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The retail banking industry must rise to the challenge of disruptive technology such as intelligent automation and competition from Fintech startups. Robotic Process Automation (RPA) is increasingly a strategic priority for banks to maintain competitive advantage and increase profitability. The major benefit of adopting RPA services in retail banking is to automate routine and repetitive processes, so that banks can improve efficiency, accuracy, operate 24/7, reduce cost and offer innovative services and better experience to customers. The sharing economy has evolved to create a more empowered consumer. The study focuses on factors influencing customer experience in retail banking services delivered by RPA. Specifically, the study theorizes the role of various factors influencing the adoption of RPA in the retail banking industry. Results highlight that factors such as security, privacy, reliability and usefulness are significant in advancing RPA in the retail banking industry. Implications for research and practice are also discussed.


Customer Experience; Retail Banking Industry; Robotic Process Automation; Technology Adoption; Financial Services


Robotic process automation (RPA) is the application of technologies to configure computer software or a “robot” to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems. RPA combines intelligence including natural language processing, machine learning, autonomics and machine vision with automation. Software named as robot captures and interprets the customer requirements and initiates operations across multiple digital systems. These software bots which perform these activities can also be termed as virtual or digital workforce in today’s work environment.

Artificial Intelligence (AI) and Robotic Process Automation (RPA) Revolution

Robots are likely to be performing 45% of manufacturing tasks by 2025 (vs. 10% today) [1]. Merrill Lynch estimated the robots and AI solution market at US$153b by 2020. Machine learning and customer interface such as voice and facial recognition will bring a huge change in the banking and financial industry. Roboadvisors are a major technological disruptor for traditional wealth management and have the potential for US$255bn in assets under management (AUM) by 2018, implying >100% CAGR, or 2% penetration of the total addressable market [1].

Banks are looking for different ways to stay competitive and maximize profit with a reduction in cost. RPA are starting to change the way Banking, Financial Services and Insurance (BFSI) is doing business. The concept of robotics automation involves the combination of intelligence with automation. RPA can produce vast information, data, analysis and workflows which have proven to provide tangible benefits to banks as well as its customers. Over the past years, various acquisitions and mergers happened which led to an increase in competition in the banking industry. Banks are investing in RPA to keep up with constantly changing and competitive industry. Automated investment programs use algorithms to arrange individual investment portfolios. Digital investment solutions can help strengthen the relationship between credibility and service provided [2].

High volume and repetitive tasks are better performed by robots. It improves service quality, high accuracy, faster turnaround time, multi-tasking and increases compliance.

The banking industry is under pressure to provide 24/7 services, their profit margins are going down and customer satisfaction surrender. RPA is today’s version of tech outsourcing. RPA is quick and cost effective with tangible return on investment (ROI) for banks. The more automation and reliability banking can bring into the customer experience, especially on mobile devices, will define the industry’s success for many years to come [3]. Robots help manufacturing industry by increasing production with improved quality, process, and backend work. Banking sector now has years of data related to customer feedback, products and bank activities which can be further analyzed with the help of Business Intelligence (BI) tools and help in strategic decision-making. RPA can allow banks to monitor customer behavior, workforce efficiency and time taken to complete various banking operations from anywhere. Banks have put AI as a key element of daily operations and believe AI can be key to enhancing customer experience.

The primary objective behind exploring and building the RPA capability is to overcome the barrier of human intelligence scalability. The speed with which humans can perform the given tasks compared to the Robot has surpassed by performing the same task in a fraction of a second. RPA looks to overcome this very challenge with human intelligence by transferring the human intelligence to cognitive machines with supreme computational capabilities. It is the proxy for future banking workforce and customer service. It can better perform repetitive tasks, with higher accuracy, faster turnaround. In the evolution of the banking service industry, top performing banks are investing in this technology with the expectation of significant reduction in the cost of their operations.

At the same time, business customers’ adoption of this technology is important for the success of RPA in the banking industry. Technology is changing at a fast pace and people find it difficult to trust technology which is controlled by bots. When customers are satisfied with technology adoption, the benefits of technology are likely to be higher and more effective. The most challenging issue in the adoption of new technologies is understanding the attitude of customers towards new technologies.

Research Question (RQ)

What are the key factors that influence the adoption of RPA in the retail banking industry to enhance the customer experience?

Our research follows a quantitative approach with a strong empirical analysis to identify the key factors influencing RPA adoption in retail banking industry to enhance customer experience. A survey questionnaire, designed with research items was sent to the appropriate stakeholders like banks’ customers, IT professionals, analysts, senior management decision-makers and and industry experts to get their responses and better understanding of the problem from a customer’s perspective. Demographical items were also included to understand the responses better. The study was carried out with samples collected mostly from the Asia Pacific Region.

There are three significant contributions of this study. First, this research focuses on RPA technology which has not yet drawn enough IS research attention. As RPA research in the domain of IS is sparse, this study contributes theoretically by setting the foundation for future research in this area. Second, To the best of our knowledge, this is one of the foremost to explore adoption factors of RPA from a customer perspective. Third, by hypothesizing the effect of different identified factors, we restate the need for a thorough understanding of these antecedents for a successful adoption of RPA technology in the retail banking industry to enhance customer experience. Holistically, this study, by depicting the RPA adoption factors, will contribute to the field of retail banking and help in understanding technology adoption from a customer perspective.

Review of Literature

Robotic Process Automation

The revolution of the industry and its achievements are so numerous that their impact can hardly be overrated. Robotics research, aimed at finding solutions to the technical necessities is now focusing on human expectations and needs to meet the demanding customer market. Any task which is definable, repeatable and rule based is a good candidate of automation by RPA such as closing and opening of bank accounts and handling various processes in the customer service department. RPA results in efficient and error free service, improves compliance management, expedites repetitive office tasks at a much faster rate and improves business process along with service quality. Hence, cost is reduced and customer experience is enhanced [4,5]. Employees can participate in more value-added services that involve customer interaction, solutions and decision-making. This will allow banks to offer the best experience to their customers. As employees can focus on more customer facing roles, it is most likely to enhance customer satisfaction, acquisition and retention. The ability to collect and mine vast data and provide a complete audit is especially useful in areas like compliance and regulatory reporting. High volume, manually intensive, prone to risks and human errors processes are prime candidates for RPA. When it is enabled with AI, it can virtually eliminate processing errors, hence, improving accuracy and efficiency.

Retail Banking Industry

Retail banking is a service industry focused towards the customer’s money and its management [6]. With the increasing competition in the retail banking industry and rapid technological evolution, how do banks innovate to meet these challenges? Technological innovation in the retail banking industry was spurred on by the need to reduce cost and increase performance. Cost savings came largely through back office automation. Online banking or internet banking, which allows customers to monitor and perform various financial transactions is widely used. Over the past two decades, remote access has migrated from the telephone to the personal computer and most recently to the mobile smart phone [7]. Most recently, with innovation in technology, banks are considering the adoption of RPA to automate repetitive processes.

Consumer Expectations in the Retail Banking Industry

The most important force of change in the banking industry is the rapid evolution of customers wants and desires. Customers are demanding anytimeanywhere delivery of financial services with an increased variety of products and services. Today, banks cannot deny the unprecedented benefits derived from implementing and adopting RPA tools in their environment. This includes corporate banking, retail banking, wealth management and other banking related services involving customer interaction. With the implementation of RPA, it enables Banks to achieve customers’ demands. Cost and fees charged by banks from its customers is one of the factors influencing customer satisfaction [8].

Perceived ease of use and perceived usefulness are the factors affecting intentions to use the Smartphone banking services [9]. Perceived usefulness, and attitude are the most significant drivers of intentions to adopt m-banking services in developed and developing countries [10]. RPA will allow banks to dramatically reduce processing time and enhance customer service with higher accuracy. Banks will be able to handle large volume, repetitive and tedious jobs with the same resources. They can also learn how to improve performance and accuracy with little or no human input. In addition, multi-lingual language processing and voice recognition capabilities allow robots to interact and conduct seemingly intelligent conversations with customers.

Research Problem

From the literature review, it is understood that new technologies have been introduced in the retail banking services sector. In order to stay competitive, banks will have to adopt these new technologies to reap the gains which includes reduction in cost, increased performance and improved customer experience. RPA has penetrated the Healthcare, Insurance and Telecommunication industries. Customer readiness is also a contributing factor for the successful adoption of a new technology. This study would consider the challenges of enhancing the customer experience through the adoption of RPA in the retail banking industry. The factors (independent variables) identified are security and privacy, reliability, usefulness and human-like interaction. Details on the independent variables referenced are covered in the Research Model and Hypotheses section.

Research Model and Hypotheses

Research Model and Hypotheses definition

Figure 1 is the research model on which this research study is built upon. Based on the literature review, the dependent variable has been identified as ‘RPA adoption by the Retail Banking Industry to enhance customer experience’. The various independent variables (which are factors influencing the dependent variable) have been identified as: 1) Security and Privacy; 2) Reliability; 3) Usefulness 4) Human-like interaction. A relationship between these variables has been established to create the research model so that we are able to further the role of each of these factors in influencing the adoption of RPA by retail banks to enhance customer experience.