*2.1. Industry 4.0*

Our current business environment is radically changing, and the increasingly demanding and rapidly changing customer needs are the underlying reason that has driven industry revolutions at different periods (Mohamed 2018). These revolutions have brought to the world drastic changes in diverse areas, posed huge challenges for industries and manufacturers, led to massive innovations and transformations, and remarkably affected people's way of life (Huang 2017). Industry 4.0 is also known as the Digital Revolution or the Fourth Industrial Revolution. The First Industry Revolution encompasses the use of the steam engine in manufacturing facilities, followed by the introduction of electrically powered mass production (Second Industry Revolution) (Pagliosa et al. 2019). The Third Industry Revolution corresponds to the use of electronics and information technology (IT) to automate manufacturing (Kagermann et al. 2013). I4.0, deemed as the Industry 4.0, focuses on the digitalization of all physical assets and the massive integration of value chain participants (PwC 2017) (see Figures 2 and 3).

**Figure 2.** Through the industry revolutions. Source: Own contribution of the authors.

**Figure 3.** The Concept of the Fourth Industry Revolution. Source: Own contribution of the authors.

There are various definitions for Industry 4.0 considering that many researchers and practitioners define this term according to their level of understanding and unique perspective. There are also inter-relating terms such as IoT, Cyber-Physical Systems (CPS), Smart Systems, Digitalization, and Digital Factory (Khan and Turowski 2016).

Certain researchers define Industry 4.0 as the concept of automation and data exchange in the manufacturing technologies, which enables the use of Internet of Things (IoT), Cyber–Physical Systems (CPS), big data analytics, cloud computing, and cognitive computing, with the main goal of achieving a higher level of progress (Herˇcko et al. 2015). Other researchers suggested that the crown jewel of Industry 4.0 is the networking of smart digital devices with products, tools, robots, and people based on intelligent factories (Mekinji´c 2019).

Moreover, I4.0 is the latest trend when it comes to automation and data exchange in production systems (SCOOP 2017; CNI, National Confederation of Industry 2016). The adoption of technologies, such as CPS, big data, and IoT provides relevant information and creates new possibilities for process improvement (Bohács et al. 2013; Schuh et al. 2017). In addition, one of I4.0's main

advantages is the ability to adapt quickly to volatile demand scenarios and products with short life cycles (Sanders et al. 2016). According to Tamás and Illés (2016), I4.0 has generated important changes in production systems and created demand for new jobs. Recent research on this subject indicates a lack of studies about the impact of I4.0 on manufacturing environments (Zuehlke 2010;Landscheidt and Kans 2016; Gjeldum et al. 2016; Xu and Chen 2016; Martinez et al. 2016; Sanders et al. 2016; Kolberg et al. 2017; Santorella 2017).

Agrawal et al. (2017) argues that Industry 4.0 can be identified as an emerging platform of technologies that revolutionize the rate of productivity per employee while reducing the cost of controlling and compliance incurred by corporations. According to Berger (2017), Industry 4.0 provides flexibility to the production processes; thus, it helps to create products that are tailored to the target segment while satisfying personalized needs through a low marginal cost. Vaidya et al. (2018) discusses the challenges incorporated with the applications of Industry 4.0, namely, intelligent decision making and negotiation mechanism, high-speed networking protocols, manufacturing specific big data and analytics, system modeling and analysis, cyber security, modularized and flexible physical artifacts, investment, etc. Lu (2017) mentions that Industry 4.0 creates a value-added integration horizontally and vertically in the manufacturing processes. Thus, horizontal integration was done through value creation modules from the material flow to the logistics of product life cycle, whereas the vertical integration through product, equipment, and human needs with different aggregation levels of the value creation and manufacturing systems.

#### *2.2. Banking 4.0*

Today, the rate of technological change in the banking sector and the entire economic ecosystem is extremely high. These changes have a significant impact on the dynamism of individuals and the socio-political community that no one could have imagined. Increasing data usage, machine learning based on artificial intelligence, the Internet of Things, and digital technologies play an important role in this process.

Banking 1.0 is what we call banking, and this is the same traditional banking that services are provided at certain times in the branch. The contemporary banking theory argues that commercial banks, composed with other financial mediators, are essential in the distribution of wealth in the economy (Bhattacharya and Thakor 1993). Then came the introduction of technologies such as the Internet and some Banking 2.0 services that were slowly pushing banking out of the branches. This is possible with the advent of ATMs and card readers, since we are witnessing the formation of off-branch services at different times. This period began in 1980 and lasted until 2007. With the advent of self-service banking, things have changed, and we have come to realize that banking can also be portable, which is Banking 3.0 (It is related to the supply and expansion of mobile services. These services may be provided on a smartphone platform or even portable card readers. This period lasted from 2007 to 2015), but banking 4.0 is a major transformation that will live with you (Figure 4). Topics such as intelligence, sharing, and evolutionary computing are discussed.

Harjanti et al. (2019) argued that digital transactions necessitate an improved banking experience, so the banking industry also conducts experiments by applying innovative technology in order to support mobility and increase transaction speeds and efficiency for its customers. Some previous studies suggested that the highest dilemma for the current banking system is to explain the high costs of branch banking but also to obtain an increase in profitability as branch-driven revenue growth (Capgemini 2012). According to Athanasoglou et al. (2006), the size of banks contributes to recognizing possible economies or diseconomies of scale in the banking area considering cost differences, products, and risk diversification.

**Figure 4.** The banking revolution. Source: Own contribution of the authors.

The banking system represents a fundamental pillar of the economic growth and macroeconomic stability, especially in the context of globalization. However, the evolution of the banking sector in each country is affected by continuous changing dynamics of the international banking architecture and financial environment (Spulbar and Birau 2019b). Nowadays, a company or startup can provide banking services by providing financial technology (FinTech)-based applications. The use of artificial intelligence and intelligent, cognitive, and voluntary algorithms has entered banking in this period). The banking sector has been immensely benefited from the implementation of superior technology during the recent past almost in every nation in the world. Productivity enhancement, innovative products, speedy transactions, the seamless transfer of funds, real-time information system, and efficient risk management are some of the advantages derived through the technology (Saravanan and Muthu Lakshmi 2016). The new era of financial deregulation is supported by the revolution in information and communication technology, which helps banks ensuring innovation in their products and services at competitive prices (Turk Ariss 2008).

Maturity models offer a complex guidance to define, assess, and evaluate the progress of the current state of the banking sector in its journey of Industry 4.0. (Bandara et al. 2019). Other researchers developed a maturity model using the existing model of Software Process Improvement and Capability Determination (SPICE) considering only two main dimensions, i.e., capability dimension and aspect dimension (Gökalp et al. 2017).On the other hand, the technology acceptance model is generally considered as the most influential theory in IT and information systems (Benbasat and Barki 2007).

The paradigm shift from the concentrated market structure under financial repression to the competitive framework under financial liberalization has laid down the foundation for the emergence of private and foreign banks originally in developed countries and afterward in developing countries (Sohrab Uddin and Sohel 2018). Today, a significant portion of bank customers are young people and middle-aged people who have different expectations and preferences than the previous generation. Meeting these expectations and preferences is no longer possible with existing banking models and will only be possible with the use of fourth generation tools, technologies, and mechanisms.Banks can no longer begin their design with business goals and market share, but they need to know how to get their attention and preferences without directly interacting with the customer, thereby achieving business goals.Based on the definition of Temenos (2018), properly digitizing, or in other words Banking 4.0, means "Experience-Driven Banking" capability that requires coverage of both "Customer Experience" and "Execution Experience"(see Figure 5).

*Int. J. Financial Stud.* **2020**, *8*, 32

**Figure 5.** The relationship between Banking 4.0 and infrastructure. Source: Own contribution of the authors.

Industry 4.0 needs its own banking structure. Industries 4.0 are largely international in scope, and customers from all over the world choose them. A radical change in the marketing and segmentation of banking customers makes it unique for each customer. There seems to be only one type of banking, and that is proprietary banking in a new way. With the development and maturation of technologies such as the Internet of Everything (IoE) (by creating a connected network of people, processes, data, objects, etc.), Internet of Value, blockchain technology, cloud technology, advanced robotics, virtual reality, 3D printing, miniaturization of sensors, and the exponential development of emerging technologies and innovations are coming across completely different generations of banking.

Certain researchers provide a Maturity Model to assess the level of readiness in adapting to Industry 4.0 of the banking sector, which includes the following maturity levels, i.e., Initial, Managed, Defined, Established, and Digital Oriented (Bandara et al. 2019).
