the what, why and how of artificial intelligence for accountants

how practical, affordable ai is already transforming accounting.

by hitendra r. patil and eli fathi

co-author eli fathi is ceo at mindbridge ai, developer of the world’s first auditing tool based upon artificial intelligence and machine learning technologies – the ai auditor – to uncover errors in financial data. he attended algonquin college and the university of ottawa, where he earned a master’s degree in engineering. fathi has been a technology entrepreneur for over 30 years, having founded or co-founded numerous technology companies including fluidware corp. he currently sits on the boards of the ontario chamber of commerce, start-up canada, and c-com, a company that develops satellite-based technologies.

artificial intelligence (ai) tends to conjure up images of sci-fi movies, with costly computers replacing humans for some sinister purpose, but the reality is much more collaborative and effective.

while ai has been adopted by many industries, its adoption rate in financial services has been relatively slow, and for understandable reasons. but you can get a feel of ai’s possible impact when you see that 76% of banking cxos agree that adopting ai will be critical to their organization’s ability to differentiate in the market.

practical, affordable ai is here, and the question is not whether or not to adopt, rather it is how quickly to get on board to differentiate in the quality, effectiveness, and efficiencies that ai-based solutions can provide.

ai is poised to transform the accounting industry. let’s see why.

the fourth industrial revolution

in the 1950s, the first ai projects were defined by academics trying to understand whether machines could think like humans, simulating our behavior and ability to do intelligent things. the biggest advances over the past 60 years have brought us closer to thinking computers, from intelligent chess players to mobile phone assistants understanding natural language. so far, the progression has been computers built to understand the world at large, as humans do, but not actually replacing the nuance and inspiration that comes with human decision making.

in this manner, ai is evolving the accounting industry, by providing the technologies that ingest, analyze, and report on vast amounts of data, with perfect consistency and repeatability, to help accountants do better. in his book, “the fourth industrial revolution,” founder and executive chairman of the world economic forum, klaus schwab, states that data is becoming as valuable as oil and metal. the book references a survey that finds that one of the upcoming technological shifts will occur when 30% of corporate audits will be conducted by ai, which 75% of respondents expect to happen by the year 2025.

what is ai and what it can do

the accounting “software” you use every day is a series of programmed algorithms, i.e., “logic” that takes inputs and produces defined “outputs.” programmers (humans) build the “logic” in the code of the accounting software.

the dictionary defines artificial intelligence “as the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages”.

an easy to understand ai example is the “autonomously operating car” or the “driverless car.” just visualize what the car’s “software” does when the car is in motion and you get a feel for what ai can do.

ai can “understand” the inputs, outputs, and the correlation between them to define the “logic.” ai is the ability of a machine or a computer program to think and learn. programmers (humans) still do the programming for capturing inputs and organizing outputs. ai-based software tools that are used in accounting, tax, or audit contain pre-programmed algorithms that have the intelligence to learn what you are doing, adjust to inputs, and perform those tasks that you do to produce the outputs. but, it will not replace or displace you.

ai, therefore, automates many tasks that were previously done manually, and it can analyze up to 100% of the dataset without a human having to create the tests, potentially missing tests, or getting fatigued. it helps finance professionals identify related patterns of activity with more confidence and completeness than traditional methods and can detect anomalous transactions that may otherwise go unnoticed.

additionally, the very nature of the technology means that ai-based systems are continually learning and adapting to their environments. as these systems learn more about datasets, they can analyze secondary data and cross-correlate with the support of hundreds of variables.

ai can enhance the audit engagements by facilitating the ingestion and analysis of large sets of data to detect anomalies, such as unusual transaction flows within a ledger, rare outliers that lie beyond the ability for a human to detect, or potential risks in inventories.

ai has also demonstrated its ability to save costs in regulatory compliance, by automating manual tasks typically performed for compliance reporting and identifying instances of noncompliance. this streamlines processes and frees people to focus on higher-value activities for clients.

why is ai needed

the exponential increase in the volume of data collected, along with increasing awareness and scrutiny over the quality of financial audits, drives the need for technological innovation. it’s why the big four firms are ramping up their ai investments and why the rest of the industry needs to seriously consider making the leap.

previously, the only feasible method for analyzing vast quantities of data was to take small random samples and forego the time and effort necessary to analyze the full dataset. while conventional thinking is that this is “good enough,” recent events arising from financial failures, such as the collapse of carillion, have started a movement by the public to demand more accountability. these events have exposed the downside of sampling processes, with anomalies that are outside the sample set being missed and clues within the larger patterns of activity remaining hidden. sampling also limits the types of conversations and advisement that can be had with clients, as the accounting professionals can only report on the data that has been analyzed, not the entire set of transactions.

from the perspective of the accounting firms, the lack of or inadequacy of resources and the ability to attract the new generation of accounting graduates that are increasingly less willing to take on the traditional laborious work to shape and analyze the data set are critical factors creating significant human resources challenges.

traditional financial analytics tools that are currently deployed across the accounting industry often require technical skills and knowledge specific to the chosen platform(s). while these tools may minimize some of the analysis efforts, firms still need to find skilled resources that can spend the time designing and implementing rules, processes, and procedures that can change from scenario to scenario.

the traditional structure of accounting firms was that of a pyramid shape with a broad-base of entry-level accountants. but the human resource challenges are creating diamond-shaped organizations exhibiting a shortage of entry-level accounting staff.

ai can significantly address the challenges mentioned above to reduce time, efforts, and cost for firms as well as deepen and increase the ability of accountants to manage huge volumes of data and information – and to benefit from the new analytical abilities of ai solutions to identify hitherto hidden anomalies. ai can help accountants live up to the accountability demands and provide greater assurance to clients and regulators.

how is ai transforming accounting

it’s important to understand that, despite fears promoted in sci-fi movies, ai is not displacing the role of the accountant. rather, ai works alongside people, automating large and mundane tasks, and assisting with decision making when the data set is too large or complex. in chess, a common myth is that an ai player can outperform a human, but the reality is that a human-ai combination beats an ai machine alone.

as stated in a survey of 100 ceos and over 1000 banking employees, 77% plan to use ai to “automate tasks to a large or very large extent in the next three years.”

ai is transforming how business is done, adding value to traditional practices and boosting engagement velocity for audit, fraud detection, regulatory compliance, and more. by enabling accountants to dive deep into 100% of the data set and extract insights, clients can be advised with better evidence and more confidence.

ai is helping accountants improve the accuracy and quality of transactional data right at the data creation stage by deriving intelligence from historical, even client-specific data. at the same time, this “transactional judgment/decision-making” help that ai gives to the accountants while processing accounting transactions is also speeding up the transactional work to the levels of efficiency not seen before. these factors alone are directly helping accounting firms grow both the top-line and the bottom-line, by being able to serve more clients within existing resources as well as reducing the cost per unit of work produced by the firm.

ai is moving the audit process from hindsight, in looking at the rear-view mirror of the past year, to providing operational insight and offering foresight of the operations in the near future.

ai will not replace accountants and auditors, but accountants and auditors that use ai can replace those that don’t.

posted on november 20, 2018