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Free Download AI For Fraud Detection And Suspicious Transaction Monitoring
Published: 3/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.25 GB | Duration: 4h 55m
AI in Banking Security - 10 Banks and 8 technology AI solutions covered.
What you'll learn
Understand the importance of transaction monitoring and suspicious activity detection in banking.
Explore how AI enhances transaction monitoring systems in financial institutions.
Risk Indicators, Regulations, and Compliance
Understand the role of Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations in transaction monitoring.
AI and Machine Learning in Fraud Detection
Get hands-on insights into the implementation of a neural network fraud detection model.
Transaction Types and AI Solutions
Study successful AI use cases from HSBC, JPMorgan Chase, Standard Chartered Bank, Danske Bank, ING Bank, DBS Bank, ICICI Bank, China Construction Bank (CCB) etc
Requirements
Basic Finance & Banking Knowledge
Description
The financial industry faces an ever-growing challenge in detecting and preventing fraudulent transactions and money laundering activities. With the rapid advancements in artificial intelligence (AI), banks and financial institutions are now leveraging AI-driven solutions to enhance transaction monitoring, detect suspicious activities, and comply with regulatory frameworks. This course, AI for Fraud Detection and Suspicious Transaction Monitoring in Banking, is designed to provide a comprehensive understanding of AI applications in financial fraud detection, covering key concepts, methodologies, and real-world case studies from leading global banks.The course begins with an Introduction, providing an Overview of fraud detection and the Importance of Transaction Monitoring & Suspicious Activity in banking. It explores the Challenges in Traditional Suspicious Activity Detection, highlighting the limitations of conventional fraud detection systems and the need for AI-driven solutions. Learners will gain insights into How AI Enhances Transaction Monitoring Systems, improving accuracy and reducing false positives.A key focus of this course is on Key Risk Indicators (KRIs) and Red Flags in Transactions, which help financial institutions identify potential fraudulent activities. The course further delves into the Role of Know Your Customer (KYC) and Anti-Money Laundering (AML) Regulations, with a detailed examination of Regulatory Frameworks such as FATF, FinCEN, and GDPR. Learners will explore AI-Driven KYC and AML Solutions in Financial Institutions, studying successful implementations in the industry.The course also covers Key NLP Techniques in Financial Transaction Monitoring, Anomaly Detection Algorithms (Supervised vs. Unsupervised Learning), and Neural Networks and AI Models for Fraud Detection. Practical implementation is emphasized through an Implementation Guide for Deploying a Neural Network Fraud Detection Model and Data Collection & Preprocessing for AI Models.A specialized section on Types of Transactions in Banks and the Role of AI explains why trade transactions are closely monitored and how AI enhances surveillance. It examines the High Volume of Transactions & AI Solutions, The Complexity of Financial Instruments & AI Solutions, and how AI helps in Detecting Emerging Financial Crimes.The course also addresses Regulatory Complexity & AI Solutions, Adaptability to Existing Legacy Systems, and Security & Data Privacy Issues. With rapidly developing AI technologies, banks face challenges in implementation, and the course discusses Resource Restrictions & AI Solutions to navigate these issues.The course features in-depth Real-World Case Studies, showcasing AI-driven fraud detection solutions in leading global banks, including HSBC, JPMorgan Chase, Standard Chartered Bank, Danske Bank, ING Bank, DBS Bank, ICICI Bank, China Construction Bank (CCB), Mitsubishi UFJ Financial Group (MUFG), and Hang Seng Bank. These case studies highlight how these financial institutions successfully deploy AI in combating financial fraud, money laundering, and trade-based money laundering (TBML).By the end of the course, learners will gain a strong understanding of AI's role in fraud detection and transaction monitoring, equipping them with the knowledge to implement AI-driven solutions in banking and finance. The course is ideal for banking professionals, compliance officers, data scientists, and AI enthusiasts looking to enhance their expertise in AI-powered fraud detection.
Banking and Finance Professionals,Fraud Analysts & Risk Managers,Compliance Officers & AML/KYC Specialists,Banking Executives & Decision-Makers,Data Scientists & AI Practitioners,Machine Learning Engineers & AI Developers,Data Analysts & Financial Data Scientists,Cybersecurity Analysts,Financial Crime Investigators,FinTech Professionals & AI Consultants,IT Architects & System Integrators,Finance, AI, and Cybersecurity Students,Researchers in Financial AI
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