Insights In Banking Analytics And Regulatory Compliance Using Ai
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Insights In Banking Analytics And Regulatory Compliance Using Ai
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Author : Rana, Sudhir
language : en
Publisher: IGI Global
Release Date : 2025-04-25
Insights In Banking Analytics And Regulatory Compliance Using Ai written by Rana, Sudhir and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-25 with Business & Economics categories.
The integration of artificial intelligence (AI) into banking analytics and regulatory compliance revolutionizes the financial industry, enhancing operational efficiency, improving decision-making, and strengthening regulatory adherence. AI-driven analytics enable banks to process data in real time, uncovering valuable insights that can drive personalized services, risk management strategies, and fraud detection. AI enhances the monitoring of financial transactions, automates compliance reporting, and helps identify potential risks related to money laundering, fraud, and illegal activities. By leveraging machine learning algorithms and natural language processing, AI tools can ensure that banks remain up to date with regulations, reduce human error, and mitigate the cost and complexity of compliance. The use of AI in banking analytics and regulatory compliance reshapes the way banks operate and fosters greater transparency, accountability, and trust within the financial ecosystem. Insights in Banking Analytics and Regulatory Compliance Using AI focuses on various aspects of use of AI on business analytics. It explores how AI reshapes the field of business analytics and drives more efficient, informed decision making. This book covers topics such as blockchain, data science, and artificial intelligence, and is a useful resource for business owners, policymakers, engineers, academicians, researchers, and data scientists.
Disrupting Finance
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Author : Theo Lynn
language : en
Publisher: Palgrave Pivot
Release Date : 2018-12-19
Disrupting Finance written by Theo Lynn and has been published by Palgrave Pivot this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-19 with Business & Economics categories.
This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase agility and improve customer retention. Technologies such as blockchain, cloud computing, mobile technologies, big data analytics and social media therefore have perhaps more potential in this industry and area of business than any other. This book defines a fintech ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research and offering perspectives from business, technology and industry.
Data Model Scorecard
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Author : Steve Hoberman
language : en
Publisher: Technics Publications
Release Date : 2015-11-01
Data Model Scorecard written by Steve Hoberman and has been published by Technics Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-01 with Computers categories.
Data models are the main medium used to communicate data requirements from business to IT, and within IT from analysts, modelers, and architects, to database designers and developers. Therefore it’s essential to get the data model right. But how do you determine right? That’s where the Data Model Scorecard® comes in. The Data Model Scorecard is a data model quality scoring tool containing ten categories aimed at improving the quality of your organization’s data models. Many of my consulting assignments are dedicated to applying the Data Model Scorecard to my client’s data models – I will show you how to apply the Scorecard in this book. This book, written for people who build, use, or review data models, contains the Data Model Scorecard template and an explanation along with many examples of each of the ten Scorecard categories. There are three sections: In Section I, Data Modeling and the Need for Validation, receive a short data modeling primer in Chapter 1, understand why it is important to get the data model right in Chapter 2, and learn about the Data Model Scorecard in Chapter 3. In Section II, Data Model Scorecard Categories, we will explain each of the ten categories of the Data Model Scorecard. There are ten chapters in this section, each chapter dedicated to a specific Scorecard category: · Chapter 4: Correctness · Chapter 5: Completeness · Chapter 6: Scheme · Chapter 7: Structure · Chapter 8: Abstraction · Chapter 9: Standards · Chapter 10: Readability · Chapter 11: Definitions · Chapter 12: Consistency · Chapter 13: Data In Section III, Validating Data Models, we will prepare for the model review (Chapter 14), cover tips to help during the model review (Chapter 15), and then review a data model based upon an actual project (Chapter 16).
Operations Management
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Author : Antonella Petrillo
language : en
Publisher: BoD – Books on Demand
Release Date : 2021-03-03
Operations Management written by Antonella Petrillo and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-03 with Business & Economics categories.
Global competition has caused fundamental changes in the competitive environment of the manufacturing and service industries. Firms should develop strategic objectives that, upon achievement, result in a competitive advantage in the market place. The forces of globalization on one hand and rapidly growing marketing opportunities overseas, especially in emerging economies on the other, have led to the expansion of operations on a global scale. The book aims to cover the main topics characterizing operations management including both strategic issues and practical applications. A global environmental business including both manufacturing and services is analyzed. The book contains original research and application chapters from different perspectives. It is enriched through the analyses of case studies.
Artificial Intelligence In Financial Services And Banking Industry
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Author : Dr. V.V.L.N. Sastry
language : en
Publisher: Idea Publishing
Release Date : 2020-03-20
Artificial Intelligence In Financial Services And Banking Industry written by Dr. V.V.L.N. Sastry and has been published by Idea Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-20 with Business & Economics categories.
In the last couple of years, the finance and banking sectors have increasingly deployed and implemented Artificial Intelligence (AI) technologies. AI and machine learning are being rapidly adopted for a range of applications for front-end and back end processes to both business and financial management operations. Thus, it is quite significant to consider the financial stability repercussions of such uses. Since AI is relatively new, the data on the usage is largely unavailable, any analysis may be necessarily considered Preliminary1 . Some of the current and potential use cases of AI and machine learning in the finance sector include the following. Institutions use AI and machine learning methods to optimize scarce capital, back-test models, and analyze the market impact of trading large positions. Financial institutions and vendors use AI and machine learning techniques to evaluate credit quality for market and price insurance contracts, and to automate client interaction. Brokers, hedge funds, and other firms are using AI and machine learning to find pointers for higher (and uncorrelated) returns to optimize trading execution. Private and public sector institutions use these technologies for data quality assessment, surveillance, regulatory compliance, and fraud detection. This book seeks to map the use of AI in current state of affairs in the banking and financial sector. By doing so, it explores: The present uses of AI in banking and finance and its narrative across the globe.
Machine Learning And Modeling Techniques In Financial Data Science
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Author : Chen, Haojun
language : en
Publisher: IGI Global
Release Date : 2025-01-22
Machine Learning And Modeling Techniques In Financial Data Science written by Chen, Haojun and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Business & Economics categories.
The integration of machine learning and modeling in finance is transforming how data is analyzed, enabling more accurate predictions, risk assessments, and strategic planning. These advanced techniques empower financial professionals to uncover hidden patterns, automate complex processes, and enhance decision-making in volatile markets. As industries increasingly rely on data-driven insights, the adoption of these tools contributes to greater efficiency, reduced uncertainty, and competitive advantage. This technological shift not only drives innovation within financial sectors but also supports broader economic stability and growth by improving forecasting and mitigating risks. Machine Learning and Modeling Techniques in Financial Data Science provides an updated review and highlights recent theoretical advances and breakthroughs in professional practices within financial data science, exploring the strategic roles of machine learning and modeling techniques across various domains in finance. It offers a comprehensive collection that brings together a wealth of knowledge and experience. Covering topics such as algorithmic trading, financial technology (FinTech), and natural language processing (NLP), this book is an excellent resource for business professionals, leaders, policymakers, researchers, academicians, and more.
Shaping Cutting Edge Technologies And Applications For Digital Banking And Financial Services
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Author : Alex Khang
language : en
Publisher: CRC Press
Release Date : 2025-01-31
Shaping Cutting Edge Technologies And Applications For Digital Banking And Financial Services written by Alex Khang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-31 with Business & Economics categories.
Cutting-edge technologies have recently shown great promise in a variety of activities for enhancing the existing services of a bank such as the improvement of transactions, ensuring that transactions are done correctly, and managing records of services of savings accounts, loan and mortgage services, wealth management, providing credit and debit cards, overdraft services and physical evidence as key drivers of bank ecosystem. In the financial world, emerging analytics and prediction tools can be used to analyze and visualize structured data, such as financial market data, and to forecast future trends that can be supported by leaders to make informed decisions about investment strategies. This book explores the importance of artificial intelligence (AI)-based predictive analytics tools in the financial services industry and their role in combating financial fraud. As fintech continues to revolutionize the financial landscape, it also brings forth new challenges, including sophisticated fraudulent activities. Therefore, this book shares the problem of enhancing fraud detection and prevention through the application of predictive analytics. This book contributes to a deeper understanding of the importance of predictive analytics in the finance field and its pivotal role in cybersecurity and combating fraud. It provides valuable insights for the financial services industry, researchers, and policymakers, aiming to fortify the security and resilience of financial systems in the face of evolving financial fraud challenges. Cuurently, AI has replaced recurrent intellectual decisions due to the availability of information and its access. These changes have created a revolution in financial operations resulting in environmental variations in the banking and finance sectors. Likewise, analytics transformed the not only finance field but also banking as it is increasing the transparency of lending-related activities. In addition, this book provides a set of tools for complex analyses of people-related data and through a variety of statistical analysis techniques ranging from simple descriptive statistics to machine learning, HR analytics enables performance evaluation and increases the transparency of finance transactions as well as the problems, advantages, and disadvantages of new digital transformation. The book is not merely a compilation of technical knowledge; it is a beacon of innovation that beckons readers to envision a future where cutting-edge technologies and finance services intertwine seamlessly. With its engaging and thought-provoking content, the book leaves an indelible impression, urging readers to embrace the transformative power of technology and embark on a collective mission to unlock the full potential of fintech for the betterment of humanity.
Generative Artificial Intelligence In Finance
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Author : Pethuru Raj Chelliah
language : en
Publisher: John Wiley & Sons
Release Date : 2025-01-22
Generative Artificial Intelligence In Finance written by Pethuru Raj Chelliah and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Computers categories.
This comprehensive volume delves deep into the diverse applications and implications of generative AI across accounting, finance, economics, business, and management, providing readers with a holistic understanding of this rapidly evolving landscape. Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes provides a comprehensive guide to ethically harnessing generative AI systems to reshape financial management. Generative AI is a key theme across the accounting and finance sectors to drive significant optimizations leading to sustainability. Across 22 chapters, leading researchers supply innovative applications of large language models across the economic realm. Through detailed frameworks, real-world case studies, and governance recommendations, this book highlights applied research for generative AI in finance functions. Several chapters demonstrate how data-driven insights from AI systems can optimize complex financial processes to reduce resource usage, lower costs, and drive positive environmental impact over the long term. In addition, chapters on AI-enabled risk assessment, fraud analytics, and regulatory technology highlight applied research for generative AI in finance. The book also explores emerging applications like leveraging blockchain and metaverse interfaces to create generative AI models that can revolutionize areas from carbon credit trading to virtual audits. Overall, with in-depth applied research at the nexus of sustainability and optimization enabled by data science and generative AI, the book offers a compilation of best practices in leveraging AI for optimal, ethical, and future-oriented financial management. Audience The audience for this book is quite diverse, ranging from financial and accounting experts across banking, insurance, consultancies, regulatory agencies, and corporations seeking to enhance productivity and efficiency; business leaders want to implement ethical and compliant AI practices; researchers exploring the domain of AI and finance.
Enhancing And Predicting Digital Consumer Behavior With Ai
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Author : Musiolik, Thomas Heinrich
language : en
Publisher: IGI Global
Release Date : 2024-05-13
Enhancing And Predicting Digital Consumer Behavior With Ai written by Musiolik, Thomas Heinrich and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-13 with Business & Economics categories.
Understanding consumer behavior in today's digital landscape is more challenging than ever. Businesses must navigate a sea of data to discern meaningful patterns and correlations that drive effective customer engagement and product development. However, the ever-changing nature of consumer behavior presents a daunting task, making it difficult for companies to gauge the wants and needs of their target audience accurately. Enhancing and Predicting Digital Consumer Behavior with AI offers a comprehensive solution to this pressing issue. A strong focus on concepts, theories, and analytical techniques for tracking consumer behavior changes provides the roadmap for businesses to navigate the complexities of the digital age. By covering topics such as digital consumers, emotional intelligence, and data analytics, this book serves as a timely and invaluable resource for academics and practitioners seeking to understand and adapt to the evolving landscape of consumer behavior.
Utilizing Ai And Machine Learning In Financial Analysis
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Author : Darwish, Dina
language : en
Publisher: IGI Global
Release Date : 2025-01-21
Utilizing Ai And Machine Learning In Financial Analysis written by Darwish, Dina and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-21 with Business & Economics categories.
Machine learning models can imitate the cognitive process by assimilating knowledge from data and employing it to interpret and analyze information. Machine learning methods facilitate the comprehension of vast amounts of data and reveal significant patterns incorporated within it. This data is utilized to optimize financial business operations, facilitate well-informed judgements, and aid in predictive endeavors. Financial institutions utilize it to enhance pricing, minimize risks stemming from human error, mechanize repetitive duties, and comprehend client behavior. Utilizing AI and Machine Learning in Financial Analysis explores new trends in machine learning and artificial intelligence implementations in the financial sector. It examines techniques in financial analysis using intelligent technologies for improved business services. This book covers topics such as customer relations, predictive analytics, and fraud detection, and is a useful resource for computer engineers, security professionals, business owners, accountants, academicians, data scientists, and researchers.