Deep Learning And Natural Language Processing For Innovation Detection In Fintech
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Intersecting Natural Language Processing and FinTech Innovations in Service Marketing
Disruptive paradigms emerge from the accelerating advancements in natural language processing (NLP) and financial technology (FinTech), which present unparalleled opportunities in customer engagement. In an era where personalized experiences and sophisticated artificial intelligence (AI) interactions are pivotal for brand success, it is imperative for businesses to capitalize on AI’s capabilities for customer needs. By translating theoretical progress into actionable strategies, business can craft deeply personalized messages and experiences. Adopting these technologies to meet evolving consumer expectations and cultivating enduring customer loyalty is of strategic importance. Intersecting Natural Language Processing and FinTech Innovations in Service Marketing provides a meticulous analysis of these underlying technologies, bolstered by empirical case studies demonstrating successful integrations. Critical issues such as data privacy, security, and ethical considerations are also addressed, offering a comprehensive perspective on the opportunities and challenges inherent in this dynamic field. Covering topics such as pricing insinuations, key performance indicators (KPIs), and vulnerable consumers, this book is an excellent resource for computer engineers, marketers, policymakers, business owners, researchers, academicians, and more.
Deep Learning and Natural Language Processing for Innovation Detection in FinTech
Advancements in technology have resulted in the emergence of numerous FinTech innovations. However, a global understanding of such innovations is limited, due to a lack of an underlying taxonomy and benchmark datasets in the FinTech domain. To address this limitation, we develop a FinTech taxonomy and manually annotate a set of FinTech patent abstracts according to the taxonomy. We use the annotated dataset to train deep learning models. Experimental results show that the deep learning models can accurately identify FinTech innovations. Specifically, we focus on patent document classification, and explores the predictive capabilities of three document sections alone and in combination. Our results indicate that the title and abstract in combination are most efficient in detecting FinTech innovations.
Fintech and Cryptocurrency
FINTECH and CRYPTOCURRENCY Dive into the world of fintech and cryptocurrency through the engaging perspectives of this diverse group of authors and uncover the intricate connections between technology, finance, and cryptocurrency that make this a must-have for anyone intrigued by the future of digital society. Digital currencies, decentralization of money, and the growth of new technologies like blockchain, the Internet of Things, and machine learning have produced new opportunities and difficulties for banking and finance, as well as users of these services in electronic commerce. New banking and finance technologies may improve operational efficiency, risk management, compliance, and client pleasure, but they can decrease barriers and introduce new concerns, such as cybersecurity risk. Cryptocurrencies with smart contracts for payments and trading, as well as AI systems with adaptive algorithms that allow picture and speech recognition, expert judgement, group categorization, and forecasting in a variety of fields, are instances of increased automation. Simultaneously, the potentials pose risks and raise regulatory concerns. The rise of blockchain technology and its widespread use have had a significant impact on the operation and management of digital systems. At the same time, researchers and practitioners have paid close attention to digital finance. Blockchain’s first applications were limited to the production of digital currency, but it has now been expanded to include financial and commercial applications. Innovative digital finance has had a huge impact on business and society since it has been extensively adopted by businesses and consumers. As a result, the goal of this edited book is to expand and deepen our knowledge of the business possibilities of novel blockchain and digital financial applications.