Fraud Analytics Using Descriptive Predictive And Social Network Techniques
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Fraud Analytics Using Descriptive Predictive And Social Network Techniques
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Author : Bart Baesens
language : en
Publisher: John Wiley & Sons
Release Date : 2015-08-17
Fraud Analytics Using Descriptive Predictive And Social Network Techniques written by Bart Baesens 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 2015-08-17 with Computers categories.
Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.
Profit Driven Business Analytics
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Author : Wouter Verbeke
language : en
Publisher: John Wiley & Sons
Release Date : 2017-09-26
Profit Driven Business Analytics written by Wouter Verbeke 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 2017-09-26 with Business & Economics categories.
Maximize profit and optimize decisions with advanced business analytics Profit-Driven Business Analytics provides actionable guidance on optimizing the use of data to add value and drive better business. Combining theoretical and technical insights into daily operations and long-term strategy, this book acts as a development manual for practitioners seeking to conceive, develop, and manage advanced analytical models. Detailed discussion delves into the wide range of analytical approaches and modeling techniques that can help maximize business payoff, and the author team draws upon their recent research to share deep insight about optimal strategy. Real-life case studies and examples illustrate these techniques at work, and provide clear guidance for implementation in your own organization. From step-by-step instruction on data handling, to analytical fine-tuning, to evaluating results, this guide provides invaluable guidance for practitioners seeking to reap the advantages of true business analytics. Despite widespread discussion surrounding the value of data in decision making, few businesses have adopted advanced analytic techniques in any meaningful way. This book shows you how to delve deeper into the data and discover what it can do for your business. Reinforce basic analytics to maximize profits Adopt the tools and techniques of successful integration Implement more advanced analytics with a value-centric approach Fine-tune analytical information to optimize business decisions Both data stored and streamed has been increasing at an exponential rate, and failing to use it to the fullest advantage equates to leaving money on the table. From bolstering current efforts to implementing a full-scale analytics initiative, the vast majority of businesses will see greater profit by applying advanced methods. Profit-Driven Business Analytics provides a practical guidebook and reference for adopting real business analytics techniques.
Database And Expert Systems Applications
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Author : Gabriele Anderst-Kotsis
language : en
Publisher: Springer
Release Date : 2019-08-19
Database And Expert Systems Applications written by Gabriele Anderst-Kotsis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-19 with Computers categories.
This volume constitutes the refereed proceedings of the four workshops held at the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019: The 10th International Workshop on Biological Knowledge Discovery from Data, BIOKDD 2019, the 3rd International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2019, the 1st International Workshop on Machine Learning and Knowledge Graphs, MLKgraphs2019, and the 16th International Workshop on Technologies for Information Retrieval, TIR 2019. The 26 selected papers discuss a range of topics including: knowledge discovery, biological data, cyber security, cyber-physical system, machine learning, knowledge graphs, information retriever, data base, and artificial intelligent.
Cognitive Computing For Big Data Systems Over Iot
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Author : Arun Kumar Sangaiah
language : en
Publisher: Springer
Release Date : 2017-12-30
Cognitive Computing For Big Data Systems Over Iot written by Arun Kumar Sangaiah and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-30 with Technology & Engineering categories.
This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT). It explores domain knowledge, data science reasoning and cognitive methods in the context of the IoT, extending current data science approaches by incorporating insights from experts as well as a notion of artificial intelligence, and performing inferences on the knowledge The book provides a comprehensive overview of the constituent paradigms underlying cognitive computing methods, which illustrate the increased focus on big data in IoT problems as they evolve. It includes novel, in-depth fundamental research contributions from a methodological/application in data science accomplishing sustainable solution for the future perspective. Mainly focusing on the design of the best cognitive embedded data science technologies to process and analyze the large amount of data collected through the IoT, and aid better decision making, the book discusses adapting decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and IoT problems can be handled in practice. This book is a valuable resource for scientists, professionals, researchers, and academicians dealing with the new challenges and advances in the specific areas of cognitive computing and data science approaches.
Credit Risk Analytics
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Author : Bart Baesens
language : en
Publisher: John Wiley & Sons
Release Date : 2016-09-19
Credit Risk Analytics written by Bart Baesens 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 2016-09-19 with Business & Economics categories.
The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.
Digital Multimedia Communications
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Author : Guangtao Zhai
language : en
Publisher: Springer Nature
Release Date : 2025-04-07
Digital Multimedia Communications written by Guangtao Zhai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-07 with Computers categories.
This volume contains 27 selected papers presented at IFTC 2024: 21st International Forum of Digital Multimedia Communication, held in Lingshui, Hainan, China, on November 28-29, 2024. The 55 full papers included in this 2-volume set were carefully reviewed and selected from 146 submissions. They were organized in topical sections as follows: CCIS 2441: Affective Computing, Graphics & Image Processing for Virtual Reality, Large Language Models, Multimedia Communication, Application of Deep Learning and Video Analysis. CCIS 2442: Human and Interactive Media, Image Processing, Quality Assessment and Source Coding.
Practical Applications Of Data Processing Algorithms And Modeling
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Author : Whig, Pawan
language : en
Publisher: IGI Global
Release Date : 2024-04-29
Practical Applications Of Data Processing Algorithms And Modeling written by Whig, Pawan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-29 with Computers categories.
In today's data-driven era, the persistent gap between theoretical understanding and practical implementation in data science poses a formidable challenge. As we navigate through the complexities of harnessing data, deciphering algorithms, and unleashing the potential of modeling techniques, the need for a comprehensive guide becomes increasingly evident. This is the landscape explored in Practical Applications of Data Processing, Algorithms, and Modeling. This book is a solution to the pervasive problem faced by aspiring data scientists, seasoned professionals, and anyone fascinated by the power of data-driven insights. From the web of algorithms to the strategic role of modeling in decision-making, this book is an effective resource in a landscape where data, without proper guidance, risks becoming an untapped resource. The objective of Practical Applications of Data Processing, Algorithms, and Modeling is to address the pressing issue at the heart of data science – the divide between theory and practice. This book seeks to examine the complexities of data processing techniques, algorithms, and modeling methodologies, offering a practical understanding of these concepts. By focusing on real-world applications, the book provides readers with the tools and knowledge needed to bridge the gap effectively, allowing them to apply these techniques across diverse industries and domains. In the face of constant technological advancements, the book highlights the latest trends and innovative approaches, fostering a deeper comprehension of how these technologies can be leveraged to solve complex problems. As a practical guide, it empowers readers with hands-on examples, case studies, and problem-solving scenarios, aiming to instill confidence in navigating data challenges and making informed decisions using data-driven insights.
Handbook Of Research On Big Data Storage And Visualization Techniques
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Author : Segall, Richard S.
language : en
Publisher: IGI Global
Release Date : 2018-01-05
Handbook Of Research On Big Data Storage And Visualization Techniques written by Segall, Richard S. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-05 with Computers categories.
The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.
Big Data Bigdata 2019
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Author : Keke Chen
language : en
Publisher: Springer
Release Date : 2019-06-19
Big Data Bigdata 2019 written by Keke Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-19 with Computers categories.
This volume constitutes the proceedings of the 8th International Congress on BIGDATA 2019, held as Part of SCF 2019 in San Diego, CA, USA in June 2019. The 9 full papers presented in this volume were carefully reviewed and selected from 14 submissions. They cover topics such as: Big Data Models and Algorithms; Big Data Architectures; Big Data Management; Big Data Protection, Integrity and Privacy; Security Applications of Big Data; Big Data Search and Mining; Big Data for Enterprise, Government and Society.
Artificial Intelligence Driven Transformation In Insurance Security Devops And Intelligent Advisory Systems
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Author : Balaji Adusupalli
language : en
Publisher: Deep Science Publishing
Release Date : 2025-05-07
Artificial Intelligence Driven Transformation In Insurance Security Devops And Intelligent Advisory Systems written by Balaji Adusupalli and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-07 with Computers categories.
The insurance industry is undergoing a radical transformation driven by the exponential growth of artificial intelligence (AI) and digital technologies. Once viewed as a traditional, paperwork-heavy sector, insurance is now embracing intelligent systems to streamline operations, enhance customer experiences, and manage risks more effectively. This book, AI-Driven Transformation in Insurance: Security, DevOps, and Intelligent Advisory Systems, explores the dynamic convergence of AI, cybersecurity, DevOps, and next-generation advisory platforms that are reshaping the insurance landscape. In a world increasingly defined by real-time data and digital interactions, insurance providers must adapt rapidly to stay competitive. AI is no longer a future ambition—it is a present-day imperative. From underwriting automation and fraud detection to personalized policy recommendations and predictive analytics, AI is enabling insurers to make smarter decisions faster. However, this transformation also introduces complex challenges related to data security, system integration, and regulatory compliance. This book takes a holistic view of the AI-powered insurance ecosystem. It discusses how secure DevOps practices—often referred to as DevSecOps—ensure that continuous integration and delivery pipelines are not only agile but also robust against evolving cyber threats. Additionally, it examines the rise of intelligent advisory systems that leverage natural language processing, machine learning, and contextual awareness to provide proactive and highly customized customer support. Through real-world case studies, industry insights, and a blend of technical and strategic analysis, readers will gain a deeper understanding of the tools and frameworks driving this new era of digital insurance. Whether you're a technology leader, insurance executive, data scientist, or researcher, this book offers a timely and practical guide to navigating the AI revolution in insurance. As the boundaries between technology and insurance continue to blur, the future belongs to those who can harness AI not just to automate, but to innovate. We invite you to explore the road ahead—where intelligent systems are not just supporting insurance operations, but redefining them entirely.