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Bisht, D.;  Singh, R.;  Gehlot, A.;  Akram, S.V.;  Singh, A.;  Montero, E.C.;  Priyadarshi, N.;  Twala, B. Industry 4.0 Enabling Technologies in the Firm’s Finance. Encyclopedia. Available online: https://encyclopedia.pub/entry/39164 (accessed on 17 November 2024).
Bisht D,  Singh R,  Gehlot A,  Akram SV,  Singh A,  Montero EC, et al. Industry 4.0 Enabling Technologies in the Firm’s Finance. Encyclopedia. Available at: https://encyclopedia.pub/entry/39164. Accessed November 17, 2024.
Bisht, Deepa, Rajesh Singh, Anita Gehlot, Shaik Vaseem Akram, Aman Singh, Elisabeth Caro Montero, Neeraj Priyadarshi, Bhekisipho Twala. "Industry 4.0 Enabling Technologies in the Firm’s Finance" Encyclopedia, https://encyclopedia.pub/entry/39164 (accessed November 17, 2024).
Bisht, D.,  Singh, R.,  Gehlot, A.,  Akram, S.V.,  Singh, A.,  Montero, E.C.,  Priyadarshi, N., & Twala, B. (2022, December 23). Industry 4.0 Enabling Technologies in the Firm’s Finance. In Encyclopedia. https://encyclopedia.pub/entry/39164
Bisht, Deepa, et al. "Industry 4.0 Enabling Technologies in the Firm’s Finance." Encyclopedia. Web. 23 December, 2022.
Industry 4.0 Enabling Technologies in the Firm’s Finance
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This entry is adapted from the peer-reviewed paper 10.3390/electronics11193252

Financial management is a critical aspect of firms, and entails the strategic planning, direction, and control of financial endeavors. Risk assessment, fraud detection, wealth management, online transactions, customized bond scheme, customer retention, virtual assistant and so on, are a few of the critical areas where Industry 4.0 technologies intervention are highly required for managing firms' finance. It has been identified that they are limited studies that have addressed the significance and application of integrating of Industry 4.0 technologies such as Internet of Things (IoT), cloud computing, big data, robotic process automation (RPA), artificial intelligence (AI), Blockchain, Digital twin, and Metaverse.

financial analytics digital auditing firms finance Industry 4.0

1. Introduction

According to the World Bank and International Monetary Fund, increased development financing is necessary to meet all 17 Sustainable Development Goals (SDGs) [1]. Schumpeter conducted early research on the connection between financial prosperity and technological progress in 1912 [2]. No poverty (goal 1); decent work and economic growth (goal 8), responsible consumption and production (goal 12), and climate on action (Goal 13) are the key goals in the area of financial management. These goals empower adopting the digital technologies in the financial management for achieving digital finance, and sustainable finance. Currently Industry 4.0 digital technologies have already gained attention in achieving digitalization and sustainability in various fields [3]. Essentially, the financial management in a firm boosts the efficiency of money, growth and quality. The goal of finance, which is a derivative of the economy, is to support actual output. Initially, finance focused mostly on the financing of trade and used conventional banking structures. Estimation of capital requirement; procurement and allocation of funds, maintaining financial control and procurement and allocation of funds are a few of the basic benefits of financial management [4]. Money is now active in the public imagination as a new kind of digital valuation with the emergence of physical finance and the third wave of the scientific and technological revolution. Over the past ten years, research in digital finance has moved quickly [5]. Risk assessment, fraud detection, wealth management, online transactions, customized bond scheme, customer retention, virtual assistant and so on, are already a few of the critical areas where Industry 4.0 digital technologies intervention are highly required for financial management [6]. Additionally, the application of blockchain in the agri-food supply chain can guarantee complete food traceability, uphold market prices, protect workers’ rights, limit the impact of supply chain middlemen, and provide incentive systems to encourage the expansion of sustainable initiatives [7]. IoT, cloud computing, robotic process automation (RPA), AI, and Blockchain are some of the digital technologies of Industry 4.0. Currently blockchain has made it possible to use cyber-currencies. It is a bottom-up system in terms of structure, which theoretically allows for official oversight to be avoided. Cybercurrencies and tokens have made international transactions even simpler while forcing the globe to transition from a unipolar to a multi-polar economy in which various reserve currencies compete for commerce and value storage. In the context of the Industry 4.0 paradigm, artificial intelligence (AI) is being viewed as one of the key technologies to achieve advanced self-capabilities like self-optimization, self-awareness, and self-monitoring and to disruptively redefine the structure of manufacturing processes and business models [8]. Banks and financial institutions must reposition themselves as service organisations that prioritize investing in digital transformation above traditional services in order to retain stability in the face of intense competition and, subsequently, shifting market conditions [9].

2. IoT

There are many potential uses for the “Internet of Things”, which refers to the internet-based communication of everyday objects, in the world of finance, particularly in the banking industry [10]. Customers’ changing usage patterns and behaviors, as well as the abundance of data already available, mean that the Bank’s stakeholders must undergo inevitable digital reforms [11]. Therefore, new developments in the digital world are what motivate the digital transformation of any institution, including those in the financial sector. IoT is one of the key pillars on which a bank may build its digital transformation. IoT that directly affect financial services, such as mobile banking, M-banking, crowd-based finance, virtual currency, high frequency trading firms, cybercrime, big data, and IT analytics, are therefore needed to help banks integrate IoT into their goods and services [12]. For business intelligence in corporate finance, the IoT-based Efficient Data Visualization Framework (IoT-EDVF) has been developed to strengthen the risk of leaks, analyze multiple data sources, and monitor data quality [13].

3. Artificial Intelligence

The industrial revolution 4.0 has brought many changes in the field of technology, including financial technology. People need to absorb the right information, in order to make good financial decisions. With various technologies that provide digital financial information, people must have the knowledge and expertise in evaluating options to maximize their long-term financial well-being [14]. Financial intelligence has slowly developed the capacity to become a “financial brain” in the contemporary dynamic capital market. Financial intelligence exhibits a quick and accurate machine learning power to handle complex data. Four open issues, namely explainable financial agents and causality, perception and prediction under uncertainty, risk-sensitive and robust decision-making, and multi-agent game and mechanism design, have been introduced with the development of financial intelligence and review state-of-the-art techniques in wealth management, risk management, financial security, financial consulting, and block chain [15]. AI implementation in commercial banking could alter operational procedures and customer interactions, opening up new behavioral finance research possibilities. Commercial banks can improve client targeting, increase security when processing payments, and decrease loan losses by employing AI [16].

4. Cloud Computing

The concept of cloud computing emerges at a pivotal period in history as a result of the Internet’s rapid development and inability of traditional Internet financial risk prediction methods to suit individual and corporate needs. Due to its distributed, dynamic, and autonomous properties, cloud computing has overturned the conventional method for predicting financial risk [17].
With the aid of cloud technology, banks may adopt a digital paradigm to provide new channels, shorten the time it takes to sell new products, meet customer expectations, and do all of this while spending less money [18]. The cloud computing has revolutionized business by increasing efficiency, scaling up capacity, ensuring transference and controlling cost.
The enterprise financial control has undergone significant changes as a result of the emergence of big data and cloud computing [19]. Future financial institutions are changing as a result of cloud computing. These days, businesses employ a wide range of cloud-based software, including those for customer relationship management (CRM), enterprise resource planning (ERP), accounting, and even commerce [20].

5. Blockchain

High degrees of data protection, decentralization, an open and transparent network infrastructure, and low operational expenses are all provided by blockchain technology. These great qualities make blockchain an incredibly useful and popular option, even in the traditionally conservative world of finance, as well as in the limited banking industry Blockchain is one of the most important areas in banking and finance sectors [21].
Blockchain enables secure, simple transactions and fosters confidence among business partners. Even the swift identification of people using digital IDs is possible.Blockchain technology enables transparent data storage and decentralized decision-making by dispersing the security risk throughout the network. The decentralized duplicated ledger technology known as blockchain, which underlies Bitcoin and other cryptocurrencies, offers a potentially appealing alternative method of structuring contemporary finance. At the moment, the financial system relies on a number of centralized trusted intermediaries [22]. Blockchain technology offers a great chance to democratize business. Initial coin offerings, or ICOs, are cutting-edge financing methods for entrepreneurs that make use of blockchain technology [23].
Regarding persistent trust concerns between trading partners in trade finance, blockchain technology has been proposed as a potential solution to enhance the trust relationship by boosting the predictability of trading partners, expanding the efficiency and quality of communication, allowing the expression of generosity, and improving the security of transactions and data transfers [24]. Asset-backed securitization (ABS) and blockchain are two examples of cutting-edge financial products and technologies that are used in supply chain finance (SCF), a combination of financing procedures and technology-based businesses that connect supply chain participants [25]. By utilizing important resources and carrying out appropriate procedures, the blockchain-driven SCF solution offers services to its clients, creating value for participants by satisfying their needs [26]. Additionally, the value of blockchain-enabled SCF enterprises is influenced by their participation in blockchain consortiums and the advancement of blockchain implementation. The market’s uncertainty is decreased by investors’ confidence in blockchain [27].

6. Big Data

Big data is a term for vast amounts of data of different types that must be collected, managed, and analyzed using certain tools. Big data platforms and analytics for the banking aid businesses in gaining insightful knowledge about how customers utilize their goods and services.New technologies like cloud computing and artificial intelligence are evolving daily with the onset of the big data era. A new era of wealth and financial market development is being tremendously aided by the increasing application of science and technology to the financial sector [28]. It’s getting harder to interpret data as businesses get it from a growing number of sources, including websites, applications, social networks, IoT devices, and sensors. Big data is used in this situation since current technology cannot keep up with the information. People may have diverse conceptions of the term big data, which is very ambiguous. In the finance sector, big data can go in one of three paths Predictive analysis, Real-time analytics, or customer analytics. Predictive analysis based on social media is one example of how alternative data are used to forecast stock prices, identify various risk exposure and find new price movement indicators [29].
The application of big data tools as real-time analytics assist financial decision-making to solve real business problems and enhancing enterprise value [30]. Applications of big data on customer analytics in the field of Internet finance are used in order to provide various users with financing services such as platform finance, supply chain finance, and consumer finance. Internet finance platforms may rely on a significant amount of user data that have been acquired over time [31]. The complexity of data analytics in the financial services sector can only be handled by big data technologies. Big data is in high demand in the financial industry, and it is driven by a number of factors like absence of a personal relationship with customers, the rising presence of FinTech on social media, changing consumer expectations, amounts of data that keep on increasing, and increasing competition in the FinTech sector.
When a company needs to store a lot of data, big data platforms like Apache Hadoop, Spark, etc. can help cut costs. These technologies aid businesses in finding more efficient ways to conduct operations. Using real-time in-memory analytics, businesses can gather information from a variety of sources. Employing big data techniques, businesses can carry out sentiment analyses. These give them access to comments on their business, including who is saying what about it. It makes it possible for businesses to meet client expectations. The company’s product line can be changed with the aid of big data analytics. It guarantees effective marketing campaigns.

7. Metaverse and Digital Twin

One of the recent blockchain-based digital assets to be created is Metaverse. The term “metaverse” refers to an alternative virtual environment where people can create programs, interact with one another, and buy, sell, and share products and services using avatars (virtual representations) of themselves. Metacurrencies, or regional cryptocoins, are also utilized in the metaverse [32]. With either the widespread theft of cryptocurrencies from exchanges or the sale of fraudulent or questionable NFT and other financial goods that have lost a lot of value quickly, financial cybercrimes in the metaverse have dramatically expanded over the past several years [33]. The Metaverse is a concept for a fictitious “parallel virtual world” that embodies lifestyles for living and working in virtual cities as an alternative to future smart cities. Indeed, the Metaverse has the potential to redefine city designing activities and service provisioning in order to increase urban efficiencies, accountabilities, and quality performance. This is because emerging innovative technologies—such as Artificial Intelligence, Big Data, the IoT, and Digital Twins—provide rich datasets and advanced computational understandings of human behavior. There are still ethical, human, social, and cultural questions about how the Metaverse may affect how well people connect with one another and how it will potentially affect how well cities function in the future [34].
A digital twin (DT) is a virtual representation of an actual thing—a system, a person, a community, or even an entire city—that is constantly updated with information from the real thing and its surroundings. It serves as a link between virtual cyberspace and actual physical entities, and as such, is regarded as the foundation of Industry 4.0 and the engine of future innovation [35]. The financial sector can reinvent itself using digital twin technology for an uncertain future in a globalized world. Digital twins, which are exact clones of the real thing, can aid with decision-making based on the actual interactions of complex systems. Rather than just making educated assumptions, they can offer fact-based insights. In order to discover the inventory and cash replenishment procedures that minimize the impact of disruptions on supply chain performance, the digital twin framework integrates machine learning (ML) and simulation [36]. The need to concentrate on enhancing customer satisfaction via online channels is becoming more and more important every year as a result of the significant consumer shift toward accessing financial services via mobile or desktop devices. Financial institutions are working with third party organizations to collect data about how customers interact with their service online in order to develop a customer relationship management and fulfilment solution that would replace the requirement to hire support personnel. This will give important information on how digital twins can be used to fully exploit this third-party data and create simulations utilizing the virtual platform to produce virtual assistants that can aid customers with their difficulties.

8. Robotic Process Automation

A relatively recent development that primarily emerged in response to the 2008 financial crisis is digitalization in the banking industry [37]. Since that time, banks have been looking for substitutes to help them adjust to innovative changes in order to create new sources of wealth. Banking organizations can continuously rethink their tactics by utilizing RPA [38]. Robotic Process Automation (RPA) is a virtual workforce that is managed by a company’s operations team [39]. Companies utilize this technology to replace a number of standardized and rule-based procedures and duties [40]. It enables the business to delegate some jobs while concentrating more on those involving people. The phrase technology that deals with the application of machines and computers to the production of goods and services is related to the concept of automation in RPA [41]. RPA is created to deal with complex calculations and to take over a part of the decision making. RPA is also able to deal with dynamic and fast changing circumstances. The use of RPA within a company will have an impact on both the employees and on the company itself [42].
RPA technology and the usage of robots in business operations are spreading throughout the world’s enterprises. Robotic process automation can immediately improve key business operations like payroll, employee status changes, new hire recruitment and onboarding, accounts receivable and payable, invoice processing, inventory management, report creation, software installations, data migration, and vendor on boarding [43]. RPA is a software robot technology created to carry out business operations that are governed by rules by imitating human interactions in a variety of applications. The next generation of RPA bots are known as cognitive robotic process automation (CRPA)or intelligent process automation (IPA), which combines RPA and AI. By making the main financial activities significantly more effective and enabling banks to customize services for consumers while simultaneously enhancing safety and security, it has been revolutionizing the banking sector. Intelligent automation has created hurdles for protecting consumer interests and the stability of the financial system, even though technology is allowing banks to rethink how they operate [44].

References

  1. Ziolo, M.; Bak, I.; Cheba, K. The role of sustainable finance in achieving sustainable development goals: Does it work? Technol. Econ. Dev. Econ. 2021, 27, 45–70.
  2. Schumpter, J.A. Captitalism, Socialllism and Democracy; Harper: New York, NY, USA; Harper & Brothers: New York, NY, USA, 1942.
  3. Ghobakhloo, M. Industry 4.0, digitization, and opportunities for sustainability. J. Clean. Prod. 2020, 252, 119869.
  4. Brigham, E.F.; Houston, J.F. Fundamentals of Financial Management; Cengage Learning: Boston, MA, USA, 2021.
  5. Guo, F.; Kong, S.T.; Wang, J. General patterns and regional disparity of internet finance development in China: Evidence from the Peking University Internet Finance Development Index. China Econ. J. 2016, 9, 253–271.
  6. Zaytsev, A.A.; Blizkyi, R.S.; Rakhmeeva, I.I.; Dmitriev, N.D. Building a Model for Financial Management of Digital Technologies in the Areas of Combinatorial Effects. Economies 2021, 9, 52.
  7. Mirabelli, G.; Solina, V. Blockchain-based solutions for agri-food supply chains: A survey. Int. J. Simul. Process Model. 2021, 17, 1–15.
  8. Peres, R.S.; Jia, X.; Lee, J.; Sun, K.; Colombo, A.W.; Barata, J. Industrial Artificial Intelligence in Industry 4.0—Systematic Review, Challenges and Outlook. IEEE Access 2020, 8, 220121–220139.
  9. Machkour, B.; Abriane, A. Industry 4.0 and its Implications for the Financial Sector. Procedia Comput. Sci. 2020, 177, 496–502.
  10. Yilmaz, N.K.; Hazar, H.B. The rise of internet of things (IoT) and its applications in finance and accounting. Pressacademia 2019, 10, 32–35.
  11. Khanboubi, F.; Boulmakoul, A. A roadmap to lead risk management in the digital era. In Proceedings of the ASD 2018: Big data & Applications 12th edition of the Conference on Advances of Decisional Systems, Marrakech, Morocco, 2–3 May 2018.
  12. Khanboubi, F.; Boulmakoul, A.; Tabaa, M. Impact of digital trends using IoT on banking processes. Procedia Comput. Sci. 2019, 151, 77–84.
  13. Shao, C.; Yang, Y.; Juneja, S.; Gseetharam, T. IoT data visualization for business intelligence in corporate finance. Inf. Process. Manag. 2022, 59, 102736.
  14. Andreou, P.C.; Anyfantaki, S. Financial literacy and its influence on internet banking behavior. Eur. Manag. J. 2020, 39, 658–674.
  15. Zheng, X.L.; Zhu, M.Y.; Li, Q.B.; Chen, C.C.; Tan, Y.C. FinBrain: When finance meets AI 2.0. Front. Inf. Technol. Electron. Eng. 2019, 20, 914–924.
  16. Königstorfer, F.; Thalmann, S. Applications of Artificial Intelligence in commercial banks—A research agenda for behavioral finance. J. Behav. Exp. Financ. 2020, 27, 100352.
  17. Li, S.; Liu, X.; Li, C. Research on Risk Prediction Model of Internet Finance Based on Cloud Computing. J. Math. 2022, 2022, 2803934.
  18. Tiwari, S.; Bharadwaj, S.; Joshi, S. A Study of Impact of Cloud Computing and Artificial Intelligence on Banking Services, Profitability and Operational Benefits. Turk. J. Comput. Math. Educ. TUR-COMAT 2021, 12, 1617–1627.
  19. Zhang, F. Digital Transformation of Enterprise Finance under Big Data and Cloud Computing. Wirel. Commun. Mob. Comput. 2022, 2022, 1068467.
  20. Dandapani, K. Electronic finance–recent developments. Manag. Financ. 2017.
  21. Gan, Q.; Lau, R.Y.K.; Hong, J. A critical review of blockchain applications to banking and finance: A qualitative thematic analysis approach. Technol. Anal. Strat. Manag. 2021, 1–17.
  22. Varma, J.R. Blockchain in Finance. Vikalpa J. Decis. Mak. 2019, 44, 1–11.
  23. Fisch, C.; Meoli, M.; Vismara, S. Does blockchain technology democratize entrepreneurial finance? An empirical comparison of ICOs, venture capital, and REITs. Econ. Innov. New Technol. 2022, 31, 70–89.
  24. Kowalski, M.; Lee, Z.W.; Chan, T.K. Blockchain technology and trust relationships in trade finance. Technol. Forecast. Soc. Chang. 2021, 166, 120641.
  25. Dong, C.; Chen, C.; Shi, X.; Ng, C.T. Operations strategy for supply chain finance with asset-backed securitization: Centralization and blockchain adoption. Int. J. Prod. Econ. 2021, 241, 108261.
  26. Wang, L.; Luo, X.; Lee, F.; Benitez, J. Value creation in blockchain-driven supply chain finance. Inf. Manag. 2021, 59, 103510.
  27. Paul, S.; Adhikari, A.; Bose, I. White knight in dark days? Supply chain finance firms, blockchain, and the COVID-19 pandemic. Inf. Manag. 2022, 59, 103661.
  28. Wang, X.; Wu, Z.; Shen, S. Financial Technology Risk Management and Control in the Big Data Era. In International Conference on Cognitive Based Information Processing and Applications (CIPA 2021); Springer: Singapore, 2022.
  29. Hansen, K.B.; Borch, C. Alternative data and sentiment analysis: Prospecting non-standard data in machine learning-driven finance. Big Data Soc. 2022, 9, 20539517211070701.
  30. Ren, S. Optimization of Enterprise Financial Management and Decision-Making Systems Based on Big Data. J. Math. 2022, 2022, 1708506.
  31. Guan, Q.; Gao, W. Prominence of Value Accumulation: Big Data Finance. In Internet Finance; Palgrave Macmillan: Singapore, 2022; pp. 143–201.
  32. Akkus, H.T.; Gursoy, S.; Dogan, M.; Demir, A.B. Metaverse and metaverse cryptocurrencies (meta coins): Bubbles or future? J. Econ. Financ. Account. 2022, 9, 22–29.
  33. Katterbauer, K.; Syed, H.; Cleenewerck, L. Financial cybercrime in the Islamic Finance Metaverse. J. Metaverse 2022, 2. Available online: https://www.europub.co.uk/articles/-A-707176 (accessed on 5 August 2022).
  34. Allam, Z.; Sharifi, A.; Bibri, S.E.; Jones, D.S.; Krogstie, J. The Metaverse as a Virtual Form of Smart Cities: Opportunities and Challenges for Environmental, Economic, and Social Sustainability in Urban Futures. Smart Cities 2022, 5, 771–801.
  35. Aheleroff, S.; Xu, X.; Zhong, R.Y.; Lu, Y. Digital twin as a service (DTaaS) in industry 4.0: An architecture reference model. Adv. Eng. Inform. 2021, 47, 101225.
  36. Badakhshan, E.; Ball, P. Applying digital twins for inventory and cash management in supply chains under physical and financial disruptions. Int. J. Prod. Res. 2022, 1–23.
  37. Voinea, G.; Anton, S. Lessons from the Current Financial Crisis: A Risk Management Approach. Rev. Econ. Bus. Stud. II. 2009, 3, 139–147.
  38. Capgemini Consulting. Robotic Process Automation (RPA): The Next Revolution of Corporate Functions. Available online: https://www.capgemini.com/consulting-fr/wp-content/uploads/sites/31/2017/08/robotic_process_automation_the_next_revolution_of_corporate_functions_0.pdf (accessed on 5 August 2022).
  39. Valgaeren, H. Robotic Process Automation in Financial and Accounting Processes in the Banking Sector. 2019. Available online: https://www.scriptieprijs.be/sites/default/files/thesis/2019-09/MBA_Valgaeren_H_Final_Report1819.pdf (accessed on 5 August 2022).
  40. Lacity, M.C.; Willcocks, L.P. A new approach to automating services. MIT Sloan Manag. Rev. 2016, 58, 41–49.
  41. Tripathi, A.M. Learning Robotic Process Automation: Create Software Robots and Automate Business Processes with the Leading RPA Tool–UiPath; Packt Publishing Ltd.: Birmingham, UK, 2018.
  42. Fernandez, D.; Aman, A. Impacts of Robotic Process Automation on Global Accounting Services. Asian J. Account. Gov. 2018, 9, 127–140.
  43. Madakam, S.; Holmukhe, R.M.; Jaiswal, D.K. The future digital work force: Robotic process automation (RPA). JISTEM-J. Inf. Syst. Technol. Manag. 2019, 16, 1–17.
  44. Moffitt, K.C.; Rozario, A.M.; Vasarhelyi, M.A. Robotic Process Automation for Auditing. J. Emerg. Technol. Account. 2018, 15, 1–10.
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Subjects: Computer Science, Artificial Intelligence
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Deepa Bisht
,
Rajesh Singh
,
Anita Gehlot
,
Shaik Vaseem Akram
,
Aman Singh
,
Elisabeth Caro Montero
,
Neeraj Priyadarshi
,
Bhekisipho Twala
View Times: 754
Revisions: 3 times (View History)
Update Date: 30 Dec 2022
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