What you'll get
  • 5+ Hours
  • 3 Courses
  • Course Completion Certificates
  • Self-paced Courses
  • Technical Support
  • Case Studies

Synopsis

  • Fundamentals of fraud and its types in financial and organizational settings
  • Techniques to detect and analyze fraudulent transactions
  • Use of Business Intelligence (BI) tools for fraud analysis
  • Applying data science methods to identify fraud patterns
  • Developing effective fraud detection and prevention strategies
  • Understanding end-to-end fraud detection processes
  • Practical skills to mitigate financial and credential-based fraud

Content

Courses No. of Hours Certificates Details
Fraud Analytics using R & Microsoft Excel2h 34m✔View Curriculum
Machine Learning Project #5 - Fraud Detection in Credit Payments1h 51m✔View Curriculum
Machine Learning Project #4 - Banking and Credit Frauds44m✔View Curriculum

Description

This Fraud Analytics course provides a comprehensive understanding of detecting, analyzing, and preventing fraudulent activities using data-driven techniques. Participants will learn how to identify illegitimate transactions in financial organizations, businesses, and personal accounts, distinguishing them from legitimate ones.

The course covers the application of quantitative methods, business intelligence (BI), and data science to identify fraud patterns and develop effective detection solutions. Learners will explore the end-to-end fraud detection process, including identifying suspicious activities, analyzing data, and implementing strategies to prevent unauthorized access to money or sensitive information.

By the end of the course, participants will gain practical skills to detect, analyze, and prevent fraud in businesses and financial systems using modern tools and techniques.

Sample Certificate

Course Certification

Requirements

  • Basic knowledge of finance, accounting, or business processes

  • Familiarity with data analysis concepts

  • Knowledge of Excel or any data management tool is helpful

  • Interest in fraud detection and risk management.

Target Audience

  • Students and professionals interested in fraud detection and analytics

  • Finance, banking, and accounting professionals

  • Data analysts and business intelligence professionals

  • Risk management and compliance officers

  • Individuals aiming for a career in fraud detection and prevention