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| customer churn analysis in banking industry: Business Information Systems Workshops Witold Abramowicz, Adrian Paschke, 2019-01-02 This book constitutes revised papers from the seven workshops and one accompanying event which took place at the 21st International Conference on Business Information Systems, BIS 2018, held in Berlin, Germany, in July 2018. Overall across all workshops, 58 out of 122 papers were accepted. The workshops included in this volume are: AKTB 2018 - 10th Workshop on Applications of Knowledge-Based Technologies in Business BITA 2018 - 9th Workshop on Business and IT Alignment BSCT 2018 - 1st Workshop on Blockchain and Smart Contract Technologies IDEA 2018 - 4th International Workshop on Digital Enterprise Engineering and Architecture IDEATE 2018 - 3rd Workshop on Big Data and Business Analytics Ecosystems SciBOWater 2018 - Scientific Challenges & Business Opportunities in Water Management QOD 2018 - 1st Workshop on Quality of Open Data In addition, one keynote speech in full-paper length and contributions from the Doctoral Consortium are included |
| customer churn analysis in banking industry: Data Mining Methods and Models Daniel T. Larose, 2006-02-02 Apply powerful Data Mining Methods and Models to Leverage your Data for Actionable Results Data Mining Methods and Models provides: * The latest techniques for uncovering hidden nuggets of information * The insight into how the data mining algorithms actually work * The hands-on experience of performing data mining on large data sets Data Mining Methods and Models: * Applies a white box methodology, emphasizing an understanding of the model structures underlying the softwareWalks the reader through the various algorithms and provides examples of the operation of the algorithms on actual large data sets, including a detailed case study, Modeling Response to Direct-Mail Marketing * Tests the reader's level of understanding of the concepts and methodologies, with over 110 chapter exercises * Demonstrates the Clementine data mining software suite, WEKA open source data mining software, SPSS statistical software, and Minitab statistical software * Includes a companion Web site, www.dataminingconsultant.com, where the data sets used in the book may be downloaded, along with a comprehensive set of data mining resources. Faculty adopters of the book have access to an array of helpful resources, including solutions to all exercises, a PowerPoint(r) presentation of each chapter, sample data mining course projects and accompanying data sets, and multiple-choice chapter quizzes. With its emphasis on learning by doing, this is an excellent textbook for students in business, computer science, and statistics, as well as a problem-solving reference for data analysts and professionals in the field. An Instructor's Manual presenting detailed solutions to all the problems in the book is available onlne. |
| customer churn analysis in banking industry: Computational Intelligence in Data Science Vallidevi Krishnamurthy, Suresh Jaganathan, Kanchana Rajaram, Saraswathi Shunmuganathan, 2021-12-11 This book constitutes the refereed post-conference proceedings of the Fourth IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2021, held in Chennai, India, in March 2021. The 20 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers cover topics such as computational intelligence for text analysis; computational intelligence for image and video analysis; blockchain and data science. |
| customer churn analysis in banking industry: Innovations in Electronics and Communication Engineering H. S. Saini, R. K. Singh, Mirza Tariq Beg, J. S. Sahambi, 2020-06-24 This book is a collection of the best research papers presented at the 8th International Conference on Innovations in Electronics and Communication Engineering at Guru Nanak Institutions Hyderabad, India. Featuring contributions by researchers, technocrats and experts, the book covers various areas of communication engineering, like signal processing, VLSI design, embedded systems, wireless communications, and electronics and communications in general, as well as cutting-edge technologies. As such, it is a valuable reference resource for young researchers. |
| customer churn analysis in banking industry: Data Science for Business Foster Provost, Tom Fawcett, 2013-07-27 Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the data-analytic thinking necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates |
| customer churn analysis in banking industry: Data Science and Data Analytics Amit Kumar Tyagi, 2021-09-22 Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured (labeled) and unstructured (unlabeled) data. It is the future of Artificial Intelligence (AI) and a necessity of the future to make things easier and more productive. In simple terms, data science is the discovery of data or uncovering hidden patterns (such as complex behaviors, trends, and inferences) from data. Moreover, Big Data analytics/data analytics are the analysis mechanisms used in data science by data scientists. Several tools, such as Hadoop, R, etc., are used to analyze this large amount of data to predict valuable information and for decision-making. Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in an unstructured form that requires advanced analytics tools. But while analyzing this data, we face several concerns, such as complexity, scalability, privacy leaks, and trust issues. Data science helps us to extract meaningful information or insights from unstructured or complex or large amounts of data (available or stored virtually in the cloud). Data Science and Data Analytics: Opportunities and Challenges covers all possible areas, applications with arising serious concerns, and challenges in this emerging field in detail with a comparative analysis/taxonomy. FEATURES Gives the concept of data science, tools, and algorithms that exist for many useful applications Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems Identifies many areas and uses of data science in the smart era Applies data science to agriculture, healthcare, graph mining, education, security, etc. Academicians, data scientists, and stockbrokers from industry/business will find this book useful for designing optimal strategies to enhance their firm’s productivity. |
| customer churn analysis in banking industry: Artificial Intelligence in Banking Introbooks, 2020-04-07 In these highly competitive times and with so many technological advancements, it is impossible for any industry to remain isolated and untouched by innovations. In this era of digital economy, the banking sector cannot exist and operate without the various digital tools offered by the ever new innovations happening in the field of Artificial Intelligence (AI) and its sub-set technologies. New technologies have enabled incredible progression in the finance industry. Artificial Intelligence (AI) and Machine Learning (ML) have provided the investors and customers with more innovative tools, new types of financial products and a new potential for growth.According to Cathy Bessant (the Chief Operations and Technology Officer, Bank of America), AI is not just a technology discussion. It is also a discussion about data and how it is used and protected. She says, In a world focused on using AI in new ways, we're focused on using it wisely and responsibly. |
| customer churn analysis in banking industry: Customer journey analytics for the financial sector. How do customers make decisions regarding their bank? Christopher Roßmann, 2019-08-29 The financial industry is facing wide-ranging changes due to historically low interest rates, higher regulation and the rise of online banks and digitization. Traditional retail banks have been losing market share, bank branches have been merged as well as products and services changed. Christopher Roßmann shows how important it is that banks understand their customers’ decision-making process. Therefore, he conducts a customer journey analysis for the German saving bank. He focusses on comprehensive bank consultations. Roßmann uncovers reasons for a low perception of the consultation approach by customers. In his book, he provides improvement proposals for several units of the bank and develops an improved target vision for the customer journey. In this book: - Sparkasse; - Sparkassen-Finanzkonzept; - process management; - product management; - marketing; - UX |
| customer churn analysis in banking industry: Discovering Knowledge in Data Daniel T. Larose, 2005-01-28 Learn Data Mining by doing data mining Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets. Employing a white box methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms and statistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include: * Data preprocessing and classification * Exploratory analysis * Decision trees * Neural and Kohonen networks * Hierarchical and k-means clustering * Association rules * Model evaluation techniques Complete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge. An Instructor's Manual presenting detailed solutions to all the problems in the book is available online. |
| customer churn analysis in banking industry: Proceedings of 4th International Conference on Artificial Intelligence and Smart Energy S. Manoharan, |
| customer churn analysis in banking industry: New Trends in Computational Collective Intelligence David Camacho, Sang-Wook Kim, Bogdan Trawiński, 2014-09-10 This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods and Applications, Computer Vision, and Intelligent Computational Methods. This book will be useful for graduate and PhD students in computer science as well as for mature academics, researchers and practitioners interested in the methods and applications of collective computational intelligence in order to create new intelligent systems. |
| customer churn analysis in banking industry: Fighting Churn with Data Carl S. Gold, 2020-12-22 The beating heart of any product or service business is returning clients. Don't let your hard-won customers vanish, taking their money with them. In Fighting Churn with Data you'll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether. Summary The beating heart of any product or service business is returning clients. Don't let your hard-won customers vanish, taking their money with them. In Fighting Churn with Data you'll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether. This hands-on guide is packed with techniques for converting raw data into measurable metrics, testing hypotheses, and presenting findings that are easily understandable to non-technical decision makers. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Keeping customers active and engaged is essential for any business that relies on recurring revenue and repeat sales. Customer turnover—or “churn”—is costly, frustrating, and preventable. By applying the techniques in this book, you can identify the warning signs of churn and learn to catch customers before they leave. About the book Fighting Churn with Data teaches developers and data scientists proven techniques for stopping churn before it happens. Packed with real-world use cases and examples, this book teaches you to convert raw data into measurable behavior metrics, calculate customer lifetime value, and improve churn forecasting with demographic data. By following Zuora Chief Data Scientist Carl Gold’s methods, you’ll reap the benefits of high customer retention. What's inside Calculating churn metrics Identifying user behavior that predicts churn Using churn reduction tactics with customer segmentation Applying churn analysis techniques to other business areas Using AI for accurate churn forecasting About the reader For readers with basic data analysis skills, including Python and SQL. About the author Carl Gold (PhD) is the Chief Data Scientist at Zuora, Inc., the industry-leading subscription management platform. Table of Contents: PART 1 - BUILDING YOUR ARSENAL 1 The world of churn 2 Measuring churn 3 Measuring customers 4 Observing renewal and churn PART 2 - WAGING THE WAR 5 Understanding churn and behavior with metrics 6 Relationships between customer behaviors 7 Segmenting customers with advanced metrics PART 3 - SPECIAL WEAPONS AND TACTICS 8 Forecasting churn 9 Forecast accuracy and machine learning 10 Churn demographics and firmographics 11 Leading the fight against churn |
| customer churn analysis in banking industry: Industrial Engineering in the Internet-of-Things World Fethi Calisir, 2021-08-07 This book gathers extended versions of the best papers presented at the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE), organized virtually on August 14–15, 2020, by Istanbul Technical University. It covers a wide range of topics, including decision analysis, supply chain management, systems modelling and quality control. Further, special emphasis is placed on cutting-edge applications of industrial Internet-of-Things. Technological, economic and business challenges are discussed in detail, presenting effective strategies that can be used to modernize current structures, eliminating the barriers that are keeping industries from taking full advantage of IoT technologies. The book offers an important link between technological research and industry best practices, and covers various disciplinary areas such as manufacturing, healthcare and service engineering, among others. |
| customer churn analysis in banking industry: Proceedings of Second International Conference on Advances in Computer Engineering and Communication Systems A. Brahmananda Reddy, B.V. Kiranmayee, Raghava Rao Mukkamala, K. Srujan Raju, 2022-02-22 This book includes original, peer-reviewed research articles from International Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2021), held in VNR Vignana Jyoythi Institute of Engineering and Technology (VNR VJIET), Hyderabad, Telangana, India, during 13–14 August 2021. The book focuses on “Smart Innovations in Mezzanine Technologies, Data Analytics, Networks and Communication Systems” enlargements and reviews on the advanced topics in artificial intelligence, machine learning, data mining and big data computing, knowledge engineering, semantic Web, cloud computing, Internet on Things, cybersecurity, communication systems, and distributed computing and smart systems. |
| customer churn analysis in banking industry: Engineering Applications of Neural Networks John Macintyre, Lazaros Iliadis, Ilias Maglogiannis, Chrisina Jayne, 2019-05-14 This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN 2019, held in Xersonisos, Crete, Greece, in May 2019. The 35 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on AI in energy management - industrial applications; biomedical - bioinformatics modeling; classification - learning; deep learning; deep learning - convolutional ANN; fuzzy - vulnerability - navigation modeling; machine learning modeling - optimization; ML - DL financial modeling; security - anomaly detection; 1st PEINT workshop. |
| customer churn analysis in banking industry: Data Mining: Concepts and Techniques Jiawei Han, Micheline Kamber, Jian Pei, 2011-06-09 Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data |
| customer churn analysis in banking industry: Predictive Analytics Eric Siegel, 2016-01-12 Mesmerizing & fascinating... —The Seattle Post-Intelligencer The Freakonomics of big data. —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a |
| customer churn analysis in banking industry: Big Data Analytics Kiran Chaudhary, Mansaf Alam, 2021-12-27 Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including: Big data analytics and algorithm Market basket analysis Anticipating consumer purchase behavior Variation in shopping patterns Big data analytics for market intelligence The third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics. |
| customer churn analysis in banking industry: Database Marketing Robert C. Blattberg, Byung-Do Kim, Scott A. Neslin, 2010-02-26 Database marketing is at the crossroads of technology, business strategy, and customer relationship management. Enabled by sophisticated information and communication systems, today’s organizations have the capacity to analyze customer data to inform and enhance every facet of the enterprise—from branding and promotion campaigns to supply chain management to employee training to new product development. Based on decades of collective research, teaching, and application in the field, the authors present the most comprehensive treatment to date of database marketing, integrating theory and practice. Presenting rigorous models, methodologies, and techniques (including data collection, field testing, and predictive modeling), and illustrating them through dozens of examples, the authors cover the full spectrum of principles and topics related to database marketing. This is an excellent in-depth overview of both well-known and very recent topics in customer management models. It is an absolute must for marketers who want to enrich their knowledge on customer analytics. (Peter C. Verhoef, Professor of Marketing, Faculty of Economics and Business, University of Groningen) A marvelous combination of relevance and sophisticated yet understandable analytical material. It should be a standard reference in the area for many years. (Don Lehmann, George E. Warren Professor of Business, Columbia Business School) The title tells a lot about the book's approach—though the cover reads, database, the content is mostly about customers and that's where the real-world action is. Most enjoyable is the comprehensive story – in case after case – which clearly explains what the analysis and concepts really mean. This is an essential read for those interested in database marketing, customer relationship management and customer optimization. (Richard Hochhauser, President and CEO, Harte-Hanks, Inc.) In this tour de force of careful scholarship, the authors canvass the ever expanding literature on database marketing. This book will become an invaluable reference or text for anyone practicing, researching, teaching or studying the subject. (Edward C. Malthouse, Theodore R. and Annie Laurie Sills Associate Professor of Integrated Marketing Communications, Northwestern University) |
| customer churn analysis in banking industry: Business Analytics for Professionals Alp Ustundag, Emre Cevikcan, Omer Faruk Beyca, 2022-05-09 This book explains concepts and techniques for business analytics and demonstrate them on real life applications for managers and practitioners. It illustrates how machine learning and optimization techniques can be used to implement intelligent business automation systems. The book examines business problems concerning supply chain, marketing & CRM, financial, manufacturing and human resources functions and supplies solutions in Python. |
| customer churn analysis in banking industry: Data Management, Analytics and Innovation Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Jan Martinovic, 2020-09-18 This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17–19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. |
| customer churn analysis in banking industry: Hands-On Data Science for Marketing Yoon Hyup Hwang, 2019-03-29 Optimize your marketing strategies through analytics and machine learning Key FeaturesUnderstand how data science drives successful marketing campaignsUse machine learning for better customer engagement, retention, and product recommendationsExtract insights from your data to optimize marketing strategies and increase profitabilityBook Description Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies. This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R. By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business. What you will learnLearn how to compute and visualize marketing KPIs in Python and RMaster what drives successful marketing campaigns with data scienceUse machine learning to predict customer engagement and lifetime valueMake product recommendations that customers are most likely to buyLearn how to use A/B testing for better marketing decision makingImplement machine learning to understand different customer segmentsWho this book is for If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-advanced data science concepts and applications in marketing with real-life examples. |
| customer churn analysis in banking industry: Applications of Data Management and Analysis Mohammad Moshirpour, Behrouz H. Far, Reda Alhajj, 2018-10-04 This book addresses and examines the impacts of applications and services for data management and analysis, such as infrastructure, platforms, software, and business processes, on both academia and industry. The chapters cover effective approaches in dealing with the inherent complexity and increasing demands of big data management from an applications perspective. Various case studies included have been reported by data analysis experts who work closely with their clients in such fields as education, banking, and telecommunications. Understanding how data management has been adapted to these applications will help students, instructors and professionals in the field. Application areas also include the fields of social network analysis, bioinformatics, and the oil and gas industries. |
| customer churn analysis in banking industry: Neural Networks in Business Kate A. Smith, Jatinder N. D. Gupta, 2003-01-01 For professionals, students, and academics interested in applying neural networks to a variety of business applications, this reference book introduces the three most common neural network models and how they work. A wide range of business applications and a series of global case studies are presented to illustrate the neural network models provided. Each model or technique is discussed in detail and used to solve a business problem such as managing direct marketing, calculating foreign exchange rates, and improving cash flow forecasting. |
| customer churn analysis in banking industry: Proceedings of International Conference on Information Technology and Applications Sajid Anwar, Abrar Ullah, Álvaro Rocha, Maria José Sousa, 2023-05-18 This book includes high-quality papers presented at 16th International Conference on Information Technology and Applications (ICITA 2022), held in Lisbon, Portugal during October 20–22, 2022. The book presents original research work of academics and industry professionals to exchange their knowledge of the state-of-the-art research and development in information technology and applications. The topics covered in the book are cloud computing, business process engineering, machine learning, evolutionary computing, big data analytics, Internet of things and cyber-physical systems, information and knowledge management, computer vision and image processing, computer graphics and games programming, mobile computing, ontology engineering, software and systems modeling, human–computer interaction, online learning / e-learning, computer networks, and web engineering. |
| customer churn analysis in banking industry: Data Mining for Business Applications Carlos A. Mota Soares, Rayid Ghani, 2010 Data mining is already incorporated into the business processes in sectors such as health, retail, automotive, finance, telecom and insurance as well as in government. This book contains extended versions of a selection of papers presented at a series of workshops held between 2005 and 2008 on the subject of data mining for business applications. |
| customer churn analysis in banking industry: Honest Signals Alex Pentland, 2010-09-24 How understanding the signaling within social networks can change the way we make decisions, work with others, and manage organizations. How can you know when someone is bluffing? Paying attention? Genuinely interested? The answer, writes Alex Pentland in Honest Signals, is that subtle patterns in how we interact with other people reveal our attitudes toward them. These unconscious social signals are not just a back channel or a complement to our conscious language; they form a separate communication network. Biologically based “honest signaling,” evolved from ancient primate signaling mechanisms, offers an unmatched window into our intentions, goals, and values. If we understand this ancient channel of communication, Pentland claims, we can accurately predict the outcomes of situations ranging from job interviews to first dates. Pentland, an MIT professor, has used a specially designed digital sensor worn like an ID badge—a “sociometer”—to monitor and analyze the back-and-forth patterns of signaling among groups of people. He and his researchers found that this second channel of communication, revolving not around words but around social relations, profoundly influences major decisions in our lives—even though we are largely unaware of it. Pentland presents the scientific background necessary for understanding this form of communication, applies it to examples of group behavior in real organizations, and shows how by “reading” our social networks we can become more successful at pitching an idea, getting a job, or closing a deal. Using this “network intelligence” theory of social signaling, Pentland describes how we can harness the intelligence of our social network to become better managers, workers, and communicators. |
| customer churn analysis in banking industry: Stability Analysis of Neural Networks Grienggrai Rajchakit, Praveen Agarwal, Sriraman Ramalingam, 2021-12-05 This book discusses recent research on the stability of various neural networks with constrained signals. It investigates stability problems for delayed dynamical systems where the main purpose of the research is to reduce the conservativeness of the stability criteria. The book mainly focuses on the qualitative stability analysis of continuous-time as well as discrete-time neural networks with delays by presenting the theoretical development and real-life applications in these research areas. The discussed stability concept is in the sense of Lyapunov, and, naturally, the proof method is based on the Lyapunov stability theory. The present book will serve as a guide to enable the reader in pursuing the study of further topics in greater depth and is a valuable reference for young researcher and scientists. |
| customer churn analysis in banking industry: Proceeding of Fifth International Conference on Microelectronics, Computing and Communication Systems Vijay Nath, J. K. Mandal, 2021-09-09 This book presents high-quality papers from the Fifth International Conference on Microelectronics, Computing & Communication Systems (MCCS 2020). It discusses the latest technological trends and advances in MEMS and nanoelectronics, wireless communication, optical communication, instrumentation, signal processing, image processing, bioengineering, green energy, hybrid vehicles, environmental science, weather forecasting, cloud computing, renewable energy, RFID, CMOS sensors, actuators, transducers, telemetry systems, embedded systems and sensor network applications. It includes papers based on original theoretical, practical and experimental simulations, development, applications, measurements and testing. The applications and solutions discussed here provide excellent reference material for future product development. |
| customer churn analysis in banking industry: Sales Engagement Manny Medina, Max Altschuler, Mark Kosoglow, 2019-03-12 Engage in sales—the modern way Sales Engagement is how you engage and interact with your potential buyer to create connection, grab attention, and generate enough interest to create a buying opportunity. Sales Engagement details the modern way to build the top of the funnel and generate qualified leads for B2B companies. This book explores why a Sales Engagement strategy is so important, and walks you through the modern sales process to ensure you’re effectively connecting with customers every step of the way. • Find common factors holding your sales back—and reverse them through channel optimization • Humanize sales with personas and relevant information at every turn • Understand why A/B testing is so incredibly critical to success, and how to do it right • Take your sales process to the next level with a rock solid, modern Sales Engagement strategy This book is essential reading for anyone interested in up-leveling their game and doing more than they ever thought possible. |
| customer churn analysis in banking industry: Advances in Machine Learning and Computational Intelligence Srikanta Patnaik, Xin-She Yang, Ishwar K. Sethi, 2020-07-25 This book gathers selected high-quality papers presented at the International Conference on Machine Learning and Computational Intelligence (ICMLCI-2019), jointly organized by Kunming University of Science and Technology and the Interscience Research Network, Bhubaneswar, India, from April 6 to 7, 2019. Addressing virtually all aspects of intelligent systems, soft computing and machine learning, the topics covered include: prediction; data mining; information retrieval; game playing; robotics; learning methods; pattern visualization; automated knowledge acquisition; fuzzy, stochastic and probabilistic computing; neural computing; big data; social networks and applications of soft computing in various areas. |
| customer churn analysis in banking industry: MSIEID 2022 Haocun Wu, Zhisheng Wang, Sikandar Ali Qalati, 2023-03-14 The Management Science Informatization and Economic Innovation Development Conference is a leading conference held annually. It aims at building an academic platform for the communication and academic exchange among participants from various fields related to management science informatization and economic innovation development. Here, scholars, experts, and researchers are welcomed to share their research progress and inspirations. It is a great opportunity to promote academic communication and collaboration worldwide. This volume contains the papers presented at the 4th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2022), held during December 9th-11th, 2022 in Chongqing, China (virtual event). For the safety concern of all participants under nowadays situation, we decided to hold it as a virtual conference which is also effective and convenient for academic exchange and communication. Everyone interested in these fields were welcomed to join the online conference and to give comments and raise questions to the speeches and presentations. |
| customer churn analysis in banking industry: Where Are the Customers' Yachts? Fred Schwed, Jr., 2006-01-10 Once I picked it up I did not put it down until I finished. . . . What Schwed has done is capture fully-in deceptively clean language-the lunacy at the heart of the investment business. -- From the Foreword by Michael Lewis, Bestselling author of Liar's Poker . . . one of the funniest books ever written about Wall Street. -- Jane Bryant Quinn, The Washington Post How great to have a reissue of a hilarious classic that proves the more things change the more they stay the same. Only the names have been changed to protect the innocent. -- Michael Bloomberg It's amazing how well Schwed's book is holding up after fifty-five years. About the only thing that's changed on Wall Street is that computers have replaced pencils and graph paper. Otherwise, the basics are the same. The investor's need to believe somebody is matched by the financial advisor's need to make a nice living. If one of them has to be disappointed, it's bound to be the former. -- John Rothchild, Author, A Fool and His Money, Financial Columnist, Time magazine Humorous and entertaining, this book exposes the folly and hypocrisy of Wall Street. The title refers to a story about a visitor to New York who admired the yachts of the bankers and brokers. Naively, he asked where all the customers' yachts were? Of course, none of the customers could afford yachts, even though they dutifully followed the advice of their bankers and brokers. Full of wise contrarian advice and offering a true look at the world of investing, in which brokers get rich while their customers go broke, this book continues to open the eyes of investors to the reality of Wall Street. |
| customer churn analysis in banking industry: Aesthetic Intelligence Pauline Brown, 2019-11-26 Longtime leader in the luxury goods sector and former Chairman of LVMH Moët Hennessy Louis Vuitton North America reinvents the art and science of brand-building under the rubric of Aesthetic Intelligence. In a world in which people have cheap and easy access to most goods and services, yet crave richer and more meaningful experiences, aesthetics has become a key differentiator for most companies and a critical factor of their success and even their survival. In this groundbreaking book, Pauline Brown, a former leader of the world’s top luxury goods company and a pioneer in identifying the role of aesthetics in business, shows executives, entrepreneurs, and other professionals how to harness the power of the senses to create products, services, and experiences that stand out, resonate with their customers, and create long-term value for their businesses. The power is rooted in Aesthetic Intelligence—or “the other AI,” as Brown refers to it. Aesthetic Intelligence can be learned. Indeed, people are born with far more capacity than they use, but even those that are naturally gifted must continue to refine their skills, lest their aesthetic advantage atrophy. Through a combination of storytelling and practical advice, the author shows how aesthetic intelligence creates business value and how executives, entrepreneurs and others can boost their own AI and successfully apply it to business. Brown offers research, strategies and practical exercises focused on four essential AI skills. Aesthetic Intelligence provides a crucial roadmap to help business leaders build their businesses in their own authentic and distinctive way. Aesthetic Intelligence is about creating delight, lifting the human spirit, and rousing the imagination through sensorial experiences. |
| customer churn analysis in banking industry: Computer Engineering: Concepts, Methodologies, Tools and Applications Management Association, Information Resources, 2011-12-31 This reference is a broad, multi-volume collection of the best recent works published under the umbrella of computer engineering, including perspectives on the fundamental aspects, tools and technologies, methods and design, applications, managerial impact, social/behavioral perspectives, critical issues, and emerging trends in the field--Provided by publisher. |
| customer churn analysis in banking industry: Advances in Information Communication Technology and Computing Vishal Goar, |
| customer churn analysis in banking industry: Information and Communication Technology for Intelligent Systems Tomonobu Senjyu, Parikshit N. Mahalle, Thinagaran Perumal, Amit Joshi, 2020-10-29 This book gathers papers addressing state-of-the-art research in all areas of information and communication technologies and their applications in intelligent computing, cloud storage, data mining and software analysis. It presents the outcomes of the Fourth International Conference on Information and Communication Technology for Intelligent Systems, which was held in Ahmedabad, India. Divided into two volumes, the book discusses the fundamentals of various data analysis techniques and algorithms, making it a valuable resource for researchers and practitioners alike. |
| customer churn analysis in banking industry: Signals, Machines and Automation Asha Rani, Bhavnesh Kumar, Vivek Shrivastava, Ramesh C. Bansal, 2023-05-22 This book constitutes selected peer-reviewed proceedings of the 2nd International Conference on Signals, machines, and Automation (SIGMA 2022). This book includes papers on technologies related to electric power, manufacturing processes & automation, biomedical & healthcare, communication & networking, image processing, and computation intelligence. The book will serve as a valuable reference resource for beginners as well as advanced researchers in the areas of engineering & technology. |
| customer churn analysis in banking industry: Proceedings of Data Analytics and Management Abhishek Swaroop, Zdzislaw Polkowski, Sérgio Duarte Correia, Bal Virdee, 2024-01-13 This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes. |
| customer churn analysis in banking industry: Database Systems for Advanced Applications Jian Pei, Yannis Manolopoulos, Shazia Sadiq, Jianxin Li, 2018-05-11 This two-volume set LNCS 10827 and LNCS 10828 constitutes the refereed proceedings of the 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, held in Gold Coast, QLD, Australia, in May 2018. The 83 full papers, 21 short papers, 6 industry papers, and 8 demo papers were carefully selected from a total of 360 submissions. The papers are organized around the following topics: network embedding; recommendation; graph and network processing; social network analytics; sequence and temporal data processing; trajectory and streaming data; RDF and knowledge graphs; text and data mining; medical data mining; security and privacy; search and information retrieval; query processing and optimizations; data quality and crowdsourcing; learning models; multimedia data processing; and distributed computing. |
Comparative Analysis of Machine Learning Models for …
Customer churn poses a significant challenge for the banking and finance industry in the United States, directly affecting profitability and market share. This study conducts a comprehensive …
Customer Churn Prediction to Enhance Customer Retention …
for customer churn prediction in the banking industry. Given that the performance evaluation was conducted using a static dataset, the study recommends extending future research by testing …
Customer Churn Analysis in Banking Sector
Using SVM, bank customer churn prediction is developed among data mining techniques, because it is widely used binary classification technique and performs good classification …
Bank Customer Churn Prediction - ijrar.org
machine learning framework for the objective of customer churn prediction in the banking industry. Through being able to single out customers who are likely to churn, the banks are then able to …
Analysis And Prediction Of Customer Churn Using Machine …
Analysis And Prediction Of Customer Churn Using Machine Learning - A Case Study In The Banking Sector. Customer turnover is a global issue that has an impact on the banking …
A COMPREHENSIVE SURVEY OF CUSTOMER CHURN IN …
The primary objective of this study is to offer a thorough analysis of the present condition of churn prediction and emphasise approaches to advance the subject in order to enhance customer …
Investigating Customer Churn in Banking: A Machine Learning …
Customer attrition, also known as customer churn, is the phenome-non where customers terminate their relationship with a business or organization. In the context of banking, customer …
Churn Prediction Modelling Using Regression Techniques
In this particular project, we utilize customer data from a banking institution to construct a predictive model that can determine the likelihood of client churn. Our main objective is to …
Customer Churn Analysis and Prediction Using Data Mining …
Customer Churn - In the definition of banking, a churn customer can be defined as the person who closes all of his accounts and stops doing business with the bank. Churn customers not only …
Prediction of Customer Churn in Banking Industry - arXiv.org
This study compares the performance of six supervised classification techniques to suggest an efficient model to predict customer churn in banking industry, given 10 demographic and …
CUSTOMER RETENTION AND CHURN PREDICTION …
The methodology for customer churn analysis in banking encompasses several key steps.Firstly, it's crucial to establish a clear definition of churn, whether it's account …
Customer Churn Prediction Model Using Artificial Neural …
In comparison to the logistic regression model outcomes, ANN models are more effective for predicting customer churn in the banking industry. The study suggests vital perceptions of how …
Customer Churn Prediction in the Banking Sector Using …
Apr 2, 2025 · analysis of model outputs revealed several salient predictors of customer attrition, such as anomalous transaction behavior, prolonged inactivity, and indicators of dissatisfaction …
Customer Churn Prediction in the Banking Sector Using
In this study, we use different machine learning models such as k-means cluster-ing to segment customers, k-nearest neighbors, logistic regression, decision tree, random forest, and support...
Prediction of bank credit customers churn based on machine …
show that the complete customer churn prediction model using Extreme Gradient Boosting (XGBoost) achieved significant performance, with accuracy, precision, recall, F1 score, and …
Bank Customer Churn Analysis and Prediction - EUDL
Sep 12, 2022 · preventing customer churn is critical to the long-term viability of commercial banks. In recent decades customer churn has become increasingly vital for industries like telecom, e …
Bank Customer Churn Prediction Using Machine Learning …
Using real customer data from a large community bank in the South of the US, this paper analyzes the customer churn prediction problem by constructing and comparing ten machine …
BANK CUSTOMER CHURN PREDICTION USING MACHINE …
predicting customer churn. The project will illuminate the challenges and opportunities inherent in predicting bank customer churn, with a focus on the potential of machine learning to enhance …
Customer Churn Prediction in Banking Industry Using Power …
In this paper, we investigate the determining factor for customer attrition in the bank-ing sector using Power BI. Our study, using the machine learning technique, aims to provide the...
Customer Churn Prediction Using a New Criterion and Data …
In this paper, in order to measure the customer churn rate in the Iranian banks, a new approach is introduced. First, using data preparation, the data is normalized. Then, using k-a medoids …
Comparative Analysis of Machine Learning Models for …
Customer churn poses a significant challenge for the banking and finance industry in the United States, directly affecting profitability and market share. This study conducts a comprehensive …
Customer Churn Prediction to Enhance Customer Retention …
for customer churn prediction in the banking industry. Given that the performance evaluation was conducted using a static dataset, the study recommends extending future research by testing …
Customer Churn Analysis in Banking Sector
Using SVM, bank customer churn prediction is developed among data mining techniques, because it is widely used binary classification technique and performs good classification …
Bank Customer Churn Prediction - ijrar.org
machine learning framework for the objective of customer churn prediction in the banking industry. Through being able to single out customers who are likely to churn, the banks are then able to …
Analysis And Prediction Of Customer Churn Using Machine …
Analysis And Prediction Of Customer Churn Using Machine Learning - A Case Study In The Banking Sector. Customer turnover is a global issue that has an impact on the banking …
A COMPREHENSIVE SURVEY OF CUSTOMER CHURN IN …
The primary objective of this study is to offer a thorough analysis of the present condition of churn prediction and emphasise approaches to advance the subject in order to enhance customer …
Investigating Customer Churn in Banking: A Machine …
Customer attrition, also known as customer churn, is the phenome-non where customers terminate their relationship with a business or organization. In the context of banking, …
Churn Prediction Modelling Using Regression Techniques
In this particular project, we utilize customer data from a banking institution to construct a predictive model that can determine the likelihood of client churn. Our main objective is to …
Customer Churn Analysis and Prediction Using Data Mining …
Customer Churn - In the definition of banking, a churn customer can be defined as the person who closes all of his accounts and stops doing business with the bank. Churn customers not only …
Prediction of Customer Churn in Banking Industry - arXiv.org
This study compares the performance of six supervised classification techniques to suggest an efficient model to predict customer churn in banking industry, given 10 demographic and …
CUSTOMER RETENTION AND CHURN PREDICTION …
The methodology for customer churn analysis in banking encompasses several key steps.Firstly, it's crucial to establish a clear definition of churn, whether it's account …
Customer Churn Prediction Model Using Artificial Neural …
In comparison to the logistic regression model outcomes, ANN models are more effective for predicting customer churn in the banking industry. The study suggests vital perceptions of how …
Customer Churn Prediction in the Banking Sector Using …
Apr 2, 2025 · analysis of model outputs revealed several salient predictors of customer attrition, such as anomalous transaction behavior, prolonged inactivity, and indicators of dissatisfaction …
Customer Churn Prediction in the Banking Sector Using
In this study, we use different machine learning models such as k-means cluster-ing to segment customers, k-nearest neighbors, logistic regression, decision tree, random forest, and support...
Prediction of bank credit customers churn based on machine …
show that the complete customer churn prediction model using Extreme Gradient Boosting (XGBoost) achieved significant performance, with accuracy, precision, recall, F1 score, and …
Bank Customer Churn Analysis and Prediction - EUDL
Sep 12, 2022 · preventing customer churn is critical to the long-term viability of commercial banks. In recent decades customer churn has become increasingly vital for industries like telecom, e …
Bank Customer Churn Prediction Using Machine Learning …
Using real customer data from a large community bank in the South of the US, this paper analyzes the customer churn prediction problem by constructing and comparing ten machine …
BANK CUSTOMER CHURN PREDICTION USING …
predicting customer churn. The project will illuminate the challenges and opportunities inherent in predicting bank customer churn, with a focus on the potential of machine learning to enhance …
Customer Churn Prediction in Banking Industry Using Power …
In this paper, we investigate the determining factor for customer attrition in the bank-ing sector using Power BI. Our study, using the machine learning technique, aims to provide the...
Customer Churn Prediction Using a New Criterion and Data …
In this paper, in order to measure the customer churn rate in the Iranian banks, a new approach is introduced. First, using data preparation, the data is normalized. Then, using k-a medoids …
