Free Download Fraud Detection & Fraud Analytics For Fraud Risk Management
Published 3/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.44 GB | Duration: 2h 40m
Learn Behavioral Fraud Detection, Fraud Analytic, and Fraud Anomaly Detection
What you'll learn
Comprehend the basic concepts of fraud, its various types, and its significance in the business environment.
Grasp the basics of behavioural analysis and fraud analytics, understanding their importance in effective fraud detection.
Master the detection of behavioural indicators associated with fraud and learn to utilize behavioural analysis in real-world situations.
Become proficient in the use of predictive modeling and data visualization for fraud detection, understanding the necessity of these techniques in fraud analyti
Gain in-depth understanding of predictive modelling techniques for fraud detection and learn to apply advanced fraud analytics techniques.
Understand the application of AI and Machine Learning in fraud detection, including real-world use cases, and appreciate the role of anomaly detection and big d
Analyze real-world case studies that employed both behavioural analysis and fraud analytics, gaining a practical understanding of the concepts.
Build a comprehensive fraud detection framework, understand prevention strategies, and implement a data-driven culture in an organization for effective fraud de
Requirements
To participate in this Certificate Program, you will need an electronic device with online video-viewing capabilities (e.g., smartphone, tablet, laptop, desktop computer, etc.).
Although this is helpful, you will need no previous knowledge in compliance or anti-financial crime.
A background in business, legal, or finance might also be beneficial but is not required.
Description
Dive into the world of fraud detection with our comprehensive course designed to equip you with the skills to identify and prevent fraud through behavioral analysis and analytics. Starting with the fundamentals of fraud and behavioral indicators, this course takes you through a journey of practical analysis using case studies, predictive modeling, and data visualization. Delve deeper with advanced modules on Machine Learning, AI applications, and the use of big data in detecting fraud. Culminating in an integrated framework for robust fraud detection, this course covers practical strategies, regulatory considerations, and the future landscape of fraud prevention. A final assessment ensures your proficiency in these specialized skills, preparing you to tackle fraud head-on in various professional settings.COURSE STRUCTUREModule 1: Understanding Fraud and the Basics of Behavioral Analysis and Fraud AnalyticsKickstart your journey with an overview of fraud, introducing the critical role of behavioral analysis and fraud analytics in detection. Explore the basics of behavioral indicators and the significance of data-driven decision-making in identifying fraud. This foundation sets the stage for understanding how to leverage analytics in fraud prevention effectively.Module 2: Behavioral Analysis and Fraud Analytics in Fraud DetectionDive deeper into the practical aspects of using behavioral analysis for fraud detection. Learn through case studies how to identify behavioral indicators of fraud, utilize predictive modeling to forecast fraudulent activities, and apply data visualization techniques to enhance detection strategies. This module equips you with the tools to build and interpret fraud prediction models.Module 3: Advanced Fraud Analytics TechniquesAdvance your skills with sophisticated analytics techniques, exploring the applications of Machine Learning and AI in fraud detection. Understand the impact of big data on fraud analytics, learn about anomaly detection, and study real-world cases to see these advanced technologies in action. This module prepares you to leverage cutting-edge tools in combating fraud.Module 4: Case Studies and Comprehensive Fraud Detection FrameworkIntegrate your knowledge and skills to build a comprehensive fraud detection framework. Analyze case studies that combine behavioral analysis with fraud analytics, develop prevention strategies, and consider regulatory and ethical implications. Stay ahead of the curve by examining future trends and challenges in fraud detection. This final module ensures you're ready to implement a data-driven culture for fraud prevention in your institution.By the end of this course, you'll be armed with the knowledge and skills necessary to identify, prevent, and manage fraud effectively using the latest techniques in behavioral analysis and analytics. Whether you're starting your journey in fraud prevention or looking to enhance your existing skills, this course offers valuable insights and practical strategies to advance your career.COURSE FEATURESInteractive Modules: Engage with dynamic content, including multiple-choice exercises that mirror real-world scenarios.Expert Instruction: Benefit from the insights and experiences of seasoned professionals in behavioural fraud detection and analytics.Flexible Learning Environment: Access our course from anywhere, at any time, through our state-of-the-art online platform, designed for busy professionals.Professional Certification: Earn a distinguished certification issued by the Financial Crime Academy that showcases your expertise in behavioural fraud detection and analytics with an understanding of its importance within the compliance, risk management, and anti-financial crime landscape.WHO THIS COURSE IS FORThis program is ideally suited for compliance officers, anti-financial crime specialists, risk managers, financial investigators, or similar professionals in mid to large-sized corporations across financial services, consulting, legal services, technology, manufacturing, healthcare, or any industry requiring a strong understanding of anti-financial crime compliance and risk management principles. These individuals are typically career-driven, value practical and applicable knowledge, and are seeking to accelerate their careers by staying updated with the latest developments in fraud detection techniques, including behavioral analysis and advanced analytics.ENROLL TODAYEnroll in our behavioral analysis and analytics course today to take a significant step towards becoming an expert in navigating and mitigating behavioral fraud detection and analytics, thereby contributing to the overall success of your organisation.Important! This course, similar to the Financial Crime Academy's Certificate in Behavioural Fraud Detection and Analytics, is available on Udemy to support FCA's mission of making professional education more widely accessible. Completion via Udemy grants a certificate of completion only without access to FCA's platform, support, or a verifiable certificate ID. Courses on Udemy do not count towards FCA's CAMP, CAIP, or CFCP programs.
Overview
Section 1: Introduction to this Program
Lecture 1 Thank You & Welcome
Lecture 2 Introduction
Section 2: Understanding Fraud and the Basics of Behavioral Analysis and Fraud Analytics
Lecture 3 Introduction to this Module
Lecture 4 Understanding Fraud: An Overview
Lecture 5 Basics of Behavioral Analysis
Lecture 6 Basics of Fraud Analytics
Lecture 7 The Importance of Behavioral Analysis and Analytics in Fraud Detection
Lecture 8 Overview of Behavioral Indicators of Fraud
Lecture 9 Introduction to Data-Driven Decision-Making in Fraud Detection
Lecture 10 Module Summary
Section 3: Behavioral Analysis and Fraud Analytics in Fraud Detection
Lecture 11 Introduction to this Module
Lecture 12 In-Depth: Behavioral Indicators of Fraud
Lecture 13 Utilizing Behavioral Analysis in Fraud Detection
Lecture 14 Case Studies: Behavioral Analysis and Fraud Detection
Lecture 15 Overview of Predictive Modelling in Fraud Detection
Lecture 16 Building a Fraud Prediction Model
Lecture 17 Introduction to Data Visualization in Fraud Detection
Lecture 18 Effective Data Visualization Techniques for Fraud Detection
Lecture 19 Module Summary
Section 4: Advanced Fraud Analytics Techniques
Lecture 20 Introduction to this Module
Lecture 21 In-depth: Predictive Modelling Techniques for Fraud Detection
Lecture 22 Advanced Fraud Analytics Techniques
Lecture 23 Machine Learning and AI in Fraud Detection
Lecture 24 Application of AI and Machine Learning in Real-world Fraud Cases
Lecture 25 Anomaly Detection in Fraud Analytics
Lecture 26 The Role of Big Data in Fraud Analytics
Lecture 27 Module Summary
Section 5: Case Studies and Comprehensive Fraud Detection Framework
Lecture 28 Introduction to this Module
Lecture 29 Case Study Analysis: Combining Behavioral Analysis and Fraud Analytics
Lecture 30 Building a Comprehensive Fraud Detection Process Framework
Lecture 31 Prevention Strategies using Behavioral Analysis and Fraud Analytics
Lecture 32 Implementing a Data-Driven Culture for Fraud Detection in an Institution
Lecture 33 Regulatory and Ethical Considerations in Fraud Detection
Lecture 34 Future of Fraud Detection: Trends and Challenges
Lecture 35 Module Summary
Section 6: Completing this Program
Lecture 36 Course Summary
Compliance and Risk Management Professionals: This group includes Compliance Officers and Risk Managers who ensure that the company is compliant with laws and regulations and manage potential risks. Understanding behavioural analysis and fraud analytics will enable them to identify, assess, and mitigate fraud risks more effectively.,Internal Auditors and Fraud Investigators: These professionals are directly involved in scrutinizing company activities and investigating any suspicious actions. Gaining advanced techniques in behavioural analysis and fraud analytics can significantly improve their ability to detect and prevent fraudulent activities.,Business Leaders: Including CEOs, CFOs, and department heads who need a comprehensive understanding of fraud risk, detection, and prevention mechanisms. The knowledge gained can guide them in strategic decision-making and implementing effective fraud detection and prevention frameworks within their departments.,IT and Data Professionals: These individuals handle the company's data and IT systems. Skills in fraud analytics can help them leverage data and machine learning for predictive modelling and anomaly detection, strengthening the company's overall fraud detection capabilities.
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