Books by Saurabh Bhattacharya
SAMVAD, 2024
The banking industry is greatly threatened by cybercrime, which makes it necessary to do a thorou... more The banking industry is greatly threatened by cybercrime, which makes it necessary to do a thorough investigation to comprehend its effects and forthcoming developments for cybersecurity. Research highlights the constant evolution of cyber risks and the disastrous effects of cyberattacks on Indian banking systems. The study explores the rise in cybercrime, the difficulties that the financial services industry faces, and the pressing demand for creative approaches to cybersecurity. Following cyber regulations and being up to date with new developments is essential for reducing risks and protecting the banking sector as cyberattacks are becoming more complex. The author suggests new-age technology and methods that can be used to tackle cyberattacks in the banking industry.
IGI Global, 2024
Chatbots, which provide a smooth and effective channel of contact, have completely changed the wa... more Chatbots, which provide a smooth and effective channel of contact, have completely changed the way companies engage with their clientele. This study explores the underlying technologies and procedures that underpin chatbot functioning, going deep into their complex workings. The chapter offers a thorough analysis of chatbot functionality and industry effects, ranging from machine learning methods to natural language processing. The abstract delves into the significance of user experience, emphasizing the importance of contextual understanding, personalization, and continuous learning in refining chatbot performance. Moreover, it touches upon challenges such as ethical considerations, biases, and limitations inherent in chatbot technology. In essence, this abstract encapsulates the multifaceted workings of chatbots, elucidating the amalgamation of linguistic processing, artificial intelligence, and machine learning that enables these conversational agents to navigate diverse user inputs and contribute to the evolving landscape of human-computer interaction.
IGI Global, 2024
In the dynamic realm of Agile development, the creation of effective user stories stands as a lin... more In the dynamic realm of Agile development, the creation of effective user stories stands as a linchpin for project success. This research article delves into the foundational principles that underpin the craft of user story creation in Agile environments. Recognizing user stories as the nexus between technical teams and end-users, the narrative unfolds through an exploration of key principles, methodologies, and best practices. From empathetic understanding to strategic innovation, the principles outlined serve as a compass for crafting user-centric stories that resonate throughout the Agile development lifecycle. User stories are essential for bridging the gap between technical teams and end users in agile software development. ChatGPT can help Agile teams create user stories by offering preliminary recommendations thanks to its language creation capabilities. The results of software development projects may be greatly improved by using AI, underscoring the need to adopt technical innovations in Agile approaches
IGI Global, 2024
The metaverse combines with reality and creates an alternate universe. The availability of techno... more The metaverse combines with reality and creates an alternate universe. The availability of technological advances enables us to perform new tasks or efficiently complete ordinary duties. The "metaverse," or extended reality, opens up fresh opportunities for fascinating telepathy as well as has the potential to simplify routine tasks. As much as these technologies assist us in this work, education, healthcare, consumption, and pleasure, they also pose several challenges. The chapter tackles the questions of why and when customers will accept an entirely integrated area for a variety of operations, such as buying things and making purchases of Banking services. Examining the potential of Metaverse banking, this study looks into interesting avenues for future development that will influence how financial environments change in virtual spaces. The research anticipates a financial transformation with a focus on Blockchain, virtual assets, smart contracts, decentralized finance (DeFi), and immersive technology.
IGI Global, 2023
Abstract
A variety of applications on handsets, including automatic speech identification, utili... more Abstract
A variety of applications on handsets, including automatic speech identification, utilize “machine learning,” including internet search engines, spam-filtering mail servers, portals that offer tailored advice, a payment gateway that looks for suspicious items, and online platforms that exert pressure. The structure of the computing world provided for the collection of both contents and the commands needed to alter such material. These early systems were primarily built to conduct mathematical tasks. This reached a stage in which the machine began to interpret the information using a linear equation of an actual framework. The machine had only been obeying commands and had no capacity for learning. Its following phase has been to come up with a series of guidelines that might enable the algorithm to draw its unique conclusions using huge quantities of information and apply such conclusions to categorize and anticipate future information. The discipline of intelligent machines, which is jointly referred to as machine learning, is born as a result of “artificial intelligence.”
IGI Global, 2023
Abstract
The method for researchers to ascertain clients' software needs is requirement gatherin... more Abstract
The method for researchers to ascertain clients' software needs is requirement gathering. Requirement gathering rarely occurs successfully, and numerous software programs have failed as a result of incorrect or partial knowledge of the needs of users. The requirement-gathering technique is widely considered to be an essential part of development. The chapter will critically discuss why many developments fail due to poor requirements gathering. It is a challenging task to elicit requirements. When requirements are elicited, errors are most common. Addressing the system's needs presents several challenges, and the chapter intends to study these challenges and provide a solution. Professionals face challenges in gathering requirements due to the unavailability of stakeholders, unclear requirements, frequent changes in demand, and lack of skills for analysts. In a variety of contexts and areas, interviews with a preference for framework proved to be among the best gathering approaches.
IGI Global, 2023
A virtual digital environment is created using the metaverse, which also connects the real world.... more A virtual digital environment is created using the metaverse, which also connects the real world. The existence of information technology allows us to do new tasks or carry out routine tasks more effectively. The extended reality, or “metaverse,” allows for new kinds of captivating telepresence but may also make mundane activities easier. These technologies help us in our employment, education, healthcare, consumption, and entertainment more and more, but they also present a number of obstacles. The concerns discussed in this chapter are why and will customers adopt the fully immersive territory for various activities like shopping and purchasing any products including bank products.
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Books by Saurabh Bhattacharya
A variety of applications on handsets, including automatic speech identification, utilize “machine learning,” including internet search engines, spam-filtering mail servers, portals that offer tailored advice, a payment gateway that looks for suspicious items, and online platforms that exert pressure. The structure of the computing world provided for the collection of both contents and the commands needed to alter such material. These early systems were primarily built to conduct mathematical tasks. This reached a stage in which the machine began to interpret the information using a linear equation of an actual framework. The machine had only been obeying commands and had no capacity for learning. Its following phase has been to come up with a series of guidelines that might enable the algorithm to draw its unique conclusions using huge quantities of information and apply such conclusions to categorize and anticipate future information. The discipline of intelligent machines, which is jointly referred to as machine learning, is born as a result of “artificial intelligence.”
The method for researchers to ascertain clients' software needs is requirement gathering. Requirement gathering rarely occurs successfully, and numerous software programs have failed as a result of incorrect or partial knowledge of the needs of users. The requirement-gathering technique is widely considered to be an essential part of development. The chapter will critically discuss why many developments fail due to poor requirements gathering. It is a challenging task to elicit requirements. When requirements are elicited, errors are most common. Addressing the system's needs presents several challenges, and the chapter intends to study these challenges and provide a solution. Professionals face challenges in gathering requirements due to the unavailability of stakeholders, unclear requirements, frequent changes in demand, and lack of skills for analysts. In a variety of contexts and areas, interviews with a preference for framework proved to be among the best gathering approaches.
A variety of applications on handsets, including automatic speech identification, utilize “machine learning,” including internet search engines, spam-filtering mail servers, portals that offer tailored advice, a payment gateway that looks for suspicious items, and online platforms that exert pressure. The structure of the computing world provided for the collection of both contents and the commands needed to alter such material. These early systems were primarily built to conduct mathematical tasks. This reached a stage in which the machine began to interpret the information using a linear equation of an actual framework. The machine had only been obeying commands and had no capacity for learning. Its following phase has been to come up with a series of guidelines that might enable the algorithm to draw its unique conclusions using huge quantities of information and apply such conclusions to categorize and anticipate future information. The discipline of intelligent machines, which is jointly referred to as machine learning, is born as a result of “artificial intelligence.”
The method for researchers to ascertain clients' software needs is requirement gathering. Requirement gathering rarely occurs successfully, and numerous software programs have failed as a result of incorrect or partial knowledge of the needs of users. The requirement-gathering technique is widely considered to be an essential part of development. The chapter will critically discuss why many developments fail due to poor requirements gathering. It is a challenging task to elicit requirements. When requirements are elicited, errors are most common. Addressing the system's needs presents several challenges, and the chapter intends to study these challenges and provide a solution. Professionals face challenges in gathering requirements due to the unavailability of stakeholders, unclear requirements, frequent changes in demand, and lack of skills for analysts. In a variety of contexts and areas, interviews with a preference for framework proved to be among the best gathering approaches.