGo system, which was able to learn and build on the rules of the ancient Chinese board game Go by playing itself around 5m times in three days. Not long after that it was able to defeat the world’s leading human player.

One of the building blocks of AI analysis is machine learning, which starts by matching common patterns and then learning what to do with similar items by copying what its human guides do. These systems are being applied to transaction autocoding in accounting systems like Xero and QuickBooks and numerous optical character recognition (OCR) and transaction capture systems.

Gerd Leonhard from the Futures Agency addressed the promise and pitfalls of AI at last November’s Xerocon. For him, the key question that Turning set had moved on from “Can machines behave like us?” to “Can machines be intelligent like we are?”

Machines might be able to look at data and process it faster, but that “doesn’t make them intelligent. It makes them faster at processing data,” he said.

“AI is a computer system that turns data and information into knowledge,” he continued, citing the cybersecurity intrusion detection, technical support, financial trading and even TripAdvisor as examples of intelligent assistance. But in the case of the latter, “What knowledge does it have about food? Has it ever eaten?” he asked.

Intelligent assistance is a powerful tool, but it can’t decide why you don’t want to have a particular expense on your books. Turning to the need for human intelligence, he explained that a modern airplane can fly itself – probably better than a human – but human pilots are needed to handle the tasks that a computer can’t – like negotiating with air traffic controllers or pacifying recalcitrant passengers. Leonhart’s summarised his argument: “You cannot automate ingenuity.”

The backlash

Wherever innovation leads, marketing inevitably follows. What this means in practice is that anytime a new buzzword appears on the scene, people in that marketplace race to apply the label to their products. Ask a supplier of accountancy software how they define AI, and their answer will be wrapped like cling film around the product they are trying to sell you.

Because AI is so wrapped up in abstract concepts and cognitive semantics, the opportunities are endless: when does an expense algorithm become a machine-learning aid, and how can you prove it, short of examining the developer’s code? That's assuming they would let you and that you had the skills to assess the sophistication of the logic – both unlikely longshots.

By this point, every software developer involved in this market will talk up their plans for embedding machine learning and AI into their products, and like Shangri-La, the fruits of these efforts are tantalisingly just over the horizon. These ever broadening interpretations fuel cynicism and disillusionment among prospective purchasers.

A botwash backlash recently broke out in the US around the claims of outsourcer Botkeeper when tech commentators Blake Oliver and Patti Scharf argued that the company’s bookkeeping bots were human bookkeepers in the Philippines rather than the automated accounting robots the company energetically implied in all the communications.

Just as Bill Clinton once argued, “It depends upon what the meaning of the word ‘is’ is,” Botkeeper CEO Enrico Palmerino tied himself into all sorts of mental knots to justify his company’s ambiguous claims.

On the strength of its disruptive, technology-driven approach to outsourced bookkeeping, Botwash raised $18m in Series A funding investors in November 2018. But while VCs have eagerly gobbled up anything labelled as AI, the marketing veil around AI has started to slip.

Even Google, feted for cutting edge developments like AlphaGo, was recently exposed in a manner similar to Botkeeper. Its Google Assistant relies heavily on massive data sets built by a squadron of overworked, subcontracted linguists.

“Artificial intelligence is not that artificial; it’s human beings that are doing the work,” a Google employee told The Guardian. Another worker called it a “White collar sweatshop”.

The academics Mary Gray and Siddharth Suri detail this reality in their new book ‘Ghost Work’. Beyond a fairly limited repertoire of decisions, Gray and Suri write, AI can’t function without humans in the loop. Human workers, like Botkeeper’s Filipino workforce, sweep up the loose ends.

The conception of Artificial intelligence, widely understood as processes making human labour obsolete, couldn’t be further from the truth – at least for now. For accountants, sold an AI bill of goods, along with the concomitant price tag, it’s certainly reason to maintain some degree of cynicism.

Tangible productivity gains

A degree of scepticism is clearly a healthy trait in the current market, but should not blind accountants to the real gains being achieved by the array of AI systems now being deployed within the profession.

MindBridge, quoted earlier, has been leading the way with audit aids and has broadened its reach in partnership with IRIS Software.

The millions invested by Big Four firms in these technologies are also beginning to emerge in public and interconnect, as an ICAEW IT Faculty post on a collaborative project called “Engine B” demonstrated. Engine B is the codename for a set of common data models (CDMs) for accessing client information. Now that leading auditors are on board, the big challenge is getting audit and accounting software developers to open up their databases and programming interfaces enough for the standardised models to operate effectively on different systems.

According to John Colthart, AI enables auditors, finance managers and regulators to test and report on complete transaction datasets rather than samples. “AI is not displacing the role of the auditor rather AI works alongside people to automate large data analysis tasks and provide new insights,” he said.

“By enabling auditors to dive deep into 100% of the data, clients can be advised on their financial health and compliance with more comprehensive evidence and greater confidence in risk assurance.” The potential savings are enormous, and could reveal new insights to help the profession deliver on its aspiration to deliver relevant, timely business advice.

About John Stokdyk

John Stokdyk, AccountingWEB head of insight

AccountingWEB’s Head of Insight has been with the site since 1999 and likes to spend his time studying accountants’ technology habits. When not nerding out, you can find him exploring obscure indie music and searching for the perfect organic sourdough loaf from his base in Brighton, UK.


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06th Jun 2019 10:59

I would say AI will help to a degree over time but not replace reconciling A properly to B. Which is where the real work is. The day you see a post from HMRC saying "Please don't worry about reconciling anything manually.. we are totally relaxed about the Accounts you send us and we will never impose a penalty of any kind if the software got it wrong and you relied in it..then we can all get the deck chairs out and start growing tomatoes...Until then....

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06th Jun 2019 11:07

Brilliant analysis and summary John. Like you I'm a tad cynical about some of the claims made around the subject.

I have long doubted the speed with which AI will change the work that accountants do. All manner of systems across the AI spectrum are having an impact and increasingly so. But the impact is slower than many proponents suggest. 'twas ever thus!

Those who embrace the new tech generally find it helps them work more efficiently and effectively. But equally the pioneers are often paying the premium price in terms of time (if not money) required to 'train' the new software and to develop new systems that 'exploit' it.

In the Susskind's wonderful book they lump accountants with other knowledge professionals and dismiss those who claim to be different.

However accountants ARE distinct as the profession is NOT a closed-shop. Our business skills also mean we have the potential to provide far more valuable services in the future with the assistance of products that include AI (or variations thereon).

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to bookmarklee
06th Jun 2019 11:27

I'm not so sure that taken as a whole all this AI is actually helping. Bits of it yes, but with it brings new problems. You only have to look at all the scams this new technology has encouraged.
Is MTD really necessary? How far should we be made to become "error free".

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06th Jun 2019 11:04

Artificial being the correct word.

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06th Jun 2019 11:13

[***] being the correct word.

I don't think the day will come in my career where I can get a bod to scan in tatty (or mislaid) bits of crap at one end and a perfectly-compliant set of financials spits out at the other end.

I'd love that tech, don't get me wrong...

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06th Jun 2019 11:30

I do not know about accountants in "Commerce".
For us in the profession this is mostly just another generation of fluff and hype. Yes, the days when I had to re-write a bundle of over 100 working papers with set of accounts because I spilled a cup of tea over them, or when my principal made me re-write a set of accounts because I put the comma in the date in the wrong place,
are long gone. Praise be to IT.
Being an accountant in public practice should be and is something different. In my small practice producing the numbers for, tax, for accounts, for comparisons, for office records, and all sorts has long been consigned to acceptably usable software. Well over 50% of my time is what I call TLC, tender loving care, helping my clients navigate through a bureaucratic swamp which has exponentially expanded during my professional life time. My impression is that most of my colleagues who I regularly meet at CPD, are in much the some situation.
I sincerely believe that software houses have an existential problem. I hold that the level with competence of software required by 90% of accounting practices, was reached years ago. It is 95% only because of the incestuous love affair HMRC has with IT that we require continual disruptive updates.
Unfortunately for software houses, "If it works don't fix it" is a death sentence. How will they survive without constant updates and maintenance contracts? It is called planned obsolescence.
For me, I will not install any new software except and unless the vendor can prove that the financial cost including cost of installation with learning time, will be outweighed by a demonstrable extra £profit.
Sadly HMRC is the exception since that organisation appears to work on Mao Tse Tung's principle that continuous revolution keeps the masses in order.
I am reminded of an article in the Times, some few weeks ago.
A govt spokesperson defended a £5 million software spend on the grounds that it would save £220,000 per year.
??? my question mark.

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06th Jun 2019 11:41

Good article.
I have two main issues with AI as currently engendered ...
1. "It" cannot always explain to humans the whys and wherefores of how it derives its endpoints - I hesitate to say 'decisions' - and from which inputs. This aspect includes the impact of 'implicit bias' which is much discussed these days.
2. (a).Under the terms of GDPR it is necesary to get explicit permission to machine process personal data - defined as data which can identify an individual [GDPR.Art.4,(1)] directly or indirectly.
(b). If, in the hamlet of Dunny-on-the-Moor, you are the only individual who pays tax at the higher rate then that fact together with the hamlet's name identifies you explicitly [to one with access to that info].
The impact of being 'identified' by AI as opposed to a human has nowhere, that I have seen, been addressed and I have grave doubts about the ability of the legal world to fully comprehend the potential privacy issues arising from this style of processing. Imagine auto-interaction of an accounting package AI engine and a HMRC AI engine, what/how they might discuss 'an individual'.
Frankly, it frightens me.

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06th Jun 2019 13:22

Great article John.
Sales people just love any new feature in the products they're tasked with selling to get the edge over the competition. Not a surprise, really.
AI is just another feature which I suspect will very short-lived, overtaken by something else soon.

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By Dandan
06th Jun 2019 13:48

AI has always been overrated. Your article seems to recognise this, I am happy to say.

Some accountants , however, seem to be getting excited over AI; thinking that it will reduce their workload. They should be thankful that business entrepreneurs make decisions with their brains and will power. If entrepreneurs started to rely on AI, there would not be much business going on.

The only trades that benefit from a form of AI (better referred to as fast calculation through programming) are Derivatives and bookmakers (not bookkeepers). Both use some laws of physics, especially the former . You could also add Actuaries.

As for the accountant, since it appears he wants to become a robot (and is already, anyway), I can understand the excitement over AI.

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07th Jun 2019 06:00

We let the boys do the heavy lifting so we can concentrate on other stuff.

For example I have a client who while using Sage was normally working catch up around 1-2 months behind on reconciliations etc. And would spend all our time with client chasing missing entries and reconciling Bank.

Now having implemented Receipt Bank, SaasAnt Excel Importer and Quickbooks into their work flow when I visit we are getting bookkeeping done up to the day and Management Accounts prepared to the previous month. Helps that 90% of their purchases can be auto published from Receipt Bank. We have had to take a slight reduction in analysis from within Accounting System in terms of splitting Sales and Cost of Sales by type (it’s a supermarket) but we can get that information elsewhere.

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