Figure 2 - uploaded by Netra Pal Singh
Content may be subject to copyright.
Source publication
This paper discusses the adoption of chatbots and virtual Assistants by different category of banks (private sector banks and public sector banks) in India. The research paper presents a brief introduction of banking industry in India, history, characteristics, and architecture of chatbots and virtual assistants. The research paper also included ba...
Similar publications
Accurate generative chatbots are usually trained on large datasets of question–answer pairs. Despite such datasets not existing for some languages, it does not reduce the need for companies to have chatbot technology in their websites. However, companies usually own small domain-specific datasets (at least in the form of an FAQ) about their product...
Citations
... Ensuring data security and privacy is a critical challenge, requiring robust cybersecurity measures, compliance with data protection regulations and secure storage and transmission of data. [43][44][45][46] Scalability and Flexibility: Organizations with diverse HR processes and requirements may find it challenging to scale and adapt automation solutions across different functions and departments. Automation tools need to be flexible enough to accommodate varying HR workflows and evolving business needs. ...
Automation has become a game-changer in the field of Human Resource (HR), revolutionizing traditional HR operations and transforming the way organizations manage their workforce. This study explores the concept of automation in HR and its impact on various HR functions including recruitment, onboarding, employee data management, payroll administration, performance management and employee engagement. The study delves into the benefits of HR automation such as increased efficiency, improved accuracy, reduced manual errors and enhanced employee experiences. It highlights the different technologies and tools used for HR automation including Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML) and data analytics. Overall, automation in HR operations brings numerous benefits to organizations including improved efficiency, accuracy, compliance and employee satisfaction. HR professionals can focus on strategic initiatives and value-added tasks, resulting in better talent management and organizational success in the dynamic business landscape.
... Advancements in NLP and large data helped in the development of SIRI. Siri can hold realistic general conversations and even understand jokes [3]. Alexa was developed and launched by Amazon in 2016 and is popular in home automation. ...
Chatbot assists users by providing useful responses and not just a conversational system functionalities. The advanced Chatbots such as Siri and Alexa are the results of evolution of different response generation and NLU techniques that have arrived since 1960s. Usually, chatbots are designed to address domain-specific queries; for instance, a medical chatbot requires the user to provide his/her symptoms; in the corporate world, the chatbots designed are mainly for addressing the FAQs asked by their clients/customers. However, state-of-the-art technologies are emerging, and knowledge graph is one of them. The idea of using knowledge graphs is that the data stored in them is linked. The proposed-chatbot addresses the problem of answering factoid questions by retrieving information from knowledge graphs. Initially, the neural machine translation approach was used; however, due to its limitations, keyword extraction approach was adopted for the proposed chatbot. In order to compare the proposed chatbot system with DBpedia metrics, the F-measure quality parameter were used for determining the overall performance of chatbots.KeywordsKnowledge graphSemantic webRASAKeyword extractionNeural machine translationSPARQLDBpedia chatbot
... Studies have focussed on social characteristics in humanchatbot interaction design (Chaves & Gerosa, 2021), using chatbots in an enterprise context (Brachten et al., 2021), brand experience and brand love of using Indian banking chatbots (Trivedi, 2019), aspects and features of chatbots in Indian banks (Pal & Singh, 2019), the impact of AI in commercial banks in India (Mor & Gupta, 2021) and use of AI in Indian banks (Srivastava, 2021). Studies on banking chatbots have focussed on technology acceptance theories (Alt et al., 2021;Bagana et al., 2021). ...
Chatbots are virtual conversation agents that offer innovative features to connect with customers and thus offer a promising avenue to engage customers. Currently many private and nationalized banks are deploying chatbots for connecting and communicating with customers. This technology is expected to dominate the banking sector in the future by improving customer service. However, the success of banking chatbots will be effective when customers are satisfied with the chatbots and engage in using them. To probe in to the question, this study investigates the antecedents and consequences of customer brand engagement in using banking chatbots, with the lens of diffusion of innovation theory. The antecedents include interactivity, time convenience, compatibility, complexity, observability, and trialability. The consequences are satisfaction with the brand experience and customer brand usage intention. The theorized model has been validated with 470 Indian banking chatbot customers usable responses. The results suggest that trialability, compatibility, and interactivity positively influence customer brand engagement through a chatbot, thereby influencing satisfaction with the brand experience and customer brand usage intention. The paper presents theoretical and managerial implications which enable banks to strengthen customer engagement, satisfaction and brand usage intention through chatbots.
... .2. Chatbots And Virtual Assistants, Ways To Connect In Indian Banks[10] ...
A conversational agent, often known as a Chatbot, is computer software that can speak with humans using natural language. In artificial intelligence and natural language processing, conversation modeling is a critical task. Since its beginnings, creating a good chatbot has been the most difficult challenge in artificial intelligence. Although chatbots can do a wide range of tasks, their primary role is to understand and reply to human speech. Previously, basic statistical approaches or handwritten templates and rules were used to create chatbot architectures. Due to their greater learning capabilities, end-to-end neural networks supplanted these models about 2015. Conversation modeling is dominated by the encoder-decoder recurrent model, especially at the moment. This architecture was inspired by the neural machine translation domain, where it performed admirably. Until now, there have been a lot of features and variations. It provides an overview of a chatbot, including what it is, its merits, limitations, and uses. The survey section covers a wide range of topics, including Healthcare, Banking, E-commerce, and Human Resources. We offered a universal theory that explains how all areas may be combined into a single chatbot.
... Chatbots, are artificial intelligence-based automated chat systems which simulate human chats without any human interventions also known as chat robot, talk bot, IM bot, interactive agents, chatterbot or chatterbox and are helping in real-time communications, handling customer enquiries, and other aspects of businesses to optimize overall customer satisfaction(Singh & Singh, 2019). Chatbots are typically text-based and are programmed to reply to only a specific set of questions or statements fails to hold long, continuing human interaction if the customer asks a different question.2 ...
The deployment of artificial intelligence (AI) in chatbots, virtual assistants, and ATMs reduces technical inefficiency in Indian commercial banks. The impact of (AI) on the technical efficiency of 47 examined commercial banks in India has reduced technical inefficiency to 11%, primarily due to internal factors or decision making. The verdict endorses the speeding up of (AI) deployment besides raising the level of assets, reducing the nonperforming assets, especially banks functioning in the public sector.
... AI can enhance profitability and refining the decision-making process made at various operational management levels (Vedapradha & Hariharan, 2018), application of innovative technologies in banks to achieve efficiency (Lagarde, 2018), and creating globally unified practices, policies and framework (Erdélyi & Goldsmith, 2018). The Indian banking sector's technical efficiency has been investigated employing stochastic frontier and data envelopment analysis along with recommending various means for augmenting the efficiency/profitability/productivity and overall performance of banks in India (Keshari & Paul, 1994 (Singh & Singh, 2019) and investing in AI-powered Robots for serving modern tech-savvy customers efficiently (Ayachit, 2017). Banking industry gradually shifting and exploring the technology for enhancing customer services (Salunkhe, 2019), and concentrating on reducing costs on jobless tasks, optimising service delivery, reducing strategy cycles and promoting customer loyalty for realising more profitability ( (Kusalovic, 2017). ...
... Recent advancements in AI technology focusing on minimising the cost of predictions, making them faster with utmost accuracy instead of enhancing the performance or efficiency of banks. The adoption of Artificial intelligence tools like chatbots and virtual assistant in India was initiated in 2017, and slowly the deployment and adoption of AI is picking up in the banking industry (Singh & Singh, 2019). In this backdrop, this paper selected 47 commercial banks to investigate their technical efficiency by including an inefficiency effects model that provides for chatbots 1 /virtual assistant 2 and ATMs as the possible factors influencing the banks operating' technical inefficiency in India. 1 Chatbots, AI-enabled automated chat systems, performs chat with human sans human involvements. ...
... In this backdrop, this paper selected 47 commercial banks to investigate their technical efficiency by including an inefficiency effects model that provides for chatbots 1 /virtual assistant 2 and ATMs as the possible factors influencing the banks operating' technical inefficiency in India. 1 Chatbots, AI-enabled automated chat systems, performs chat with human sans human involvements. These are also known as chatterbot or chatterbox, talk bot, interactive agents, chat robot, IM bot, handling customer inquiries, real-time communications, and other aspects of businesses to optimise overall customer satisfaction (Singh & Singh, 2019). Chatbots are programmed to reply to only a specific set of questions or statements, typically text-based, and usually fail to hold long, continuing human interaction if they ask a different question. ...
Artificial intelligence technology in the agricultural sector can reduce carbon emissions from agrarian activities and revitalize the whole industry. The Indian agricultural sector has become costly, time‐consuming, and outdated owing to the global warming process. The deployment of AI technology in Indian agriculture is still a distant dream, given the peculiarities like small‐size farms, traditional farming methods, lack of credit, storage facilities, and the decision maker's risk‐seeking attitude. AI solutions need to be delivered at the farmers' doorstep in their local language, with proper training, input support, and in collective/cooperative manner for realizing sustainable and green agriculture.
... Chatbot originally coined from the words "chat" and "robot" is a computer program designed to simulate human conversations via text. They analyze and interpret words or text given by humans and provide a pre-set answer [5]. There are three types of chatbots; Rule based chatbots which provide predefined answers to questions that exists in its model known as pattern matching, Intelligent chatbots which use machine learning models to learn from users request or information to teach themselves overtime to understand more questions and deliver better answers where a distinct pattern is required for the chatbot to provide accurate information to queries and AI Powered Chatbot which combine the power of rule based and intelligent chatbots. ...
Technology has been a tool that has driven the banking sector to efficiently serve its customer better. Chatbots have many advantages for both banks and customer as they improve convenience, provide new data collection and enable new user touchpoints. This review paper discusses the importance and role of chatbot adoption in the Nigerian banking sector and provides insight which are critical to effective chatbot deployment. Paper concludes that if stakeholders in the Nigerian banking sector intend to be relevant in the industry of the future, adoption of a dynamic plan is necessary as the future promises an exciting partnership between human professionals and Artificial Intelligence.
Financial institutions have, in recent years, increasingly begun to rely on the use of financial technologies (fintech) to provide more efficient and convenient services. Adapting to fintech innovations brings new challenges and opportunities. At the same time, sustainable finance has become the subject of interest for academics and practitioners alike. Both directly and indirectly, fintech be used to improve sustainability and influence policies and regulations. Issues such as climate change, water pollution, and non-renewable resource management can all be addressed in innovative ways with fintech. Unfortunately, as with any new technology, these innovations also present new challenges and environmental risks that need to be carefully monitored and controlled. Thus, fintech and its application in sustainability is a double-edged sword that calls for both consideration and caution. This book aims to provide an overview of various fintech applications with an analysis of how fintech will influence the future of sustainable finance. In this introductory chapter, we explore sustainability and sustainable finance, why they are important, and how fintech can be a catalyst for meaningful change. In addition, we offer a summary of the eleven chapters of this collection.
Introduction-Today banks have started adopting latest cutting-edge AI technology in their work processes. Objective-The main objective of the study is to systematically review the diverse uses of Artificial Intelligence and understand its impact on customer service, employee productivity and organisation performance mainly in banking sector. Research Methodology-This research paper based on systematic literature review has been conducted as per guidelines of PRISMA i.e, Preferred Reporting Items for Systematic Reviews and Meta Analyses. Authors have studied articles from around 15 years research papers i.e, from 2007 to 2022 from authentic database such as WOS, Scopus, Springer, Scopus, Science direct, Elsevier and other reputed journals while using search words like artificial intelligence, banking, emerging technology, machine learning, banking applications, bank performance, customer satisfaction. Result-Initially, a total of 108 titles were identified, 31 duplicate entries were found. 87 publications were considered for abstract reading after manually screening of all titles. Finally, 46 studies were included for systematic review study who met the inclusion criteria. The literature review supported that artificial intelligence technology plays a very significant and crucial role in the area of finance specially banking sector.
Introduction-Today banks have started adopting latest cutting-edge AI technology in their work processes. Objective-The main objective of the study is to systematically review the diverse uses of Artificial Intelligence and understand its impact on customer service, employee productivity and organisation performance mainly in banking sector. Research Methodology-This research paper based on systematic literature review has been conducted as per guidelines of PRISMA i.e, Preferred Reporting Items for Systematic Reviews and Meta Analyses. Authors have studied articles from around 15 years research papers i.e, from 2007 to 2022 from authentic database such as WOS, Scopus, Springer, Scopus, Science direct, Elsevier and other reputed journals while using search words like artificial intelligence, banking, emerging technology, machine learning, banking applications, bank performance, customer satisfaction. Result-Initially, a total of 108 titles were identified, 31 duplicate entries were found. 87 publications were considered for abstract reading after manually screening of all titles. Finally, 46 studies were included for systematic review study who met the inclusion criteria. The literature review supported that artificial intelligence technology plays a very significant and crucial role in the area of finance specially banking sector.
