Accounting in Big Data Era: Tech Advancements & Changes

The Accounting Profession in the Big Data EraIntroductionWith the technological advancements in all sectors and functions, the new concepts of continuous auditing, big data, and robotic process automation emerged. These technologies started impacting various industries including the auditing industry and are expected a much larger transformational impact in the upcoming years. The paper aims to study the impact of the emerging Big Data concept on the accounting profession in the near future. This includes an analysis of how this technology would enrich and enhance the quality, efficiency, and effectiveness of the accounting profession.

A second focus will be about how these changes in the accounting function will impact the accountants' jobs including a discussion about whether the accountants' jobs are threatened by the introduction of this technology. This research paper attempts to respond to the following research question: How will the auditing industry be impacted by the rapidly emerging technological concept of continuous big data? The paper answers the question in terms of the extent of improvement that this technology will bring to the accounting industry and how will this technology affect the career prospects of the accountants and the current accounting students.

Get quality help now
Bella Hamilton
Bella Hamilton
checked Verified writer

Proficient in: Accounting

star star star star 5 (234)

“ Very organized ,I enjoyed and Loved every bit of our professional interaction ”

avatar avatar avatar
+84 relevant experts are online
Hire writer

What is Big Data?Data is the new oil is one of the popular catchphrases; 90% of the world's data has been created since 2010 is a frequently mentioned fact (Al-Htaybat & Von Alberti-Alhtaybat, 2017). In fact, the IBM Big Data Flood Infographic shows that 2.7 Zettabytes of data exist in the digital universe today [and] 100 Terabytes [are] updated daily through social networks this leading to an estimate of 35 Zettabytes of data generated annually by 2020 (Ularu, Puican, Apostu, & Velicanu, 2012).

Get to Know The Price Estimate For Your Paper
Topic
Number of pages
Email Invalid email

By clicking “Check Writers’ Offers”, you agree to our terms of service and privacy policy. We’ll occasionally send you promo and account related email

"You must agree to out terms of services and privacy policy"
Write my paper

You won’t be charged yet!

The world today has access to unprecedented volumes of data which brings a challenge to our ability to analyze and gain new insights from the data. And from here comes the importance of big data as a significant opportunity for businesses to utilize it for strategic advantage.As Big Data analytics is one of the most hyped and fast growing technological concept in the world today, there is no consensus on the definition of big data. It is defined by Deloitte as structured and unstructured data generated from diverse sources in real time, in volumes too large for traditional technologies to capture, manage, and process in a timely manner (Errity, & Lucker, 2013). The main characteristics of Big Data that challenge the capabilities of modern information systems are its huge Volume, high Velocity, huge Variety, and uncertain Veracity (Zhang, Yang, and Appelbaum, 2015). Big Data is very substantial and impressive, however, in order for it to be useful, it should be processed and analyzed in the right way. As the pre-mentioned notion data is the new oil implies, Big Data is an unrefined and raw resource that, in order to be useful, needs to be refined, i.e. cleaned, structured and processed in order to generate any useful insight (Al-Htaybat & Von Alberti-Alhtaybat, 2017). Big data unlocks revolutionary opportunities for various business applications including their significant usefulness in the applications of marketing, supply chain management, human resources, and accounting and finance. Big Data and AccountingAs accounting is a field that heavily constitutes of data, information, analysis, measurement, and reporting, it is of no doubt one of the most impacted fields by the Big Data revolution. The following sections will have a brief discussion about some of the effects that Big Data bring to managerial accounting, financial accounting, and auditing functions.Managerial AccountingManagerial accounting involves identifying and evaluating quantitative and qualitative financial data to help the leadership formulate significant decisions to meet the business goals and missions. A report by Chartered Global Management Accountants revealed that 86% of professionals surveyed stated that they are struggling to get valuable insight from data (2013). However, with big data mined from both internal and external data sources, management accountants now can utilize data analytics techniques to answer the questions including: what has happened (descriptive analytics), what will happen (predictive analytics), and what is the optimized solution (prescriptive analytics) (Appelbaum, Kogan, Vasarhelyi, & Yan, 2017). One of the most powerful benefits of Big Data is simply its ability to make greater availability, visibility, and transparency of information for decision makers (Barker, White, Mozafari, & Ha, 2016). The analytics of big data fosters the abilities of executives to measure and improve businesses, market, customers and directly transform this data into enhanced decision making (Frankel & Reid, 2008). Managerial accountants use behavior-regulating devices called management control systems (MCSs) to align the organizational goals with the behaviors of managers and employees (Warren, Moffitt, & Byrnes, 2015). According to Warren, Moffitt, & Byrnes (2015), Big Data can play a role in MCSs by discovering behaviors correlated with specific goal outcomes, which would prompt the creation of corresponding performance measures. For instance, the Balanced Score Card gathers data in the following areas: financial, customer, internal business process, and learning and growth. Inside each area, Big Data can recognize new behaviors that impact particular goal outcomes. They further state that Big Data analyses can facilitate the discovery of important measures to be incorporated in MCSs. Companies use metadata to track performance. For example, employees are monitored on the time they spend using phones, emails, surfing internet, and using Microsoft excel. Big Data can be useful in finding out new motivational measures to managers and employees by discovering relationships between different types of data. In fact, Big Data analytical tools can uncover correlations in very large datasets between performance and numerous variables that were previously not studied. This allows revolutionary positive changes in the work of managerial accountants that makes their work more valuable and efficient to the frame the decisions of the top management. Of course, budgeting constitutes a major role of management accounting. For example, planning and budgeting for the production process is a fundamental role of managerial accountants in all companies and for that they rely on historical costs and expected profits. However, in big data era, the models for analyzing expected sales could include additional factors, such as customer behaviors, cultures, and competitors of target markets (Wang & Wang, 2016). The analyzed information extracted from Big Data will yield to a more precise prediction and thus, to a better strategic decision. Today, many are implementing beyond budgeting techniques that involves the use of substitute sources of information for performance evaluation, communication of objectives, and strategy formation (Bourmistrov and Kaarboe 2013). Big Data, including additional streams of data outside ERP systems (e.g., climate, satellite, census, labor, and macroeconomic data) could be used to enhance beyond budgeting practices (Warren, Moffitt, & Byrnes, 2015). Financial Accounting Financial Accounting is concerned with keeping track of transactions of the company and recording, summarizing, and presenting data in accordance to standardized guidelines. The main goal of financial accounting is to enhance the reliability and relevancy of accounting information and to better comply with the followed accounting standards. Although bookkeeping aspect of accounting is still reliant on traditional documents like invoices and shipping receits, Big Data will act as a great complementary to the traditional documents to make the accounting information reported more precise and relevant. Big data facilitate the better achievement of this goal as it makes it possible to generate accurate and timely accounting numbers that are supported by multi-format evidence (Tang & Karim, 2017). For instance, this technology can combine non-financial data such as text, image, video, or audio with financial data to verify the amount in a miscellaneous expense account. Another example would be using the Big Data technology in evaluating the creditworthiness of the customer including her transaction history and reputation through incorporating data from news and online reviews; this would enable the financial accountant to have a better estimate for the bad debt account. Warren, Moffitt, & Byrnes (2015) mention two aspects of financial accounting that will be significantly influenced by the revolutionary Big Data technology: Off-balance sheet items and fair value accounting. According to Kieso, Weygandt, and Warfield (2013) balance sheets usually exclude several intangible items of substantial importance because it is difficult to decide their values objectively. These items include customer base, human resources, product quality, vendor base, and company reputation and are so valuable to stakeholders as they play a role differentiating the company and delivering competitive advantage (Warren, Moffitt, & Byrnes, 2015). Companies worldwide are investing more in technologies that incorporate those intangible assets into the balance sheets because traditional financial statements are becoming increasing less relevant. According to Warren, Moffitt, & Byrnes (2015), to achieve this incorporation, companies should first comprehend the characteristics and nature of those intangible assets, and here exactly where Big Data can help. They say that, for example, key indicators associated with a target asset could be accumulated, processed, and analyzed via data-mining algorithms (P. 402). The results would have immediate value potential to stakeholders. In the short run, the data will be most qualitative and disclosed in the supplementary notes of the financial statements. However, in the long run, as Big Data analytical tools develop, substantially quantitative valuation methods could be developed for these soft assets, allowing them to appear in the actual financial statements. It could affect [also] the evolution of accounting practices, thus influencing the manner in which reporting takes place (Warren, Moffitt, & Byrnes,2015, p. 402). As for the impact of Big Data technologies on fair value accounting, Warren, Moffitt, & Byrnes (2015) also believe that Big Data assess in addressing the issue of discrepancy between Generally Accepted Accounting Principles (GAAP) and International Financial Reporting standards (IFRS) fair value accounting and facilitate developing a global set of accounting standards. One prospective method for facilitating this process entails the use of long-lived Internet software agents [that] would collect information to assist in the valuation of otherwise hard-to-value assets by using extensive automated Internet search methods running over extended periods of time (Warren, Moffitt, & Byrnes, 2015, p. 403). Thus, much might predicted in the few upcoming year on the role of Big Data in aiding the development of accounting standards that are recognized globally.AuditingBig Data is changing the auditing function and is expected to lead to more efficient, effective, and high quality audit (Alles, & Gray, 2016). The potential advantages of incorporating Big Data into audits include a strong predictive power, gaining access to massive data sets to identify fraud activities, the ability of analyzing all data, and developing more predictive models of going concern, using leading indicators of sales and costs (Alles, & Gray, 2016, P. 51). Kelly Todd, a managing member and the member in charge of forensic investigations with audit firm Forensic Strategic Solutions thinks that it is a huge jump to go from traditional audit approaches, which are based on sampling transactions, to an audit that looks at literally everything. She states that the reality is with data analytics, you have the ability to look at 100 percent of the transactions; you can see the footprint of the beast, the unusual patterns, and the things that don't make sense (Whithouse, 2014, P. 1). An EY report titled How Big Data and Analytics are transforming Audit by Ramulkan (2015) states that the transformed audit will expand beyond sample-based testing to include analysis of entire populations of audit-relevant data, using intelligent analytics to deliver a higher quality of audit evidence and more relevant business insights. He further states that Big data and analytics will enhance the auditors' ability to better detect financial reporting, fraud and operational business risks and tailor their approach to deliver a more relevant audit. A report by PWC (2015) also states that Big Data are altering the way the audit process is done at both the transaction and general ledger levels. Auditors have new tools to extract and visualize data, allowing them to dig into larger, non-traditional data sets and perform more intricate analysisBrown-Liburd, Issa, and Lombardi (2015) explain how Big Data Analytics can help the auditors in assessing high-risk areas such as assessing suspicious transactions. For instance, payments exceeding a certain threshold usually require approvals. To avoid this, some users may resort to keeping the amount of the transaction just below the threshold, or dividing the amount into multiple transactions, a phenomenon known as split payments (Brown-Liburd, Issa, & Lombardi, 2015, p. 453). While these transactions are not against any internal controls, the frequency of such transactions can raise a red flag. Big Data Analytics can uncover patterns in these transactions that would remain otherwise unknown, [and thus,] Data Analytics used to extract information from larger volumes of data can help auditors identify high-risk areas where they should focus their investigative efforts (Brown-Liburd, Issa, & Lombardi, 2015, p. 453). Hence, it can be concluded that Big Data Analytics will bring more efficiency and effectiveness to the auditing function that will allow auditors to focus on more complex and risk areas and spend more time on the Judgmental parts of the analysis. Big Data and the Future of the Accounting and Auditing Profession With the various benefits that are reaped from Big Data and the accompanying technologies of Data Analytics, Artificial Intelligence, and automation, there are serious concerns about the future career prospects for accountants and auditors. As previously discussed, with the availability of Big Data, a many cognitive tasks are becoming completely computerized. Frey and Osborne (2013) predict a 94 percent probability that accounting and auditing jobs will soon become automated. In fact, Richins, Stapleton, Stratopoulos, & Wong (2017) state that the threat Big Data Analytics will replace many traditional tasks performed by the accountants is particularly apparent in auditing. They explain that, for example, instead of relying on traditional sampling techniques to perform tests of detail, automated processes could examine entire populations for unusual patterns and anomalies (Richins, Stapleton, Stratopoulos, & Wong, 2017). With the new dimensions of accounting and auditing shaped by Big Data, accountants' jobs are not only threatened by automation, but also the jobs are threatened by non-accountants who have data analytics knowledge and can take over many accounting jobs. This should raise a warning to all accounting professionals and students to be able to cope up with technological revolution of Big Data by equipping themselves with the necessary skills. However, whether Big Data presence denotes a danger or an opportunity to the accounting profession is up to accountants. Big Data with no doubt adds substantial value to the profession by increasing the efficiency and effectiveness of accounting processes and thus, by allowing accountants to focus on high-value, judgmental areas of the profession. Accounting professionals can view Big Data as an opportunity to add value to their professional careers by moving away from restricted themselves to book-keeping and number crunching tasks that can be easily replaced to developing Big Data Analytics skills that allow them to perform highly cognitive tasks that is of high added value to the business. Hence, academics and educators must revamp their accounting and auditing curricula to provide the necessary skills for Big Data in the accounting and auditing profession (Griffen & Wright, 2015). By equipping accountants with Big Data Analytics skills, they will be future-proof as accountants. Conclusion and RecommendationsIn this paper, I tried to spot a light on the impact of the Big Data technology on the accounting field by providing a few examples of the effect of this technology on the managerial accounting, financial accounting, and auditing functions. It is clear how Big Data is revolutionizing the accounting field along with many other business fields, however, accountants are observed not to be acting as necessary with this revolution.

Updated: May 03, 2023
Cite this page

Accounting in Big Data Era: Tech Advancements & Changes. (2019, Aug 20). Retrieved from https://studymoose.com/the-accounting-profession-in-the-big-data-eraintroductionwith-the-technological-advancements-in-essay

Accounting in Big Data Era: Tech Advancements & Changes essay
Live chat  with support 24/7

👋 Hi! I’m your smart assistant Amy!

Don’t know where to start? Type your requirements and I’ll connect you to an academic expert within 3 minutes.

get help with your assignment