The Impact of Fintech on Management Accounting

The Impact of Fintech on Management Accounting
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The Impact of Fintech on Management Accounting
Background Information/Introduction
Management accounting involves establishing, evaluating, measuring, and interpreting accounting information to help corporate leaders make informed decisions and, thus, run the firm’s operations efficiently. In management accounting, big data can be theorized as the magnitude of data that is kept or processed at the same thresholds or beyond the necessary information systems limits. Big data comprises vast datasets encompassing distinct forms of data, which could be evaluated to establish patterns, assumptions, and trends. Big data and big data analytics significantly influence the role of accountants within the managerial accounting domains. Due to technological advancements and the burgeoning data availability forms make big data increasingly central in influencing auditing and related management accounting practices (Herath and Woods, 2021, p.196). Accordingly, blockchain is a technological tool disrupting how management accounting operates and its role within an organization. Blockchain can be described as distributed ledger technological tool that allows only authorized participants within a shared network to share transaction data among different stakeholders. In addition, blockchain ensures that data records are continuously verified by all the authorized stakeholders within the shared networks. In this way, blockchain allows for more secure and transparent data records compared to a centralized transaction information system (Saputro et al., 2021, p.1). This paper critically evaluates the emergence of fintech and how it impacts management accounting. More specifically, it discusses the impact of big data and blockchain on management accounting decision-making to contribute to the limited knowledge on the subject matter.
The Emergence of Fintech and Overview of its Impact on Management Accounting Decision Making.
Digital financial services are increasingly being used by organizations and consumers, providing a favorable climate for digital entrepreneurship, Blockchain, Big Data, mobile payments, etc. Extant research is inclined to understand and explain this phenomenon by focusing on FinTech (Sghari and Mezghani, 2020, p.1). Some researchers view “FinTech” as innovations within the financial services sector that disrupt the current market landscape. In contrast, others regard them as startups driven by financial innovations increasingly sending ripple effects across the financial industry ecosystem (Sghari and Mezghani, 2020, p.1). Fintech provides a significant opportunity for management accounting practice to become increasingly relevant in contemporary organizations. It has changed the analyzed and presented metrics to influence corporate managers to make decisions. Fintech and its related digitization tools impact a company’s statement of financial position, traditional financial indicators, and return on investments, and how the metrics are applied to understand the customers (Tho, 2019, n.p.). In this way, fintech broadens the scope of management accounting practice and plays a central role in product-level decision-making processes.
The adoption of fintech in the organization was characterized by the use of advanced information systems and new enterprise resource planning, immensely impacting management accounting practices. Change in information systems implied that management accounting logic needed to be evaluated and potentially become a subject of digital transformation as well. Fintech prompts organizations to re-examine the possibilities of financial digitalization. For example, multinational corporations such as BP and Microsoft collaborated with their service providers to standardize their management accounting globally. They shifted their database to the cloud and designed business analytics that allowed for shifting accounting practices to embrace a strategic role within the organization. Consequently, the adoption of fintech lowered the operating costs to a great extent, as well as offered an added value by ensuring financial analytics are increasingly accessible in making decisions (Toni, 2018, p.21).
Impact of Big Data on Management Accounting Decision Making.
One of the significant impacts of big data on managerial accounting is anchored on enhancing organizational ability to access real-time data and subsequently using such data to make reports. Within traditional managerial accounting practices, most of the data applied to evaluate the market value of distinct financial report accounts were either outdated or inaccurate. Intangibles, last-in-first-out (LIFO), first-in-first-out (FIFO), historical costs measurements, and annual depreciation estimation are evaluated using different assumptions and formulas, which are, to a great extent, inaccurate. On the other hand, big data technology enables organizations to obtain real-time data as well as to calculate and estimate value with a high degree of accuracy. In this vein, different data types complement conventional financial information to provide additional knowledge for improved transparency and assurance (Yadav, 2020, p.7). The Enterprise Resource Planning (ERP) system contains essential information concerning a company’s assets that could be utilized to complement other data, including phone calls, video recordings, email messages, etc., to comprehensively understand the respective asset’s features and attributes and condition. Once annual depreciation is estimated using distinct variables and assumptions, it can be obtained using current value comparisons across a specified timescale (Yadav, 2020, p.7). For example, Citibank uses big data to scan transactional records and identify anomalies, which helps sport or forecast defects and unusual or incorrect charges in the customer domains. It is far more accessible for management accountants to spot the costs emanating from these anomalies using predictive modeling tools. In addition, Citi has managed to drive down platforming costs due to the shift towards using big data horizontal architecture (Marr, 2016, n.p). Therefore, big data helps management accountants with real-time data to inform managerial reports in contemporary organizations.
Further, the traditional accounting models measured inventory value using different valuation methods, including physically counting the items. However, the technology-improved accounting data (i.e., big data) ensures the management accountants obtain the inventory’s current value in real-time. Organizations are now using big data technology to collect data from diverse sources instantly, that is, at the point-of-sale (POS), thus facilitating better data analysis applications such as inventory control and identifying associated products. A practical case scenario of the application above involves vendor managed inventory system powered by big data. Today, big companies are applying diverse non-financial and financial data to prepare increasingly sophisticated reports to inform managerial decision-making for project management and process improvements (Yadav, 2020, p.7). In addition, they are utilizing different databases to substitute historical figures in statements of financial position with fair market values leading to more accurate and sophisticated decisions.
Accordingly, management accounting practice has gained substantial prominence in the recent past because of the rise in multinational corporations (MNCs) with enormous operating costs amounting to billions of dollars and a massive magnitude of data within their enterprise systems. That said, companies are investing considerable resources in designing systems such as Balanced Scoreboard (BSC) and management control systems (MCSs) to regulate employee and management behaviors as well as establish non-financial and financial measures for behaviors to fit with corporate objectives feasibly. Big companies are applying MCSs, and are utilizing big data to evaluate employee behavioral tendencies for internal control. Also, there are many avenues to monitor staff activities to evaluate their performance or productivity. For example, companies extract information from employees’ computers, including click streams, web use, and time spent on productivity tools such as MS Excel. Furthermore, big data also enables management accountants to identify diverse patterns, trends, as well as demand forecasts to improve the budgeting processes within the company (Yadav, 2020, p.8).
Auditing is one of the areas of management accounting significantly impacted by the use of big data in contemporary organizations. Auditing is a disciplined and systematic approach tailored to investigate a firm’s financial records to ensure their accuracy per the standards. It examines and enhances the effectiveness of procedures and related controls to protect investors’ financial interests in the company. Within the traditional management accounting domains, auditing entailed physically verifying receipts or periodically counting the inventory, including annually, quarterly, and monthly. These processes are inaccurate and time-consuming. In this regard, the organizations could only audit the financial areas of the business, thus undermining the quality of the decision-making process. However, the management accounting paradigm regarding auditing has changed due to the use of big data. It is irrelevant and insufficient to continue depending on limited magnitudes of paper-stored data to inform decisions. It is now possible to automatically create and store data of enormous magnitudes as well as expand variable sets utilizing various tools such as radio-frequency identification (RFID) chips, scanners, mobile apps, etc. Data’s rising complexity and magnitudes pose significant auditing problems (Yadav, 2020, p.9). The auditor’s assurance and audits provided using conventional methodologies place auditing at significant risk of becoming obsolete, mainly due to auditors’ inability to validate extensive data contents.
Auditors within the big data organizational context are exposed to vast data magnitudes to authenticate the data’s reliability and relevance. Huge public accounting companies and firms are applying advanced data analytic technologies to leverage their available data. With expanded access to the right tools and enterprise data, auditors can investigate the whole data population. Big data-driven analytical tools not only evaluate the whole available data population but also include additional unstructured data to identify associations between each data evaluated and make insightful inferences from them. For example, managerial accountants can now use data analytic tools to evaluate the whole financial data sets at diverse dimensions such as time, purpose, transaction ...