Download or read book Credit Card Fraud Detection by Adaptive Neural Data Mining written by Rüdiger W. Brause and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Neural Network Based Data Mining for Credit Card Fraud Detection written by Adrian Tinio and published by . This book was released on 2005 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Innovations in Neural Information Paradigms and Applications written by Monica Bianchini and published by Springer Science & Business Media. This book was released on 2009-10-16 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tremendous advances in all disciplines including engineering, science, health care, business, avionics, management, and so on, can also be attributed to the development of artificial intelligence paradigms. In fact, researchers are always interested in desi- ing machines which can mimic the human behaviour in a limited way. Therefore, the study of neural information processing paradigms have generated great interest among researchers, in that machine learning, borrowing features from human intelligence and applying them as algorithms in a computer friendly way, involves not only Mathem- ics and Computer Science but also Biology, Psychology, Cognition and Philosophy (among many other disciplines). Generally speaking, computers are fundamentally well-suited for performing au- matic computations, based on fixed, programmed rules, i.e. in facing efficiently and reliably monotonous tasks, often extremely time-consuming from a human point of view. Nevertheless, unlike humans, computers have troubles in understanding specific situations, and adapting to new working environments. Artificial intelligence and, in particular, machine learning techniques aim at improving computers behaviour in tackling such complex tasks. On the other hand, humans have an interesting approach to problem-solving, based on abstract thought, high-level deliberative reasoning and pattern recognition. Artificial intelligence can help us understanding this process by recreating it, then potentially enabling us to enhance it beyond our current capabilities.
Download or read book Data mining techniques in financial fraud detection written by Rohan Ahmed and published by GRIN Verlag. This book was released on 2018-05-24 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2016 in the subject Computer Science - General, grade: 1.7, Heilbronn University, language: English, abstract: In this seminar thesis you will get a view about the Data Mining techniques in financial fraud detection. Financial Fraud is taking a big issue in economical problem, which is still growing. So there is a big interest to detect fraud, but by large amounts of data, this is difficult. Therefore, many data mining techniques are repeatedly used to detect frauds in fraudulent activities. Majority of fraud area are Insurance, Banking, Health and Financial Statement Fraud. The most widely used data mining techniques are Support Vector Machines (SVM), Decision Trees (DT), Logistic Regression (LR), Naives Bayes, Bayesian Belief Network, Classification and Regression Tree (CART) etc. These techniques existed for many years and are used repeatedly to develop a fraud detection system or for analyze frauds.
Download or read book Review on Credit Card Fraud Detection Using Data Mining Classification Techniques Machine Learning Algorithms written by Rahul Goyal and published by . This book was released on 2020 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining (DM) involves a core algorithm that enables data deeper than basic insights and knowledge. In fact, data mining is more part of knowledge discovery process. Credit card (CC) providers provide multiple cards to their customers. All credit card users must be genuine and sincere. Giving a card to any kind of mistake can lead to a financial crisis. Due to the rapid growth in cashless transactions, it is unlikely, Fake transactions can also be increased. A fraudulent transaction can be identified by studying credit cards of various behaviors as a previous transaction history data set. If there is any deviation from the available cost pattern, it is a bogus transaction. DM & machine learning techniques (MLT) are widely applied in credit card fraud detection (CCFD). In this survey paper we show an indication of various widely available DM & MLT for detecting credit card fraud.
Download or read book Innovations in Neural Information Paradigms and Applications written by Monica Bianchini and published by Springer. This book was released on 2009-10-13 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tremendous advances in all disciplines including engineering, science, health care, business, avionics, management, and so on, can also be attributed to the development of artificial intelligence paradigms. In fact, researchers are always interested in desi- ing machines which can mimic the human behaviour in a limited way. Therefore, the study of neural information processing paradigms have generated great interest among researchers, in that machine learning, borrowing features from human intelligence and applying them as algorithms in a computer friendly way, involves not only Mathem- ics and Computer Science but also Biology, Psychology, Cognition and Philosophy (among many other disciplines). Generally speaking, computers are fundamentally well-suited for performing au- matic computations, based on fixed, programmed rules, i.e. in facing efficiently and reliably monotonous tasks, often extremely time-consuming from a human point of view. Nevertheless, unlike humans, computers have troubles in understanding specific situations, and adapting to new working environments. Artificial intelligence and, in particular, machine learning techniques aim at improving computers behaviour in tackling such complex tasks. On the other hand, humans have an interesting approach to problem-solving, based on abstract thought, high-level deliberative reasoning and pattern recognition. Artificial intelligence can help us understanding this process by recreating it, then potentially enabling us to enhance it beyond our current capabilities.
Download or read book Heuristics in Analytics written by Carlos Andre Reis Pinheiro and published by John Wiley & Sons. This book was released on 2014-03-03 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Employ heuristic adjustments for truly accurate analysis Heuristics in Analytics presents an approach to analysis that accounts for the randomness of business and the competitive marketplace, creating a model that more accurately reflects the scenario at hand. With an emphasis on the importance of proper analytical tools, the book describes the analytical process from exploratory analysis through model developments, to deployments and possible outcomes. Beginning with an introduction to heuristic concepts, readers will find heuristics applied to statistics and probability, mathematics, stochastic, and artificial intelligence models, ending with the knowledge applications that solve business problems. Case studies illustrate the everyday application and implication of the techniques presented, while the heuristic approach is integrated into analytical modeling, graph analysis, text analytics, and more. Robust analytics has become crucial in the corporate environment, and randomness plays an enormous role in business and the competitive marketplace. Failing to account for randomness can steer a model in an entirely wrong direction, negatively affecting the final outcome and potentially devastating the bottom line. Heuristics in Analytics describes how the heuristic characteristics of analysis can be overcome with problem design, math and statistics, helping readers to: Realize just how random the world is, and how unplanned events can affect analysis Integrate heuristic and analytical approaches to modeling and problem solving Discover how graph analysis is applied in real-world scenarios around the globe Apply analytical knowledge to customer behavior, insolvency prevention, fraud detection, and more Understand how text analytics can be applied to increase the business knowledge Every single factor, no matter how large or how small, must be taken into account when modeling a scenario or event—even the unknowns. The presence or absence of even a single detail can dramatically alter eventual outcomes. From raw data to final report, Heuristics in Analytics contains the information analysts need to improve accuracy, and ultimately, predictive, and descriptive power.
Download or read book Advances in Fire and Process Safety written by N. A. Siddiqui and published by Springer. This book was released on 2018-01-08 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the International Conference on Health, Safety, Fire, Environment, and Allied Sciences (HSFEA 2016). The book highlights the latest developments in the field of science and technology aimed at improving health and safety in the workplace. The volume comprises content from leading scientists, engineers, and policy makers. The papers included in this volume look at identifying the limitations of the existing approaches and open new avenues for future research. The book also looks at the accident and work-health records, specifically in Asian countries, and discusses measures to improve the Asian standards and implementation issues with regards to workplace health and safety. The contents of this volume will be of interest to researchers, practitioners, and policy makers alike.
Download or read book Red Wired written by Shermon So and published by Marshall Cavendish International Asia Pte Ltd. This book was released on 2010-01-28 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: China now contains over 250 million Internet users, the largest in the world, and growing. Fortunes have been made, but more importantly, society and business are being transformed along the unique lines of Chinese Internet development. This will substantially affect the business and political character of the fastest growing economic power in the world. Red Wired takes a fascinating inside look at how China has adopted the Internet at rapid pace. Through unique access to the key players in China’s Internet revolution, the authors offer a new perspective on the growth of this superpower and the role that technology has played. Moreover, they offer business lessons from Internet companies which succeeded in this most complex and unique of markets.
Download or read book Real time Fraud Detection Analytics on IBM System z written by Mike Ebbers and published by IBM Redbooks. This book was released on 2013-04-11 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: Payment fraud can be defined as an intentional deception or misrepresentation that is designed to result in an unauthorized benefit. Fraud schemes are becoming more complex and difficult to identify. It is estimated that industries lose nearly $1 trillion USD annually because of fraud. The ideal solution is where you avoid making fraudulent payments without slowing down legitimate payments. This solution requires that you adopt a comprehensive fraud business architecture that applies predictive analytics. This IBM® Redbooks® publication begins with the business process flows of several industries, such as banking, property/casualty insurance, and tax revenue, where payment fraud is a significant problem. This book then shows how to incorporate technological advancements that help you move from a post-payment to pre-payment fraud detection architecture. Subsequent chapters describe a solution that is specific to the banking industry that can be easily extrapolated to other industries. This book describes the benefits of doing fraud detection on IBM System z®. This book is intended for financial decisionmakers, consultants, and architects, in addition to IT administrators.
Download or read book Fraud Detection in White Collar Crime written by Rohan Ahmed and published by GRIN Verlag. This book was released on 2018-06-28 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bachelor Thesis from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1.3, Heilbronn University, language: English, abstract: White-collar crime is and has always been an urgent issue for the society. In recent years, white-collar crime has increased dramatically by technological advances. The studies show that companies are affected annually by corruption, balance-sheet manipulation, embezzlement, criminal insolvency and other economic crimes. The companies are usually unable to identify the damage caused by fraudulent activities. To prevent fraud, companies have the opportunity to use intelligent IT approaches. The data analyst or the investigator can use the data which is stored digitally in today’s world to detect fraud. In the age of Big Data, digital information is increasing enormously. Storage is cheap today and no longer a limited medium. The estimates assume that today up to 80 percent of all operational information is stored in the form of unstructured text documents. This bachelor thesis examines Data Mining and Text Mining as intelligent IT approaches for fraud detection in white-collar crime. Text Mining is related to Data Mining. For a differentiation, the source of the information and the structure is important. Text Mining is mainly concerned with weak- or unstructured data, while Data Mining often relies on structured sources. At the beginning of this bachelor thesis, an insight is first given on white-collar crime. For this purpose, the three essential tasks of a fraud management are discussed. Based on the fraud triangle of Cressey it is showed which conditions need to come together so that an offender commits a fraudulent act. Following, some well-known types of white-collar crime are considered in more detail. Text Mining approach was used to demonstrate how to extract potentially useful knowledge from unstructured text. For this purpose, two self-generated e-mails were converted into struc-tured format. Moreover, a case study will be conducted on fraud detection in credit card da-taset. The dataset contains legitimate and fraudulent transactions. Based on a literature research, Data Mining techniques are selected and then applied on the dataset by using various sampling techniques and hyperparameter optimization with the goal to identify correctly pre-dicted fraudulent transactions. The CRISP-DM reference model was used as a methodical procedure.
Download or read book Advances in Computer Communication and Computational Sciences written by Sanjiv K. Bhatia and published by Springer. This book was released on 2019-05-21 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes key insights that reflect ‘Advances in Computer and Computational Sciences’ from upcoming researchers and leading academics around the globe. It gathers high-quality, peer-reviewed papers presented at the International Conference on Computer, Communication and Computational Sciences (IC4S 2018), which was held on 20-21 October, 2018 in Bangkok. The book covers a broad range of topics, including intelligent hardware and software design, advanced communications, intelligent computing techniques, intelligent image processing, and web and informatics. Its goal is to familiarize readers from the computer industry and academia with the latest advances in next-generation computer and communication technology, which they can subsequently integrate into real-world applications.
Download or read book Computational Intelligence in Data Mining written by Himansu Sekhar Behera and published by Springer. This book was released on 2018-07-03 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Conference on “Computational Intelligence in Data Mining” (ICCIDM), after three successful versions, has reached to its fourth version with a lot of aspiration. The best selected conference papers are reviewed and compiled to form this volume. The proceedings discusses the latest solutions, scientific results and methods in solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. The volume presents a sneak preview into the strengths and weakness of trending applications and research findings in the field of computational intelligence and data mining along with related field.
Download or read book Machine Learning Forensics for Law Enforcement Security and Intelligence written by Jesus Mena and published by CRC Press. This book was released on 2016-04-19 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasingly, crimes and fraud are digital in nature, occurring at breakneck speed and encompassing large volumes of data. To combat this unlawful activity, knowledge about the use of machine learning technology and software is critical. Machine Learning Forensics for Law Enforcement, Security, and Intelligence integrates an assortment of deductive
Download or read book Machine Learning Approach for Credit Card Fraud Detection KNN Na ve Bayes written by Darshan Kaur and published by . This book was released on 2020 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: The extraction of the useful information from the raw data is done a technique known as data mining. The prediction of new things from the current data has been done using the prediction analysis which is the application of data mining. Classifications techniques are most commonly used which are implemented for the prediction analysis. Hence, prediction of the credit card fraud detection is the main objective of this work. Author proposed various credit card fraud detection mechanisms and techniques to prevent and detect fraud timely. The fundamental of the proposed technique in the base paper is based on the conventional neural networks. This system drives the new values and learns from the previous experiences. For the detection of the credit card fraud, hybrid of KNN and naïve bayes classifier is proposed in this research work using which input data is classified into normal and fraud transactions. Test and training sets are the two sub-parts of the input data. In terms of precision and recall, the normal and fraud transactions have been predicted on the basis of test and training sets.
Download or read book Detection Estimation and Modulation Theory written by and published by . This book was released on 1968 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Balancing for Credit Card Fraud Detection Using Complementary Neural Networks and SMOTE Algorithm written by Vrushal Shah and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This Research presents an innovative approach towards detecting fraudulent credit card transactions. A commonly prevailing yet dominant problem faced in detection of fraudulent credit card transactions is the scarce occurrence of such fraudulent transactions with respect to legitimate (authorized) transactions. Therefore, any data that is recorded will always have a stark imbalance in the number of minority (fraudulent) and majority (legitimate) class samples. This imbalanced distribution of the training data among classes makes it hard for any learning algorithm to learn the features of the minority class. In this thesis work, we analyze the impact of applying class-balancing techniques on the training data namely oversampling (using SMOTE algorithm) for minority class and under sampling (using CMTNN) for majority class. The usage of most popular classification algorithms such as Artificial Neural Network (ANN), Support Vector Machine (SVM), Extreme Gradient Boosting (XGB), Logistic Regression (LR), Random Forest (RF) are processed on balanced data and which results to quantify the performance improvement provided by our approach. The experiments show that the hybrid approach which integrates Complementary Neural Network and Synthetic Minority Oversampling Technique gives a Quantitative performance in terms of Accuracy of 99% and 99.7% of AUC with Random Forest Classification Algorithm compared to simple undersampling and oversampling.
