Since last couple of years, the ongoing development in the area of artificial intelligence and blockchain technology has been creating a chaos about the future role of accountant and audit professional. Comparing to other industries it’s a relatively a new concept in accounting arena but gaining a momentum at very fast pace. Big four accounting firms are already deploying the artificial intelligence in some of the areas. Lately, they have invested heavily in the research and development of these technologies with the sole objective of introducing these technologies in day to day accounting and audit operations. The aim of this paper is to provide an overview, the implications these technologies will have on accountants, auditors and auditors/audit process. And also to shed a light on the skills that the professionals will be required to equip with to survive in the industry. A comprehensive review is impossible and beyond the scope of this paper, due to the pace of development in the technology and limited access to the literature. The real life industry examples discussed here should provide the impetus to accounting students/professional to get ready for the changes and to equip themselves better with the skills that will be sought after in the period ahead.
Since the inception of accounting, the role of accountant has undergone several changes from counting and keeping the stock records to predict future financial trends of the entity. But till date the professional are treated as a compliance specialist. Lately, in the wake of financial frauds that happened across the countries, the profession is losing its reputation. Peterson (2017) mentioned that “A conventional wisdom is gradually developing that the audit is largely irrelevant to the investment process today”.
Accountants and auditor work has been defined as the post mortem of the past transactions which has a little impact on the future operations of an entity. In the globalised trade the businesses generally prefer problem-avoidance and problem-containment to problem-solving. But currently the professional are reactive in nature rather than proactive. However, the latest trends in technology have the potential to automate most of the recording aspect which may lead to change the job profile of accountant. When technology will take over the mundane task, the professional has to be proactive to survive in the industry (Susskind 2015, p. 108, ACCA, 2016). These technologies could prove a helping hand to boost/maintain the confidence in audit process which had waned since 2008 in the wake of the global financial crisis. The blockchain and artificial intelligence are forward looking technologies that provide real time data and can contribute to change the future course of action (Smith, 2017).
Nixon (2016) is of the view that since the introduction of double entry system, innovation was stalled in accounting. The only change according to him is “things that used to be done on papers, shifted to computer”. However, the new technologies have the potential to take this profession to new level that has never witnessed before. Researchers and developers had termed it as the ‘Fourth Industrial Revolution’. The notable components of fourth industrial revolution are ‘Artificial Intelligence’ and ‘Block Chain’ technology (Schwab, 2018). The Blockchain has been labelled as the fifth pillar in IT revolution after mainframes, personal computers, Internet, and social media (Thakkar, 2017).
The Institute of charted accountants in England and Wales (ICAEW, 2017) commented that “in short to medium term AI will deliver more value to the business, aligned with opportunities for accountants to improve their efficiency. However, in long run radical changes will happen and machines will be replacing the human beings by taking over the decision making tasks”. In the wake of these technologies public perception about this profession will be change from ‘part of the problem ‘to ‘guardians of integrity’.
As per the survey conducted by Association of Chartered Certified Accountants (ACCA) there will be various factors (e .g. Globalisation, Regulation and governance, Social Accounting, Offshoring etc.) that will be effecting the accountants/audit professional works and will be requiring them to comply with the rules framed by various governing bodies. However, introduction of smart technology will effects the job profile of the profession. Regulatory framework is the second key factor that may have effect accounting professional but to most extent it’ll be embedded in the new technology (Oliver, 2000). By 2025, new technologies will transform the practice and competencies requirements. Susskind (2015, p.109) has categorized the technology impact on the profession in terms of automation and innovation. Means automation will lead to innovation in the required skills. To survive in the industry professional will have to acquire new set of skills i.e. gain more technical, social, marketing and communication skills (Ketz, 2016, ACCA, 2016). To foresee the impacts on the professionals, an overview on the working of these technologies, the applicability and impacts on current business scenarios has been discussed. Consider the cost factor the entities may prefer one technology over other so the Impacts on the profession has been discussed separately.
Basically accountants are the product of the needs and demands of the contemporary commerce and industry. Jones and Abraham (2007) stated that “accounting has always been the servant of wealth” while “maintain orderly functioning of commerce”. To meet the demand of industry, the role of accountant has evolved a lot since its inception, so its education implications.
History of accounting can be traced back to the origin of the trade in ancient civilization. In different parts of the world the sole purpose of accounting was just limited to counting and recording of the stock. With the advancement of economy, removal of trade barrier, introduction of money as a mean of exchange and to meet the industry demands, more responsibilities added under accountant’s umbrella from time to time. To meet the industry requirements accountants and audit professional had embraced the changes in the profession with open arms. It started in Bronze Age when the records were kept physically, then evolved to manual record keeping, then to excel sheets then to different accounting software’s and now the current one is cloud computing (Deloitte, 2016). Over the time period this profession has led to specialization in accounting branches and the accountant role has evolved into financial accountant, cost accountant, management accountant, auditors, forensic accountant, tax accountant etc.
Dabor (2008) had identified four stages in development of accounting profession as follow:
Pre-capitalist Period (4000 BC-1000 AD): In this period accounting solely was used for keeping the stock records, so was limited to counting and recording. No special qualification was required to keep these records.
Commercial Capitalism (1000-1750): Accounting profession evolved and flourished during this period. An Italian scholar Luca Pacioli (known as father of modern accounting) laid the foundation of accounting as practiced today and wrote a book on modern form of accounting i.e. double entry book keeping in 1494. Accountants were required to have some basic knowledge to keep and verify the records.
Industrial Capitalism (1760-1830): This period witnessed industrial revolution in Britain so the idea of capitalism emerged. Doubled entry system of book keeping flourish in this period. Demands for more in-depth knowledge of accounting practices were required.
Financial Capitalism (1830 onwards): First professional accountant body established in Scotland in 1854 and businesses started to demand a qualified accountant. To frame the accounting roles and assurance at large, American Institute of Certified Public Accountant professional body established in in 1887. Industry and business demanded accountant to provide in-depth knowledge of the account and the business demanded to separate capital and revenue, valuation of fixed assets, calculating periodic profit, publish appropriate contents of financial statements for investors and shareholders etc.
Till 1979, accountant work as very laborious as all the work had to be done on paper which was also an obstacle to get the timely information. The advent of first spreadsheet programme ‘VisiCalc’ in 1979 gave some relief to accountant and made their work much easier, efficient and quicker (Cooke, 2015). Till the advent of VisiCalc accountant needed to be well versed in mathematics formulas but it automated the calculation process and accountant didn’t need to have the root knowledge of mathematical formulas. The first accounting software named ‘Quickbook’ introduced in 1998 followed by different accounting software’s across the countries. Accounting software’s not only made the job easy but also helped the professional to expand their business. Accountant were required to upskill to meet the demand of technology. Public perception about the accountant began to change and more services added to accountant umbrellas like; interpretation of data, financial advice and involvement in tax matters etc. It required accounting professional to equipped with the computational and communication skills. The latest trend in accounting industry is cloud computing which was introduced in 2014. It didn’t require accountant to acquire any special kind of qualification nor has added any other service to accountant profile. However, on client side it has positive effects in forms of availability of real time information.
Technological advancement in the field of accounting has proven an augmented tool to assist accountants and had enabled them to take efficient and faster decisions e.g. variety of data analysis techniques in Excel, features of accounting software’s (like Xero, Quickbook etc.) to perform almost all the bank reconciliation by itself and availability of accounting information anytime and anywhere in cloud computing etc. In big organization most of transaction are recorded by itself in the system at the point of sale (i.e. scanning of barcode) and all the relevant ledgers are gets updated by itself, like inventory, cash, debtors, account receivable etc. However, till date all the technological advancement in accounting field have just proved a tool that can’t make any kind of decisions because of the fact that all these machine are working on rule-based programming and can process the structural data only (Baldwin, 1995). In-spite of faster and efficient processing of the data and software’s characteristics to analysis the data in different dimensions, still human input is the first requisite that is required to derive any meaningful information that can be relied upon. The ongoing research and developments in the field of technology is expected to bring robust changes the way all we work. The advent of computers changed the scope and the methods of examination. The advent of analytics will change the time scope of the audit (more proactive than reactive), the efficiencies, and the cost and benefit of the work (Issa et al., 2017)
Technology is spreading its wings at fast paced that never happened before and is already bearing its effects in some of the industries. In Sep 2016, Walmart laid off 7000 position dealing with management of cash flows and processing of vendor claims. In 2000, Goldman Sach’s was employing 600 traders in New York to buy and sell the stock, by 2017 it reduced to only 2 traders, rest of the people got replaced with machine (Byrnes, 2017). The study conducted by Xero in 2017 covering 600 accountants and SME owners (South African) concluded that technology will evolved the job profile of accountants, from number crunchers to consultants and specialist in strategic business review. However, 31% of the SME see don’t think they’ll need an accountant in a decade. The advance technologies like artificial intelligence coupled with blockchain and Internet of Things (IoT) will lead to automation of transactional data and compliance report (Ketz, 2016).
Before touching upon how Artificial Intelligence can disrupt the accounting field, it is imperative to understand the working and origin of artificial intelligence. The term ‘Artificial Intelligence’ was coined by computer scientist, John McCarthy in 1955 (Marsden, 2018). As per John McCarthy “Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs”. Wikipedia defines it as as an intelligence exhibited by machines. In computer science, an intelligence machine/device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.
In simple words Artificial Intelligence is the learning power of machine from its own past experience i.e. data feed and decision taken by it in the past. It is not a new concept but gain a momentum since last couple of decades due to availability of the resources/technological advancement in the other fields of technology e.g. exponential increases in computing power.
Deep Blue computer that defeated chess champion Gary Kasparov in 1997 and Watson AI that defeated two champions in Jeoparday game in 2011 are classic example of AI. Following picture showing the different stages in the development of AI.
Pic Source: https://digitalintelligencetoday.com/artificial-intelligence-timeline-infographic-from-eliza-to-tay-and-beyond/
Nowadays, directly or indirectly, we encounter with ‘Artificial Intelligence’ but not aware how it is interfering/assisting us in daily life e.g. computer showing the trends/material by itself based on past research, Facebook suggesting friends based on tag sharing service/school, university attended. Virtual assistants Siri, Alexa, Cortana can find all sorts of information for people, and they can talk to other machines such as alarm systems, climate control, and cleaning robots (McCollum, 2017). As per Isuru Fernando, Artifical Intelligence/machine learning is the way to improve the common behavioral mistakes on part of humans. While rationing, human are biased in observing, interpreting and evaluating so the mistakes happen. However, machine learning/artificial intelligence which learns from initial data feed does not possess the human attributes of biasness so least chances of mistake.
- Data Ingestion: It stores the vast amount of data
- Adaptive/Learning: Depending upon the situation and decision that made in the past it tries to adapt itself to the new scenario
- Unbiased: Processing of information and reasoning to arrive at a particular decision unbiased.
Artificial Intelligence can be classified as a structural or non-structural depending upon the functionality of the machine. Structural AI is unable to learn from itself rather works on the defined patterns. It’s the structural Artificial Intelligence that is playing a crucial role in couple of industries. Google self-driving car project that started in 2009 (Waymo, n.d.), the United Kingdom digital tax return platform launched in 2016 (Susskind, 2015) etc.
Non-structural AI or as it is called neural network has the ability to rationale. US justice department tool to assist lawyers in deciding the punishment is a classic example of non-structural AI. It’s combatively new in accounting arena and has not spread its wings to the fullest so is used in the limited working. For example, in United Kingdom, Deloitte is using AI tool ‘Revatic Smart’ to recover foreign VAT payments. It scans client’s document using OCR (optical character recognition) and automatically files the correct forms with little human input. (Susskind, 2015, p. 87). EY is using machine learning to identify fraudulent invoices, to review the lease accounting standards for the clients. EY fraud detection system has accuracy a 97% accuracy and been rolled out to over 50 companies. (Zhou, 2017).
As per Baldwin, Brown and Trinkle (2007) the concept of AI technology is not new to audit and assurance services. The expansion of research into expert system and other AI applications for accounting task, taxation, management accounting, financial accounting and analysis began in the 1980s. However, it’s limited to rule based expert system e.g. IRD, NZ personal tax calculator, online mortgage repayment calculator, determine eligibility of the applicants for welfare benefits etc. Rule based expert system can only handle the structural information but non rule based expert system is able to handle the non-structural information as well.
The area of accounting, auditing and taxation has lagged behind in adoption of AI due to the range of decision structure and involvement of non-structural information. However, non rule based expert system/neural network is getting momentum since last couple of years due to availability of resources in the field of technology. These developing technologies can serve as motivators of automation as well as change of accounting and auditing methodology. With the effective implementation of cognitive technologies, the audit process will become smarter, more insightful, and more efficient. This is the future of the audit profession, and the users of financial statements deserve it (Issa et al., 2017).
With the introduction of this system managers will be relying less on the accountants and auditors to have the timely information. On a click or by a giving a simple command, managers will be able to have the required information e.g. to have the sale turnover figures for different products based on tertiary, AI just be requiring a verbal command, a reminder letter to the aging account receivable could be send by just giving a command etc. Like that there are countless functions that can be implemented by a verbal command. It could prove superior to human in concluding any information.
Blockchain technology was conceived and initiated by Nakamoto Satoshi in 2008. Originally it was designed to transact the digital currency and recording of the transactions between two or more parties efficiently, without the approval of centralized agency and in a verifiable and permanent way (Wikipedia, 2018). Most of us have the misconception when we think about Blockchain, the only idea comes to mind is the bitcoin because originally it was invented for Bitcoin (Dai & Vasarhelyi, 2017). Blockchain is the mechanism that is behind the execution of bitcoin and other crypto currencies. Blockchain enables to generate an accounting information system that chronologically records validated transactions (Dai, 2017)
Peter (2016) has identified the following four principles of blockchain mechanism.
- Distributed: Blockchain is decentralized, and all participants in the network has a copy of same records.
- Public: The participants are hidden i.e. a participants may not know other participant by face but everyone can see all transactions by involved participants.
- Time-stamped: Each transaction and block is time stamped.
- Persistent: Blockchain transactions can’t catch fire, be misplaced or get damaged by water. Even if one participants system is stolen or catches fire the data is not lost.
Distributed ledger has been categorize into public and private. In public distributed ledger mechanism every party in the network has the right to read, verify, and update transactions to the chain. In private distributed ledger access can be restricted to certain level. Distributed ledger are having the followings attributes:
- It is a decentralized digital ledger which has collection of records with verifiable integrity. The entries are called block which can be seen by anyone on the network.
- The records are kept over number of stations i.e. each computer in the shared network have its own copy of record.
- The validated blocks/record have the time stamp and the trail of previous events.
- In public distributed ledger everyone in the network have the access to record.
- The records/blocks are immutable and indestructible.
- To establish a record each piece of block needs to be verified/validated by the nodes in the network. Once the record is establish it can’t be altered (Kokina, Mancha, Pachamanova, 2017).
- Blockchain is immune to manipulation as each new block of the transaction is linked to the prior block. Any attempt to manipulate the prior transaction necessitate a reprocessing of all subsequent blocks in the chain (Coyne, McMickle, 2017).
It is indestructible and incorruptible ledger that store and share the data in such a way that it’s simultaneously interoperable. Blockchain can make it easier to understand what assets are available in real-time in an entity, along with their values and can provide information on any other commitments that could affect cash flow in the future. Distributed ledger could rule out of the possibility of illegal practices in book keeping and also could help to overcome on illicit structuring of transactions and financial database manipulations. Since the inception lots of new features has been embedded into Blockchain technology e.g. ‘Internet of Things (IoT)’ and ‘Smart Contracts’. Unlike the centralize ledger the data is stored on various locations but rather is dispersed over a network of interconnected computers (Ernst & Young, 2015).
As per Peck (2017), this technology is poised to change nearly every aspect of human lives, from the way we send the money to the way we heat our home and mentioned that during the first half of 2017 alone, over 1 billion dollars was directed to the funding of block chain. Even the largest financial institutions; including J.P.Morgan, Goldman Sachs, and Barclays—joined forces in 2014 to explore how blockchain might increase efficiencies in the banking sector.
Till the advent of Blockchain mechanism all the data (electronic) was stored in a centralized system irrespective whether the machine is in local network/public network/or aligned with cloud computing. In centralized storage of data, control remains with the administrators who frames various policies to grant the access level to view or alter the data. Depending upon the access level whenever a change is made, the master copy gets updated and everyone in the network have the updated copy. There are too many risks and cost involved in protecting the data form natural and deliberate phenomenon e.g. keeping the backup of data, framing and updating security codes to protect it from hackers etc.
After the global financial crisis 2008 government across the countries have widened the scope of auditor duties and had imposed a stricter regime. In the wake of globalization the professionals not only have to deal with a large volume of data and but in the same time also have to comply with the different accounting and assurance procedures. Issa, Sun and Vasarhelyi (2017) have suggested that the humans perform poorly in the complex tasks that require the collection and aggregation of excessive information from multiple sources. This hold true in accounting and audit field and this is one of the reason that financial fraud does happen in the industry. But the deep learning/AI and blockchain can easily overcome this limitation of human, not only by providing the unbiased opinion but also to overcome and flagged the anomalies in real time.
Artificial Intelligence/Machine Learning/Deep Learning
Basically the accountants are recording and verifying the historical data against set standards, providing insight to the stakeholders and lodging the same with government agencies for tax or other purposes. The robust developments in the field of technology has automated the recording of the mundane tasks e.g. at point of sale (scanning the bar code) to its effects on the financial statements etc. that were performed by the accountants earlier. Combined with cloud computing accounting data have much more integrity e.g. when sale is made inventory records and its effects on operational profit are updated by itself and same records are available to each party involved in the network. In-spite of integrity in data and availability of information still management depends upon the accountants to conclude the hidden message behind the data. It is projected that accountant and auditors will be deprived from this vital function with the introduction of ‘Artificial Intelligence’ into the accounting field. Intuit 2020 report suggest the technology will displace the mundane tasks of accountant in near future. In the past technology led to improvement and productivity in data processing, in future the intelligent technology would be one the major driver of the change and believed that future would be marked by intelligent interpretation of information and decision making support (Henry, Hicks 2015).
Although accountant and auditors are using the latest available technology for deeper dimensional analysis of the data and are employing hypothesis techniques to predict the trends in future to overcome the errors and fraud but due to the volume of data to deal with and plethora of standards and policies to comply with, anomalies are still happening and the frauds remain undetected. Kokina and Davenport (2017) have suggested that, machine learning is particularly relevant when organizations wish to dramatically increase the speed, granularity, and productivity of modeling to deal with large volume of data and can be used for identifying anomalies in large datasets, which may be a basis for further forensic investigation. Machine learning is the next level of intelligence for analyzing numbers is machine learning, which is already being widely used outside of accounting to automate statistical and mathematical modeling. Traditional accounting and tax functions will be revolutionized by machine learning that offer real-time collaborations, scenario planning, cost modelling and risk simulation tools (EY, 2016). Anomalies in accounting books will be easily detected as the machine will analyze the scanned document and links it to appropriate record.
Artificial Intelligence Impacts on Book Keepers
I believe AI will largely have its impacts on the role of book keeper or entry level accountant role. They will be replaced by a virtual assistant. For example an ‘artificial intelligence’ tool (BOTKEEPER) that is catering to the small business entities (SME’s) has already taken over the book keeping function of the accountants. BOTKEEPER is a virtual assistant that that has the attribute to work on existing accounting software or to migrate and work on new platform apart that it offers unlimited reporting of any aspect of book keeping e.g. aging payable/receivable, unit cost budgeting etc., payroll, vendor mapping, reconciliation, collection calls and emails and many more (Botkeeper, 2018). It is performing most of the book keeping functions with accuracy using different accounting software’s like XERO, Quickbook etc. (Shieber, 2018). It retrieve and analysed the scanned data and post the transaction to relevant ledgers (Botkeeper, 2018).
Artificial Intelligence Impacts on Tax Accountants
Automation will also have its impacts on the work of tax accountants. Susskind (2015, p. 85-87) has mentioned that “Tax and audit have two things in common: they are heavily regulated, they involve regular interaction with the state, and the raw material upon which they operate is financial data. There are signs, however, that much that they do will be challenged by technology”. As per Intuit report 2020, accountant no longer will be focusing on preparing the tax returns and financial statements but their job will be to ensure that the automated data is complying with the regulatory laws. In that context the professional will be required to gain more computational and analytical skills. In UK, Deloitte is using AI tool ‘Revatic Smart’ to recover foreign VAT payments. It scans client’s document using OCR (optical character recognition) and automatically files the correct forms, with little human input. In 2014, in United States almost 48 million prepared their own returns online, without the help of any tax professional/accountant, the United Kingdom launched digital tax return platform in 2016 (Susskind, 2015).
The machines can do the repetitive tasks at super-high speeds, it will transform the way people interact with the tax function (EY, 2016). Not only it will provide the transparency and real time tax data but also will speed up the processing of tax returns. The process that is currently in place; to collate the transactions, differentiate between taxable and non-taxable transactions, prepare a return and then file it will no longer will be valid. Machine learning will be able to differentiate between taxable and non-taxable transactions at the point of scanning the barcode or incurring the actual expenditure. So real time taxable amount will be available to the entity and accountants or tax specialist will be deprived from this function. On the audit side, it will comparatively be easier for auditors to check the records.
However, on the other hand overseas sales/purchase may give rise to the issue of double taxation. So this area needs to be looked, whether accountant inputs still be required in this scenario?
Artificial Intelligence Impacts on Auditors
Another area that will mostly effected with the automation is Audit. Kokina & Davenport (2017) are of the view that the field of accounting in general and auditing in particular is undergoing a fundamental change due to advances in data analytics and artificial intelligence. As per the survey conducted by ‘World Economic Forum’ in 2015, three fourth of respondent expected that by year 2025, thirty percent corporate audit will be performed by AI. Welch (2017) has mentioned that, auditors will be able to use the cognitive technology in the field of tax planning and compliance will see a dramatic change in the next few years. As per Eleanor O’Neill (2016) big 4 accounting firms are already having a taste of artificial intelligence in their day to day workings e.g. since 2015 KPMG is using predictive analysis techniques (MAT) in its audit process and also aligned with WATSON to read the complex documents with given criteria. Similarly in 2016, to provide better auditing and consultancy services, Deloitte made an alliance with Kira System to read and analysis the complex and unstructured contracts and policies of the client. With the introduction of Kira System not only the employees are spared from doing the mundane task but it also has speed up the process (CISION, 2018). To harness and to predict the potential disruption of financial technology, PwC internal analysts and its clients are deploying a tool named DeNovo in their day to day workings (MIT, 2018)
As per the report KPMG is already using AI tools in its audit matter to distinguish between an expense which constitutes a deductible repair and one that is a non-deductible. By using the different aspects of AI auditors will be able to have the full-fledged knowledge about the entity. Issa et al. (2017) stated that “by scaling human skills and judgment through the application of cognitive technology, auditors will gain a more comprehensive understanding of aspects of the business” e.g. Deloitte Kira system is able to extract every bit of contract information depending upon the provided criteria.
With the evolving nature of business that is not confined to the local boundaries the auditors need lead indicator that can help to make an effective judgement. Mostly auditors consider the structural data structural information/data to make a judgement but the unstructured information also play a pivot role in deciding which direction an entity is moving in (Kokina & Davenport, 2017). With expansion of trade auditors are not able to attend each and every board meeting. Although the meeting notes are there but more chances to overlook the information especially the tone of the management. Which plays a vital part on concluding the hidden message behind any announcement. The features of AI such as speech and facial recognition can prove an extra tool for auditors to derive the meaningful information. Auditors can use AI tools to derive the hidden message behind board meeting notes or speech. Sun and Vasarhelyi (2016) explore textual analysis with deep learning. Their study utilizes the sentiment features of management earnings conferences calls generated by Alchemy Language API, a deep learning textual analyser, as predictors for material weakness in internal control over financial reporting and provides evidence that those sentiment features provide incremental information for the prediction task. But as a matter of fact that to gain something we have to lose something in return. Nothing is free in this materialistic world even the freebies like Facebook, WhatsApp regarded as free but to me the price we paid for these services is our personal life, our confidentiality, our time etc. Although, AI has a price and equipped with plethora of advantages so the firm will consider cost-benefit analysis to introduce AI for keeping the records. However, to introduce AI in book keeping and assurance services accounting and assurance bodies have to revamp the existing system in place. Baldwin et al. (2007)has suggested that even the juror’s evaluation off auditor legal liability is affected depending upon the fact whether the auditor has used technology in providing the judgement or not? Juror attribute lower responsibility to auditor’s relying on highly reliable aids, even when the aid was incorrect. However, to me this doesn’t sound correct as it falls under auditors obligations to check the effectiveness of the technology. If satisfied with the effectiveness then jurors may attribute lower liability to the auditors. However, Issa et al. (2017) has argued that relying on AI for audit and assurance purposes, auditors will be trading of their independence as they will be relying on the company machinery/AI. If they decide not to rely on the information provided by AI then they will be lagged behind and company won’t be requiring the auditors anymore. Artificial Intelligence/Deep learning no doubt will speed up the process and overcome the anomalies before it turned up into something big however, it will only provide the decisions or required result not the ethical consideration that it taken into consideration to arrive at specific results. The assurance work require justification for the work done if auditors won’t have that justification then they have to do all the work from scratch. In that scenario implementation of such technology will prove futile. Gershgorn (2018) has mentioned that Bank of America management wants to understand how the decision is made by AI/deep learning so that they can justify it to the legislative bodies the machine (AI) decision of accepting/rejecting the loan or credit card application. I assume that more research is required to shed light on this aspect of AI/deep learning.
So far artificial intelligence is not bearing the desired results where critical thinking play a crucial part in concluding the decisions. For example, most hospital have abandoned IBM Watson for Oncology to cure the cancer, likewise US justice system has abandoned the algorithm system that was used as an tool to concluded whether to sentence the criminals or not (Polonski, 2018). Mere relying on the AI capabilities to perform all the daily tasks may results in the financial losses as it witnessed in stock market “flash crash”. It happened in May 2010 resulted in wiping out $1 trillion out of the stock market (Cooke, 2017). The security board issued a statement that that “humans may need to wrest some control back from the machines” (Salmon and Stokes, 2018). Will be requiring intelligent people to decode the results/judgement provided by AI for the legal purposes. In case of court action, it won’t be wise to take the coding of AI/smart contract for defending purposes as even judge won’t be able to derive any meaning from it (Morrison, 2016).
How Artificial Intelligence impacts Demand for the Professionals
On the demand side for accountants and auditor, people have a flair of technology will be in demand to fill the supply gap education institution need to change their curriculum.
On the demand prospectus for accountants there are conflicting views. Demand pattern for the accountants is already going under some changes. Accounting degree or knowledge is not enough to land the job in accounting arena anymore. As per Crosby (2017), industry is now demanding the accountants having the digital skills, critical thinking, creative, presentation and communication skills. But what will be future prospectus for accountant, will they still be needed? There are conflicting views among scholars as the technology is in infancy. As per the report by Mckinsey Global Institute the value of AI is not to be found in the models themselves, but in companies and its people abilities to harness it, in the accounting field it won’t be possible to harness AI without the foresight of skilled accountant (Chui et al., 2018). However, paper published by ICAEW in 2017 suggests that (Institute of Charted Accountant of England and Wales) AI adoption in accounting field is in the early stage so it is too early to forecast how it will affects the accountants. As per Kokina & Davenport (2017), Ernest & Young (EY) new hires each year could will fall by half, which could substantially alter the industry’s employment model. Whereas Olivier (2000) is of the view that demand for control and assurance will increase in the business sphere. As per the study cognitive technologies like AI increase the productivity three time higher and offer the highest monetary return, equivalent to around $1.90 per employee for every $1 invested (Morrison, 2018). Considering the cost benefit analysis, definitely accountants will be at the receiving end. McCollum (2017) saw AI a challenge to internal auditor not as replacement but as upgradation of their skill. Internal auditor won’t be displaced but the job profile will be changed from doing the mundane tasks to implementing AI tools and its maintenance. Auditors will help identify and certify that machine learning and AI applications are being fair.
History is the witness that whenever there is a new invention, new human experience and capabilities actually emerged. In case of AI applicability to accounting domain, accountants can move from having a hindsight view to having more predictive foresight. Predictive foresight will enable the management in effective allocation of the resources e.g. what inventory to hold etc., so there will be need for the accountants but with a different set of skills. (Chiew, Yeong, 2017). Henry and Hicks (2015) have suggested that with the changing role of the profession, businesses will require two types of accountants: general business advisor and auditors. Even mention that current students won’t be requiring accounting knowledge rather than they need to develop a strong understanding of the business. Reams (2016) has suggested that the automation of transactional data no way eliminate the need for the professional, but rather empowers them to play a larger role in operations.
Considering the results beard by AI in other fields, the researchers’ claims that ‘Artificial Intelligence’ seems to be taking away the decision making powers away from the noble profession of the accountants. However, I believe research needs to be done to make it happen and also researcher’s needs to look into the following question?
If human make a mistake then he/she got penalized or have to face the disciplinary actions. I believe researchers need to dig further into the subject matter; who is to blame for the wrong output provided AI mechanism?
Skills that will be in demand and whether education sector ready to supply the army equipped with required skills?
Association of Chartered Certified Accountants (ACCA) report suggested that the sought after skills will be communication, team work, ability to collaborate, presentation, business awareness, data analysis etc. As the audit become more holistic, corporate reporting will become less about the numbers and more about the story of the organisation. So the professionals will need to acquire the data presentation skills. Boomer (2017) suggested that accountants may need to be well versed in mathematics and statistical skills. AI has not been incorporated into the accounting education curriculum. It may prove an obstacle in implementing the technology on wider scale. Due to infancy of the technology even faculty is not equipped with this subject. Morgan and Baldwin (1995) suggested that first faculty needs to recognize the need for AI integration. Secondly, learn about it. Thirdly, knowledgeable faculty can then implement the changes to accounting curriculum, then faculty can provide the knowledge to students.
AI and blockchain are capable of dealing with large volume of data in fraction of a time comparing to time consume by humans to solve the problem and the information provided is unbiased. Machine learning will enable the accountants to focus on strategic decision making, problem solving, leadership and relationship building.
Carnegie Mellon University in States is the first university to offer AI bachelor degree starting from fall of 2018 (Carnegie Mellon University, n.d.). Chartered Financial Analyst (CFA) reshaped its exam two years back to include algorithmic and high-frequency trading, and also covers economics, financial reporting and investment. To meet the industry demand from 2019 new curriculum will be covering artificial intelligence, big data and robo-advice (Pooley, 2017). KPMG is spending nearly $450 million on a campus set up to train its employees on new technology (Brinded, 2018).
And professional will be providng strategic services. In coming years, Google might replace the big four. It’ll provide more information than you can get from the auditors.
Literature Review: Blockchain
Since last couple of years, blockchain is getting popular as a mean of keeping the records. Originally invented for crypto currency transaction but the attributes of immutable records, time stamp, audit trail etc. is making it as a viable and effective alternate to reflect transparency in the business operations especially in record keeping. Paine (2018) has commented that blockchain will disrupt everything, especially the industries where data is stored, there’s an opportunity for blockchain to come along and take over things, but that becomes even truer when it comes to industries where interoperable data is required. Different entities using blockchain may gain access to records of other entities. PwC see blockchain as the ‘‘next-generation business process improvement software to structurally alter shared practices between customers, competitors, and suppliers’’ (PwC, 2016). And Deloitte expects that blockchain will improve collaboration among businesses and individuals, the transparency of business processes and data, and, ultimately, the productivity and sustainability of the economy (Deloitte, 2016). Several of the leading accounting software companies (Xero, Sage, Intuit, Intacct and NetSuite) are already investing in this technology (Boomer, 2017). And in August 2016, the Big 4 representative met with the AICPA (American Institute of Certified Public Accountants) to assess the applicability of blockchain to accounting industry (Del Castillo, 2016). Apart providing a platform for the functionality of crypto currency, currently this mechanism is being used in the supply chain to track the movement of the inventory. However, considering the interest of big companies and their investment in development of blockchain, I believe but it won’t be long to see its implementation in accounting and assurance fields. Irrespective whether it is Artificial Intelligence or real accountant is deploy to record the transactions, blockchain poised to bring radical changes in the accounting fields.
How it can enhance or impact the auditors
As per Don & Alex Tapscott (Bitcoin Revolution Book) some problems that exist in accounting can be overcome by introduction of block Chain ledger technology. First problem they defined is misleading information or lack of integrity by management in providing information on financial statement, even sometime auditors have no choice rather than taking this information true and correct e.g. the case like Enron, Lehman Brothers, Tyco and Toshiba proved that due to existence of vested interest management always does not act in integrity. If ledgers are kept using block chain technology this type of situation won’t arise as every tempered record will have time stamp and auditors could easily detect any kind of fraud. Second, involvement of human error, which sometime led to a big blunder.
Kokina at al. (2017) has suggested that real benefits of blockchain can be found in auditing through the establishment of a detailed audit trail, and ability to review the exceptions generated from a population of transactions rather than a sample. Audit trails can be documented on blockchain to facilitate tracing and review in the future. Similarly, information in electronic invoices, bills of lading, letters of credit, receipts, etc. could also be documented in the Blockchain (Ernst & Young, 2015). Accounting frauds happens when someone manipulate the accounting figures and principles. The features of blockchain combined with smart contracts will make it hard to manipulate the figures. Once a transaction is posted on the blockchain, it becomes unchangeable and irreversible and the transaction won’t be uploaded into the block unless verified by the majority. Even if the majority get succeeds in manipulating the records, it is time stamped and generate a new log with reference to the previous entry and manipulation can easily be detected at the later stage. The system itself protect the integrity of the data and make sure that there is less space to manipulate the data. The computers jointly supervise system operation and prevent the information in the ledger from being tampered with (Dai & Vasarhelyi, 2017). Apart that real time availability of the data in distributed ledgers could provide an opportunity to conduct more frequent audit or even on continuous basis with an increased sense of trust (Kokina et al., 2017).
Currently, auditors are dealing with the historical information that limit their capabilities to intervene and advice to management the right course of action. However, the features of blockchain will change their actions from reactive to proactive (Issa et al., 2017). In the globalisation of the trade it is a challenge for the auditors to verify the authenticity of PPE, Boomer (2017) has labelled it as the uncertainty in a trade and has suggested that blockchain is capable to overcome the uncertainty of identity (proof, security and privacy), transparency (asset tracking) etc. Blockchain attribute of measure the right and obligation over property will be make it easier for the auditors to verify the authenticity of PPE.
Blockchain combined with IoT (Internet of Things) will make it easier to measure the inventory without visiting the entity premises and can simplified the sale tax aspect of an entity. For example, smart contract will trigger the post events based on the geographical information transmitted via IoT (Dai & Vasarhelyi, 2017). Blockchain mechanism wouldn’t give rise to the situation like Anderson where they tore the audit papers, even the audited records are safe against removal so can be used as a legal aid on forever basis (Peck, 2017). As the whole idea is consensus the validate the records and availability of the data across various networks it offers the following advantages
- No unauthorized change in data
- Prevent cyber attacks
- Timely examination of potential errors and frauds
- Efficient control of the recording process.
- Real time information
- Saving in social cost of mistrust of corporate managers
- Data is not prone to threats
- Auditability of the information
To maintain stake holder’s faith, businesses are spending a huge sum of money for the verification of financial statements. Yermick (2017) has labelled auditor/compliance cost as ‘the social cost of mistrust of corporate managers’ and mentioned that blockchain records will bring savings in social cost. Nixon (2015) mentioned that accounting profession around the world has carved out billions upon billions of dollars in annual compliance revenue (which is basically history writing) because of heavy data and human involvement, which is going to be affected with introduction of smart technology. As per Susskind (2015) the ‘Big 4’ accountancy firms have a combined revenue of more than $120 billion. Coyne and McMickle (2017) have suggested, Application of blockchain/distributed ledger in accounting and assurance services mean reductions in fraud, greater transparency and less need to verify records across and within organisations. In that context it won’t be wrong to conclude that blockchain will have negative effects on audit and assurance services. As having more timely, accurate and transparent access to data will enable the decision makers to act proactively which will reduce the costs of intermediation (i.e. the need to incentivise a third party to verify transactions) and also it does not provide a central point of potential failure.
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