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AI-Based Fraud Detection

AI-Based Fraud Detection
Author: Trevor Johnson
Publisher: Independently Published
Total Pages: 0
Release: 2024-02-23
Genre: Computers
ISBN:

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In today's digital landscape, the proliferation of cyber threats poses significant challenges to businesses worldwide. As technology advances, so do the methods employed by cybercriminals. "AI-Based Fraud Detection: Safeguarding Your Business Against Cyber Threats" is your comprehensive guide to understanding, implementing, and optimizing artificial intelligence (AI) for fraud detection, ensuring the protection of your business from evolving cyber risks. Delve into the fundamental concepts of AI-based fraud detection, exploring the intersection of artificial intelligence, machine learning, and cybersecurity. Gain insights into how AI revolutionizes fraud detection methodologies, empowering businesses to stay ahead of sophisticated cyber threats. Learn why robust cybersecurity measures are imperative in today's interconnected world. Discover the critical role of AI in fortifying your defenses against cyber attacks, safeguarding sensitive data, and preserving the trust of your customers. Uncover the inner workings of machine learning algorithms and their pivotal role in fraud detection. Explore how these algorithms analyze vast amounts of data to identify patterns, anomalies, and potential fraudulent activities with unparalleled accuracy. Discover strategies for enhancing your fraud detection capabilities through AI-driven solutions. Learn how AI empowers organizations to adapt to evolving fraud tactics, detect suspicious behavior in real-time, and mitigate financial losses effectively. Explore the transformative potential of artificial intelligence technology in combating fraud. Discover how AI-driven tools enable proactive fraud prevention, predictive analytics, and adaptive security measures to stay ahead of emerging threats. Unlock the power of real-time fraud monitoring solutions powered by AI. Learn how these innovative technologies provide continuous surveillance, instantly flagging suspicious activities and enabling swift response to potential threats. Explore the myriad benefits of AI in fraud prevention, from improved accuracy and efficiency to cost savings and enhanced customer trust. Discover how AI-driven fraud detection solutions deliver measurable results, bolstering your bottom line and reputation. Gain practical insights into implementing AI for fraud detection within your organization. Navigate the challenges, best practices, and considerations involved in deploying AI-driven solutions effectively to combat fraud. Learn how AI tools mitigate risks associated with fraudulent activities, minimizing financial losses and reputational damage. Explore advanced techniques for leveraging AI to identify, analyze, and respond to emerging cyber threats proactively. Fortify your business security infrastructure with AI-based fraud detection mechanisms. Discover how AI strengthens your defense against cyber attacks, ensuring the resilience and continuity of your operations in the face of evolving threats. Harness the power of AI to detect anomalies indicative of fraudulent activities. Learn how AI algorithms analyze data patterns, behaviors, and transactions in real-time, enabling swift identification and mitigation of potential threats. Equip your organization with the tools and techniques needed to prevent fraudulent activities effectively. Discover how AI-powered cyber threat protection solutions defend against a wide range of cyber attacks. From phishing scams to ransomware attacks, explore how AI enhances threat detection, response, and remediation capabilities, safeguarding your business from harm. Ensure the integrity and security of financial transactions with AI-based fraud detection mechanisms. Learn how AI monitors transactional activities, identifies suspicious behavior, and prevents fraudulent transactions in real-time, preserving the financial health of your business.


Machine Learning Advances in Payment Card Fraud Detection

Machine Learning Advances in Payment Card Fraud Detection
Author: Nick Ryman-Tubb
Publisher: Academic Press
Total Pages: 350
Release: 2018-05-01
Genre: Business & Economics
ISBN: 012813416X

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Machine Learning Advances in Payment Card Fraud Detection provides a thorough review of the state-of-the-art in fraud detection research that is ideal for graduate level readers and professionals. Through a comprehensive examination of fraud analytics that covers data collection, steps for cleaning and processing data, tools for analyzing data, and ways to draw insights, the book introduces state-of the-art payment fraud detection techniques. Other topics covered include machine learning techniques for the detection of fraud, including SOAR, and opportunities for future research, such as developing holistic approaches for countering fraud. Covers analytical approaches and machine learning for fraud detection Explores SOAR with full R-code and example obfuscated datasets in a freely-accessible companion website Introduces state-of the-art payment fraud detection techniques


Artificial Intelligence for Intelligent Systems

Artificial Intelligence for Intelligent Systems
Author: Inam Ullah Khan
Publisher: CRC Press
Total Pages: 375
Release: 2024-07-31
Genre: Computers
ISBN: 1040086969

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The aim of this book is to highlight the most promising lines of research, using new enabling technologies and methods based on AI/ML techniques to solve issues and challenges related to intelligent and computing systems. Intelligent computing easily collects data using smart technological applications like IoT-based wireless networks, digital healthcare, transportation, blockchain, 5.0 industry and deep learning for better decision making. AI enabled networks will be integrated in smart cities' concept for interconnectivity. Wireless networks will play an important role. The digital era of computational intelligence will change the dynamics and lifestyle of human beings. Future networks will be introduced with the help of AI technology to implement cognition in real-world applications. Cyber threats are dangerous to encode information from network. Therefore, AI-Intrusion detection systems need to be designed for identification of unwanted data traffic. This book: Provides a better understanding of artificial intelligence-based applications for future smart cities Presents a detailed understanding of artificial intelligence tools for intelligent technologies Showcases intelligent computing technologies in obtaining optimal solutions using artificial intelligence Discusses energy-efficient routing protocols using artificial intelligence for Flying ad-hoc networks (FANETs) Covers machine learning-based Intrusion detection system (IDS) for smart grid It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.


Innovative Technology at the Interface of Finance and Operations

Innovative Technology at the Interface of Finance and Operations
Author: Volodymyr Babich
Publisher: Springer Nature
Total Pages: 304
Release: 2022-01-01
Genre: Business & Economics
ISBN: 3030757293

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This book examines the challenges and opportunities arising from an assortment of technologies as they relate to Operations Management and Finance. The book contains primers on operations, finance, and their interface. After that, each section contains chapters in the categories of theory, applications, case studies, and teaching resources. These technologies and business models include Big Data and Analytics, Artificial Intelligence, Machine Learning, Blockchain, IoT, 3D printing, sharing platforms, crowdfunding, and crowdsourcing. The balance between theory, applications, and teaching materials make this book an interesting read for academics and practitioners in operations and finance who are curious about the role of new technologies. The book is an attractive choice for PhD-level courses and for self-study.


Machine Learning Applications for Accounting Disclosure and Fraud Detection

Machine Learning Applications for Accounting Disclosure and Fraud Detection
Author: Papadakis, Stylianos
Publisher: IGI Global
Total Pages: 270
Release: 2020-10-02
Genre: Business & Economics
ISBN: 179984806X

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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.


Guide to Vulnerability Analysis for Computer Networks and Systems

Guide to Vulnerability Analysis for Computer Networks and Systems
Author: Simon Parkinson
Publisher: Springer
Total Pages: 384
Release: 2018-09-04
Genre: Computers
ISBN: 3319926241

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This professional guide and reference examines the challenges of assessing security vulnerabilities in computing infrastructure. Various aspects of vulnerability assessment are covered in detail, including recent advancements in reducing the requirement for expert knowledge through novel applications of artificial intelligence. The work also offers a series of case studies on how to develop and perform vulnerability assessment techniques using start-of-the-art intelligent mechanisms. Topics and features: provides tutorial activities and thought-provoking questions in each chapter, together with numerous case studies; introduces the fundamentals of vulnerability assessment, and reviews the state of the art of research in this area; discusses vulnerability assessment frameworks, including frameworks for industrial control and cloud systems; examines a range of applications that make use of artificial intelligence to enhance the vulnerability assessment processes; presents visualisation techniques that can be used to assist the vulnerability assessment process. In addition to serving the needs of security practitioners and researchers, this accessible volume is also ideal for students and instructors seeking a primer on artificial intelligence for vulnerability assessment, or a supplementary text for courses on computer security, networking, and artificial intelligence.


AI-Driven Decentralized Finance and the Future of Finance

AI-Driven Decentralized Finance and the Future of Finance
Author: Irfan, Mohammad
Publisher: IGI Global
Total Pages: 426
Release: 2024-08-26
Genre: Business & Economics
ISBN:

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In the evolving landscape of finance, traditional institutions grapple with challenges ranging from outdated processes to limited accessibility, hindering the industry's ability to meet the diverse needs of a modern, digital-first society. Moreover, as the world embraces Decentralized Finance (DeFi) and Artificial Intelligence (AI) technologies, there becomes a need to bridge the gap between innovation and traditional financial systems. This disconnect not only impedes progress but also limits the potential for financial inclusion and sustainable growth. AI-Driven Decentralized Finance and the Future of Finance addresses the complexities and challenges currently facing the financial industry. By exploring the transformative potential of AI in decentralized finance, this book offers a roadmap for navigating the convergence of technology and finance. From optimizing smart contracts to enhancing security and personalizing financial experiences, the book provides practical insights and real-world examples that empower professionals to leverage AI-driven strategies effectively.


Beyond the Hype: Realizing the True Potential of AI

Beyond the Hype: Realizing the True Potential of AI
Author: Anup Bolshetty
Publisher: Anup Bolshetty
Total Pages: 28
Release: 2023-04-19
Genre: Computers
ISBN:

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Discover the true potential of AI beyond the hype with this insightful and thought-provoking book. From healthcare to finance, transportation to manufacturing, explore the many ways in which AI is transforming industries and society, as well as the ethical challenges that must be addressed. Written in an accessible and engaging style, this book is essential reading for anyone interested in the future of technology and its impact on our world.


The Fight Against Fraud

The Fight Against Fraud
Author:
Publisher:
Total Pages: 0
Release: 2004
Genre: Credit cards
ISBN:

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Machine Learning Approach to Detect Fraudulent Banking Transactions

Machine Learning Approach to Detect Fraudulent Banking Transactions
Author: Riwaj Kharel
Publisher: GRIN Verlag
Total Pages: 75
Release: 2022-09-22
Genre: Computers
ISBN: 3346728943

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Master's Thesis from the year 2022 in the subject Computer Sciences - Artificial Intelligence, grade: 3, University of Applied Sciences Berlin, course: Project management and Data Science, language: English, abstract: The study investigates whether a machine learning algorithm can be used to detect fraud attempts and how a fraud management system based on machine learning might work. For fraud detection, most institutions rely on rule-based systems with manual evaluation. Until recently, these systems had been performing admirably. However, as fraudsters become more sophisticated, traditional systems' outcomes are becoming inconsistent. Fraud usually comprises many methods that are used repeatedly that's why looking for patterns is a common emphasis for fraud detection. Data analysts can, for example, avoid insurance fraud by developing algorithms that recognize trends and abnormalities. AI techniques used to detect fraud include Data mining classifies, groups, and segments data to search through millions of transactions to find patterns and detect fraud. The scientific paper discusses machine learning methods to detect fraud detection with a case study and analysis of Kaggle datasets.