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| at a financial institution a fraud detection system: 2018 3rd International Conference on Computer Science and Engineering (UBMK) IEEE Staff, 2018-09-20 UBMK 2018 provides a forum for researchers, practitioners and educators to present and discuss the most recent research, innovations, trends, experiences, and concerns in the field of computer science, computer software information systems information security engineering and computational methods On the other hand, in parallel with the regular scientific presentations, Heads of Departments of Computer Engineering Council (and other related departments) will meet to discuss the quality issues and problems in the computing field specifically the computing curricula in Turkish Universities as part of the 32rd Convention of the Assembly |
| at a financial institution a fraud detection system: Bank Fraud Revathi Subramanian, 2014-04-14 Learn how advances in technology can help curb bank fraud Fraud prevention specialists are grappling with ever-mounting quantities of data, but in today's volatile commercial environment, paying attention to that data is more important than ever. Bank Fraud provides a frank discussion of the attitudes, strategies, and—most importantly—the technology that specialists will need to combat fraud. Fraudulent activity may have increased over the years, but so has the field of data science and the results that can be achieved by applying the right principles, a necessary tool today for financial institutions to protect themselves and their clientele. This resource helps professionals in the financial services industry make the most of data intelligence and uncovers the applicable methods to strengthening defenses against fraudulent behavior. This in-depth treatment of the topic begins with a brief history of fraud detection in banking and definitions of key terms, then discusses the benefits of technology, data sharing, and analysis, along with other in-depth information, including: The challenges of fraud detection in a financial services environment The use of statistics, including effective ways to measure losses per account and ROI by product/initiative The Ten Commandments for tackling fraud and ways to build an effective model for fraud management Bank Fraud offers a compelling narrative that ultimately urges security and fraud prevention professionals to make the most of the data they have so painstakingly gathered. Such professionals shouldn't let their most important intellectual asset—data—go to waste. This book shows you just how to leverage data and the most up-to-date tools, technologies, and methods to thwart fraud at every turn. |
| at a financial institution a fraud detection system: Real-time Fraud Detection Analytics on IBM System z Mike Ebbers, Dheeraj Reddy Chintala, Priya Ranjan, Lakshminarayanan Sreenivasan, IBM Redbooks, 2013-04-11 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. |
| at a financial institution a fraud detection system: Fraud Prevention and Detection Rodney T. Stamler, Hans J. Marschdorf, Mario Possamai, 2014-03-12 Lessons can be learned from major fraud cases. Whether the victim is a company, public agency, nonprofit, foundation, or charity, there is a high likelihood that many of these frauds could have been prevented or detected sooner if early Red Flag warning signs had been identified and acted upon. Fraud Prevention and Detection: Warning Signs and the |
| at a financial institution a fraud detection system: Computational Intelligence and Information Technology Vinu V Das, Nessy Thankachan, 2011-12-10 This book constitutes the proceedings of the First International Conference on Computational Intelligence and Information Technology, CIIT 2011, held in Pune, India, in November 2011. The 58 revised full papers, 67 revised short papers, and 32 poster papers presented were carefully reviewed and selected from 483 initial submissions. The papers are contributed by innovative academics and industrial experts in the field of computer science, information technology, computational engineering, mobile communication and security and offer a stage to a common forum, where a constructive dialog on theoretical concepts, practical ideas and results of the state of the art can be developed. |
| at a financial institution a fraud detection system: Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques Bart Baesens, Veronique Van Vlasselaer, Wouter Verbeke, 2015-08-17 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. |
| at a financial institution a fraud detection system: Fraud Analytics with SAS , 2019-06-21 SAS software provides many different techniques to monitor in real time and investigate your data, and several groundbreaking papers have been written to demonstrate how to use these techniques. Topics covered illustrate the power of SAS solutions that are available as tools for fraud analytics, highlighting a variety of domains, including money laundering, financial crime, and terrorism. Also available free as a PDF from: sas.com/books. |
| at a financial institution a fraud detection system: Network Science Albert-László Barabási, Márton PÃ3sfai, 2016-07-21 Illustrated throughout in full colour, this pioneering text is the only book you need for an introduction to network science. |
| at a financial institution a fraud detection system: Financial Fraud Prevention and Detection Michael R. Young, 2013-09-06 Step-by-step guidance for board members and executives on preventing and detecting accounting fraud In the wake of highly publicized allegations of accounting irregularities and fraudulent financial reporting that are shaking up today's corporate community, Financial Fraud Prevention and Detection provides a step-by-step guide to how these crises can envelop a company and how to prevent them from happening in the first place. It is written for almost everyone involved: outside directors, audit committee members, senior executives, CFOs, CPAs, in-house lawyers, and outside law firms. Provides a blueprint for Fraud Prevention and Detection for corporate executives Presents step-by-step guidance to corporate boards and C-suite executives on managing the threat of accounting fraud Prepares directors and executives for the possibility of accounting irregularities Answers the question of how accounting fraud starts—and grows With solid strategies for prevention of accounting fraud as well as a process to follow when fraud has been discovered, Financial Fraud Prevention and Detection vividly explores the corporate environment that causes fraud, how it spreads, the kind of crises it can create for a company, and the best ways to deal with it. |
| at a financial institution a fraud detection system: Machine Learning Applications for Accounting Disclosure and Fraud Detection Papadakis, Stylianos, Garefalakis, Alexandros, Lemonakis, Christos, Chimonaki, Christiana, Zopounidis, Constantin, 2020-10-02 The prediction of the valuation of the “quality” of firm accounting disclosure is an emerging economic problem that has not been adequately analyzed in the relevant economic literature. While there are a plethora of machine learning methods and algorithms that have been implemented in recent years in the field of economics that aim at creating predictive models for detecting business failure, only a small amount of literature is provided towards the prediction of the “actual” financial performance of the business activity. Machine Learning Applications for Accounting Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment. The book applies machine learning models to identify “quality” characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. Covering topics that include data mining; fraud governance, detection, and prevention; and internal auditing, this book is essential for accountants, auditors, managers, fraud detection experts, forensic accountants, financial accountants, IT specialists, corporate finance experts, business analysts, academicians, researchers, and students. |
| at a financial institution a fraud detection system: My Billion Dollar Education Toshihide Iguchi, 2014-04-29 The true untold story of a rogue trader, whose decision to right a wrong ignited a series of political maneuvering by American and Japanese officials, leading to the expulsion of a major Japanese bank from the U.S. Toshihide Iguchi, formerly an Executive VP and U.S. Government Bond trader at Daiwa Bank's New York Branch, was responsible for $1.1 billion in unauthorized trading losses accumulated over a period of 12 years beginning in 1983. At 18, Toshihide Iguchi came to the U.S. with high hopes. Graduating from college in Missouri, marrying a St. Louis girl, and landing a promising job at Daiwa Bank in New York, he was ready to embark on his American dream. Unbeknownst to him, a storm of unprecedented financial deregulation on both sides of the Pacific was about to rage... Twelve years later, he found himself in the maximum security ward of a Manhattan jail, surrounded by Arab terrorists and a Mafia boss. The author looks back on his psychological struggles and redemption, which gave him valuable insight in helping others to prevent future billion dollar trading losses, tying in more recent rogue trading cases, discussing common misconceptions of rogue trading as well as operational risks that continue to exist in financial institutions today. |
| at a financial institution a fraud detection system: Corporate Fraud Handbook Joseph T. Wells, 2017-05-01 Delve into the mind of a fraudster to beat them at their own game Corporate Fraud Handbook details the many forms of fraud to help you identify red flags and prevent fraud before it occurs. Written by the founder and chairman of the Association of Certified Fraud Examiners (ACFE), this book provides indispensable guidance for auditors, examiners, managers, and criminal investigators: from asset misappropriation, to corruption, to financial statement fraud, the most common schemes are dissected to show you where to look and what to look for. This new fifth edition includes the all-new statistics from the ACFE 2016 Report to the Nations on Occupational Fraud and Abuse, providing a current look at the impact of and trends in fraud. Real-world case studies submitted to the ACFE by actual fraud examiners show how different scenarios play out in practice, to help you build an effective anti-fraud program within your own organization. This systematic examination into the mind of a fraudster is backed by practical guidance for before, during, and after fraud has been committed; you'll learn how to stop various schemes in their tracks, where to find evidence, and how to quantify financial losses after the fact. Fraud continues to be a serious problem for businesses and government agencies, and can manifest in myriad ways. This book walks you through detection, prevention, and aftermath to help you shore up your defenses and effectively manage fraud risk. Understand the most common fraud schemes and identify red flags Learn from illustrative case studies submitted by anti-fraud professionals Ensure compliance with Sarbanes-Oxley and other regulations Develop and implement effective anti-fraud measures at multiple levels Fraud can be committed by anyone at any level—employees, managers, owners, and executives—and no organization is immune. Anti-fraud regulations are continually evolving, but the magnitude of fraud's impact has yet to be fully realized. Corporate Fraud Handbook provides exceptional coverage of schemes and effective defense to help you keep your organization secure. |
| at a financial institution a fraud detection system: Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance El Bachir Boukherouaa, Mr. Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Mr. Alin T Mirestean, Rangachary Ravikumar, 2021-10-22 This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight. |
| at a financial institution a fraud detection system: Credit Card Fraud Detection and Analysis Through Machine Learning Yogita Goyal, Anand Sharma, 2020-07-28 |
| at a financial institution a fraud detection system: Harmony Search Algorithm Joong Hoon Kim, Zong Woo Geem, 2015-08-08 The Harmony Search Algorithm (HSA) is one of the most well-known techniques in the field of soft computing, an important paradigm in the science and engineering community. This volume, the proceedings of the 2nd International Conference on Harmony Search Algorithm 2015 (ICHSA 2015), brings together contributions describing the latest developments in the field of soft computing with a special focus on HSA techniques. It includes coverage of new methods that have potentially immense application in various fields. Contributed articles cover aspects of the following topics related to the Harmony Search Algorithm: analytical studies; improved, hybrid and multi-objective variants; parameter tuning; and large-scale applications. The book also contains papers discussing recent advances on the following topics: genetic algorithms; evolutionary strategies; the firefly algorithm and cuckoo search; particle swarm optimization and ant colony optimization; simulated annealing; and local search techniques. This book offers a valuable snapshot of the current status of the Harmony Search Algorithm and related techniques, and will be a useful reference for practising researchers and advanced students in computer science and engineering. |
| at a financial institution a fraud detection system: Fraud and Fraud Detection, + Website Sunder Gee, 2014-12-03 Detect fraud faster—no matter how well hidden—with IDEA automation Fraud and Fraud Detection takes an advanced approach to fraud management, providing step-by-step guidance on automating detection and forensics using CaseWare's IDEA software. The book begins by reviewing the major types of fraud, then details the specific computerized tests that can detect them. Readers will learn to use complex data analysis techniques, including automation scripts, allowing easier and more sensitive detection of anomalies that require further review. The companion website provides access to a demo version of IDEA, along with sample scripts that allow readers to immediately test the procedures from the book. Business systems' electronic databases have grown tremendously with the rise of big data, and will continue to increase at significant rates. Fraudulent transactions are easily hidden in these enormous datasets, but Fraud and Fraud Detection helps readers gain the data analytics skills that can bring these anomalies to light. Step-by-step instruction and practical advice provide the specific abilities that will enhance the audit and investigation process. Readers will learn to: Understand the different areas of fraud and their specific detection methods Identify anomalies and risk areas using computerized techniques Develop a step-by-step plan for detecting fraud through data analytics Utilize IDEA software to automate detection and identification procedures The delineation of detection techniques for each type of fraud makes this book a must-have for students and new fraud prevention professionals, and the step-by-step guidance to automation and complex analytics will prove useful for even experienced examiners. With datasets growing exponentially, increasing both the speed and sensitivity of detection helps fraud professionals stay ahead of the game. Fraud and Fraud Detection is a guide to more efficient, more effective fraud identification. |
| at a financial institution a fraud detection system: Financial Statement Fraud Zabihollah Rezaee, Richard Riley, 2009-09-11 Practical examples, sample reports, best practices and recommendations to help you deter, detect, and prevent financial statement fraud Financial statement fraud (FSF) continues to be a major challenge for organizations worldwide. Financial Statement Fraud: Prevention and Detection, Second Edition is a superior reference providing you with an up-to-date understanding of financial statement fraud, including its deterrence, prevention, and early detection. You will find A clear description of roles and responsibilities of all those involved in corporate governance and the financial reporting process to improve the quality, reliability and transparency of financial information. Sample reports, examples, and documents that promote a real-world understanding of incentives, opportunities, and rationalizations Emerging corporate governance reforms in the post-SOX era, including provisions of the SOX Act, global regulations and best practices, ethical considerations, and corporate governance principles Practical examples and real-world how did this happen discussions that provide valuable insight for corporate directors and executives, auditors, managers, supervisory personnel and other professionals saddled with anti-fraud responsibilities Expert advice from the author of Corporate Governance and Ethics and coauthor of the forthcoming Wiley textbook, White Collar Crime, Fraud Examination and Financial Forensics Financial Statement Fraud, Second Edition contains recommendations from the SEC Advisory Committee to reduce the complexity of the financial reporting process and improving the quality of financial reports. |
| at a financial institution a fraud detection system: Introduction to Online Payments Risk Management Ohad Samet, 2013-06-07 If you've been tasked with building a team to handle risk management for online payments (RMP), this practical introduction provides a framework for choosing the technologies and personnel you need. Author and financial services executive Ohad Samet explains the components of payments risk management, and presents a coherent strategy and operational approach. You'll learn the answers to questions you're likely to encounter in the first 18 months of operation, with information that Samet has shaped and tested over several years in the industry. This book is ideal whether you intend to be a one-person task force or work with dozens of agents and analysts. Use both a portfolio and behavioral approach to analyzing and optimizing losses Learn about your customers to determine if they can and will meet obligations Build an RMP team for payment risk operations, analytics, and decision automation Use linking mechanisms and velocity models to detect unusual activity among your customers Design system and data architecture to facilitate your activity analysis Implement the decision and loss-reduction mechanisms you need to act on your findings |
| at a financial institution a fraud detection system: 1st Review of the Suspicious Activity Reporting System (SARS). , 1998 |
| at a financial institution a fraud detection system: Corruption and Fraud in Financial Markets Carol Alexander, Douglas Cumming, 2020-06-22 Identifying malpractice and misconduct should be top priority for financial risk managers today Corruption and Fraud in Financial Markets identifies potential issues surrounding all types of fraud, misconduct, price/volume manipulation and other forms of malpractice. Chapters cover detection, prevention and regulation of corruption and fraud within different financial markets. Written by experts at the forefront of finance and risk management, this book details the many practices that bring potentially devastating consequences, including insider trading, bribery, false disclosure, frontrunning, options backdating, and improper execution or broker-agency relationships. Informed but corrupt traders manipulate prices in dark pools run by investment banks, using anonymous deals to move prices in their own favour, extracting value from ordinary investors time and time again. Strategies such as wash, ladder and spoofing trades are rife, even on regulated exchanges – and in unregulated cryptocurrency exchanges one can even see these manipulative quotes happening real-time in the limit order book. More generally, financial market misconduct and fraud affects about 15 percent of publicly listed companies each year and the resulting fines can devastate an organisation's budget and initiate a tailspin from which it may never recover. This book gives you a deeper understanding of all these issues to help prevent you and your company from falling victim to unethical practices. Learn about the different types of corruption and fraud and where they may be hiding in your organisation Identify improper relationships and conflicts of interest before they become a problem Understand the regulations surrounding market misconduct, and how they affect your firm Prevent budget-breaking fines and other potentially catastrophic consequences Since the LIBOR scandal, many major banks have been fined billions of dollars for manipulation of prices, exchange rates and interest rates. Headline cases aside, misconduct and fraud is uncomfortably prevalent in a large number of financial firms; it can exist in a wide variety of forms, with practices in multiple departments, making self-governance complex. Corruption and Fraud in Financial Markets is a comprehensive guide to identifying and stopping potential problems before they reach the level of finable misconduct. |
| at a financial institution a fraud detection system: Business Theft and Fraud James R. Youngblood, 2016-08-05 Business Theft and Fraud: Detection and Prevention offers a broad perspective on business-related theft, providing a detailed discussion of numerous avenues of theft, including internal and external fraud, organized retail crime, mortgage fraud, cyber fraud, and extortion. Combining current research and the author’s extensive experience with loss prevention and security, this professional text identifies industry trouble areas and offers techniques to combat business theft, such as how to identify sales underreporting, track sales by shifts, and educate employees on computer-related fraud. This publication is critical for those involved with loss prevention, security, or criminal justice. Business Theft and Fraud’s accessible, franchise-oriented scope will help many professionals identify and thwart threats in the evolving business world. |
| at a financial institution a fraud detection system: Observability in Finance Brindha Priyadarshini Jeyaraman, 2024-06-25 Observe, optimize, and transform in finance KEY FEATURES ● Learn observability basics in finance. ● Monitor financial data with logs and alerts and improve data security. ● Identify the key metrics for financial oversight. ● Use new tech for financial observability. DESCRIPTION This book explains the role of observability in the finance sector, showing how new technologies can help monitor and manage financial systems more effectively. It outlines the use of real-time data monitoring, Machine Learning, and cloud computing to enhance the efficiency of financial operations and ensure they meet regulatory standards. The chapters guide you through the process of setting up systems to track financial activities accurately, analyze market trends, and predict future challenges to keep operations secure and competitive. It offers clear explanations of how these technologies can help finance professionals make better decisions and manage risks proactively. Designed for finance professionals looking to update their technical skills, this book provides practical guidance on adopting modern observability tools and practices. It will help you understand how to apply these technologies to increase transparency and strengthen the resilience of financial operations in a constantly evolving industry. WHAT YOU WILL LEARN ● Implement effective data monitoring strategies in finance. ● Use Machine Learning to enhance financial risk assessment. ● Develop robust compliance frameworks using observability tools. ● Apply real-time analytics for quicker financial decision-making. ● Integrate predictive analytics for forward-looking financial insights. ● Understand and deploy distributed tracing for financial operations. WHO THIS BOOK IS FOR This book is ideal for financial professionals seeking to deepen their understanding of observability. It is also suitable for IT specialists in finance who wish to advance their skills in modern observability tools and practices. TABLE OF CONTENTS 1. Introduction 2. The Fundamentals of Observability 3. Monitoring and Logging for Financial Data 4. Tracing and Correlation in Finance 5. Metrics and Key Performance Indicators for Finance 6. Real-time Monitoring and Alerting in Finance 7. Observability for Algorithmic Trading and Market Data 8. Compliance and Regulatory Considerations 9. Advanced Techniques: Machine Learning and Predictive Analytics 10. Organizational Culture and Collaboration 11. Case Studies and Best Practices Observability 12. The Future of Observability in Finance 13. The Horizon of Financial Observability |
| at a financial institution a fraud detection system: Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track Gianmarco De Francisci Morales, |
| at a financial institution a fraud detection system: Communication Technologies and Security Challenges in IoT Ajay Prasad, |
| at a financial institution a fraud detection system: ICT Systems Security and Privacy Protection Nora Cuppens-Boulahia, Frederic Cuppens, Sushil Jajodia, Anas Abou El Kalam, Thierry Sans, 2016-09-21 This book constitutes the refereed proceedings of the 29th IFIP TC 11 International Information Security and Privacy Conference, SEC 2014, held in Marrakech, Morocco, in June 2014. The 27 revised full papers and 14 short papers presented were carefully reviewed and selected from 151 submissions. The papers are organized in topical sections on intrusion detection, data security, mobile security, privacy, metrics and risk assessment, information flow control, identity management, identifiability and decision making, malicious behavior and fraud and organizational security. |
| at a financial institution a fraud detection system: Big Data Computing Tanvir Habib Sardar, Bishwajeet Kumar Pandey, 2024-02-27 This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing. |
| at a financial institution a fraud detection system: Fraud Risk Assessment Tommie W. Singleton, Aaron J. Singleton, 2011-04-12 Praise for the Fourth Edition of Fraud Auditing and Forensic Accounting Tommie and Aaron Singleton have made important updates to a book I personally rely very heavily upon: Fraud Auditing and Forensic Accounting (FAFA). In the newest edition, they take difficult topics and explain them in straightforward actionable language. All my students benefitted from reading the third edition of the FAFA to better understand the issues and area of fraud and forensic accounting. With their singular focus on understandability and practicality, this Fourth Edition of the book makes a very important contribution for academics, researchers, practitioners, and students. Bravo!—Dr. Timothy A. Pearson, Director, Division of Accounting, West Virginia University, Executive Director, Institute for Fraud Prevention Finally someone has written a book that combines fraud examination and forensic accounting. The authors have clearly explained both in their earlier edition and now they have enhanced the first with additional materials. The order in which the material is presented is easy to grasp and logically follows the 'typical' fraud examination from the awareness that something is wrong to the court case. The explanatory materials presented aid this effort by being both well placed within the book and relevant to the narrative. —Dr. Douglas E. Ziegenfuss, Chair and Professor, Department of Accounting, Old Dominion University Fraud Auditing and Forensic Accounting is a masterful compilation of the concepts found in this field. The organization of the text with the incorporation of actual cases, facts, and figures provides a logical and comprehensive basis for learning the intricacies of fraud examination and forensic accounting. The authors successfully blend the necessary basics with advanced principles in a manner that makes the book an outstanding resource for students and professionals alike.—Ralph Q. Summerford, President of Forensic/Strategic Solutions, PC |
| at a financial institution a fraud detection system: Reference Guide to Anti-money Laundering and Combating the Financing of Terrorism Paul Allan Schott, World Bank, 2006 Efforts to launder money and finance terrorism have been evolving rapidly in recent years in response to heightened countermeasures. The international community has witnessed the use of increasingly sophisticated methods to move illicit funds through financial systems across the globe and has acknowledged the need for improved multilateral cooperation to fight these criminal activities. The World Bank and International Monetary Fund have developed this guide to help countries understand the new international standards. It will hopefully serve as a comprehensive source of practical information for countries to fight money laundering and terrorist financing. It discusses the problems caused by these crimes, the specific actions countries need to take to address them, and the role international organizations, such as the Bank and the IMF, play in the process. This guide is a tool for countries to establish and improve their legal and institutional frameworks and their preventive measures according to international standards and best practices. -- From Foreword (p. ix). |
| at a financial institution a fraud detection system: The International Corporate Governance System F. Lessambo, 2016-01-26 This book provides a comprehensive approach to Corporate Governance, Audit Process and Risk Management. Furthermore, it provides an analytical and comprehensive approach of the issues facing governance directors, internal and external auditors, risk managers, and public officials conducting assessments based upon the Report on Standards and Codes. |
| at a financial institution a fraud detection system: Database Management using AI: A Comprehensive Guide A Purushotham Reddy, 2024-10-20 Database Management Using AI: A Comprehensive Guide is a professional yet accessible exploration of how artificial intelligence (AI) is reshaping the world of database management. Designed for database administrators, data scientists, and tech enthusiasts, this book walks readers through the transformative impact of AI on modern data systems. The guide begins with the fundamentals of database management, covering key concepts such as data models, SQL, and the principles of database design. From there, it delves into the powerful role AI plays in optimizing database performance, enhancing security, and automating complex tasks like data retrieval, query optimization, and schema design. The book doesn't stop at theory. It brings AI to life with practical case studies showing how AI-driven database systems are being used in industries such as e-commerce, healthcare, finance, and logistics. These real-world examples demonstrate AI's role in improving efficiency, reducing errors, and driving intelligent decision-making. Key topics covered include: Introduction to Database Systems: Fundamentals of database management, from relational databases to modern NoSQL systems. AI Integration: How AI enhances database performance, automates routine tasks, and strengthens security. Real-World Applications: Case studies from diverse sectors like healthcare, finance, and retail, showcasing the practical impact of AI in database management. Predictive Analytics and Data Mining: How AI tools leverage data to make accurate predictions and uncover trends. Future Trends: Explore cutting-edge innovations like autonomous databases and cloud-based AI solutions that are shaping the future of data management. With its clear explanations and actionable insights, Database Management Using AI equips readers with the knowledge to navigate the fast-evolving landscape of AI-powered databases, making it a must-have resource for those looking to stay ahead in the digital age. |
| at a financial institution a fraud detection system: 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. |
| at a financial institution a fraud detection system: Advanced Information Technology, Services and Systems Mostafa Ezziyyani, Mohamed Bahaj, Faddoul Khoukhi, 2017-11-10 This book includes the proceedings of the International Conference on Advanced Information Technology, Services and Systems (AIT2S-17) held on April 14–15, 2017 in Tangier, Morocco. Presenting the latest research in the field, it stimulates debate, discusses new challenges and provides insights into the field in order to promote closer interaction and interdisciplinary collaboration between researchers and practitioners. Intended for researchers and practitioners in advanced information technology/management and networking, the book is also of interest to those in emergent fields such as data science and analytics, big data, Internet of Things, smart networked systems, artificial intelligence and expert systems, pattern recognition, and cloud computing. |
| at a financial institution a fraud detection system: Home Equity Conversion Mortgages United States. Department of Housing and Urban Development, 1994 |
| at a financial institution a fraud detection system: Databricks Certified Associate Developer for Apache Spark Using Python Saba Shah, 2024-06-14 Learn the concepts and exercises needed to confidently prepare for the Databricks Associate Developer for Apache Spark 3.0 exam and validate your Spark skills with an industry-recognized credential Key Features Understand the fundamentals of Apache Spark to design robust and fast Spark applications Explore various data manipulation components for each phase of your data engineering project Prepare for the certification exam with sample questions and mock exams Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionSpark has become a de facto standard for big data processing. Migrating data processing to Spark saves resources, streamlines your business focus, and modernizes workloads, creating new business opportunities through Spark’s advanced capabilities. Written by a senior solutions architect at Databricks, with experience in leading data science and data engineering teams in Fortune 500s as well as startups, this book is your exhaustive guide to achieving the Databricks Certified Associate Developer for Apache Spark certification on your first attempt. You’ll explore the core components of Apache Spark, its architecture, and its optimization, while familiarizing yourself with the Spark DataFrame API and its components needed for data manipulation. You’ll also find out what Spark streaming is and why it’s important for modern data stacks, before learning about machine learning in Spark and its different use cases. What’s more, you’ll discover sample questions at the end of each section along with two mock exams to help you prepare for the certification exam. By the end of this book, you’ll know what to expect in the exam and gain enough understanding of Spark and its tools to pass the exam. You’ll also be able to apply this knowledge in a real-world setting and take your skillset to the next level.What you will learn Create and manipulate SQL queries in Apache Spark Build complex Spark functions using Spark's user-defined functions (UDFs) Architect big data apps with Spark fundamentals for optimal design Apply techniques to manipulate and optimize big data applications Develop real-time or near-real-time applications using Spark Streaming Work with Apache Spark for machine learning applications Who this book is for This book is for data professionals such as data engineers, data analysts, BI developers, and data scientists looking for a comprehensive resource to achieve Databricks Certified Associate Developer certification, as well as for individuals who want to venture into the world of big data and data engineering. Although working knowledge of Python is required, no prior knowledge of Spark is necessary. Additionally, experience with Pyspark will be beneficial. |
| at a financial institution a fraud detection system: Machine Learning in Healthcare and Security Prashant Pranav, Archana Patel, Sarika Jain, 2024-01-19 This book brings together a blend of different areas of machine learning and recent advances in the area. From the use of ML in healthcare to security, this book encompasses several areas related to ML while keeping a check on traditional ML algorithms. Machine Learning in Healthcare and Security: Advances, Obstacles, and Solutions describes the predictive analysis and forecasting techniques in different emerging and classical areas using the approaches of ML and AI. It discusses the application of ML and AI in medical diagnostic systems and deals with the security prevention aspects of ML and how it can be used to tackle various emerging security issues. This book also focuses on NLP and understanding the techniques, obstacles, and possible solutions. This is a valuable reference resource for researchers and postgraduate students in healthcare systems engineering, computer science, cyber-security, information technology, and applied mathematics. |
| at a financial institution a fraud detection system: Knowledge Management Irma Becerra-Fernandez, Rajiv Sabherwal, Richard Kumi, 2024-02-23 Knowledge Management: Systems and Processes in the AI Era, Third Edition, is aimed at students and managers who seek detailed insights into contemporary knowledge management (KM). It explains the concepts, theories, and technologies that provide the foundation for knowledge management; the systems and structures that constitute KM solutions; and the processes for developing, deploying, and evaluating these KM solutions. This book serves as a complete introduction to the subject of knowledge management, incorporating technical and social aspects, as well as concepts, practical examples, traditional KM approaches, and emerging topics. This third edition has been revised and expanded to include more coverage of emergent trends such as cloud computing, online communities, crowdsourcing, and artificial intelligence. Aimed at advanced undergraduate, postgraduate, and MBA students who are seeking a comprehensive perspective on knowledge management, Knowledge Management is also complemented by online support for lecturers including suggested solutions to the many review questions and application exercises contained within the book. |
| at a financial institution a fraud detection system: Advances in Emerging Financial Technology and Digital Money Yassine Maleh, Justin Zhang, Abderrahim Hansali, 2024-03-29 The financial sector is witnessing rapid technological innovations, leading to the emergence of Fintech (financial technologies), revolutionizing national and international financial landscapes. Fintech is expanding and enhancing financial products and services, making them more accessible and affordable while transforming customer relationships, payment methods, financing, and transfers. Advances in Emerging Financial Technology and Digital Money provides a platform for collective reflection, bringing together institutions, policymakers, digital and financial service providers, professionals, and academics from various disciplines. The aim is to clarify the challenges, opportunities, and socio-economic impacts of innovations in finance and technology on citizens and businesses in Morocco, Africa, and worldwide. This comprehensive collection offers valuable insights into the current state and prospects of financial technology and digital money. This book covers all the essential topics, including: AI and Machine Learning in Fintech and Beyond Financial Inclusion, Literacy, and Behavior Fintech Ecosystems, Collaboration, and Analysis Blockchain, Security, and Sustainability Fintech Innovations and Applications In this new book, the authors share their experiences to provide a comprehensive and well‐researched overview of the technologies and concepts that will transform the banking industry as we know it. It aspires to be a useful reference for executive managers, CIOs, Fintech professionals, and researchers interested in exploring and implementing an efficient Fintech strategy. The book also presents selected papers from International Fintech Congress (IFC 2022). |
| at a financial institution a fraud detection system: Banking Services Nicholas Greifer, 2004 |
| at a financial institution a fraud detection system: Encyclopedia of Organizational Knowledge, Administration, and Technology Khosrow-Pour D.B.A., Mehdi, 2020-09-29 For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication. |
| at a financial institution a fraud detection system: Anomaly Detection Saira Banu, 2021 When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspension by differing significantly from the majority of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase in the spams faced by the individuals and the companies are increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, Machine Learning, Artificial Intelligence, Deep learning, Image Processing, Cloud Computing, Audio processing, Video Processing, VoIP, Data Science, Wireless Sensor etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data. This book will mainly target researchers and higher graduate learners in computer science and data science. |
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Greenbacks Financial Services located at 123 E Main St suite b, Fabens, TX 79838 - reviews, ratings, hours, phone number, directions, and more.
Financial Times
Did the US know about Israel’s attack all along? The Weekend Essay. The struggle for Los Angeles. Hedge fund manager Ian Wace is ‘catalysing’ change in an abandoned rural …
MarketWatch: Stock Market News - Financial News
AMD just showed signs of progress — but can its new chips really take on Nvidia? Americans spend $10 billion more on Mother’s Day than Father’s Day. What’s going on? Israel-Iran …
Personal Finance and Financial Basics | Fidelity
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