Description
MRC Members receive exclusive pricing when accessed through the member portal.
Step into the future of eCommerce fraud fighting with our course on Machine Learning for Fraud Prevention. Designed for fraud and risk professionals in the digital age, this course offers a deep dive into the essentials of machine learning (ML) and its pivotal role in combating card-not-present fraud. You'll learn to define machine learning, differentiate various model types, and understand their specific applications in fraud management. Additionally, you'll learn about model scores, including the distinction between raw and calibrated scores, and how to set decision thresholds. This course shows how machine learning can be combined with rules and manual review for optimal decision-making in fraud prevention. Ideal for those looking to harness the power of machine learning in securing eCommerce platforms.
Who Should Enroll?
- Fraud prevention professionals looking to integrate machine learning techniques into their fraud-fighting strategies.
- Risk management professionals seeking advanced methods to identify and mitigate potential fraud risks.
- Data analysts and scientists interested in applying their expertise to detect and prevent fraud through machine learning models.
- Financial and payment professionals seeking to improve their knowledge of advanced fraud prevention techniques.
- This course may also benefit eCommerce business owners and managers, IT and security professionals, and compliance officers in digital retail.
Program Details
Program Level: Basic
Program Field of Study: Specialized Knowledge
Program Delivery Method: QAS Self Study
CPE Credits: 2.5
Advanced Preparation and/or Pre-requisites: None
For more information regarding any concerns, please email us at [email protected].
Refunds and cancellations are determined on a case-by-case basis. Cancellations and requests for refunds must be communicated in writing to [email protected]. Refunds will not be issued once a course has been started. Additionally, courses must be completed within one year of purchase.
Merchant Risk Council is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org
Course Created: 01/23/2023
Updated: 06/12/2024
Objectives
- Define machine learning
- Distinguish types of models and their applications in fraud management
- Compare and contrast the advantages and disadvantages between the traditional approach to fraud fighting and machine learning
- Convert data into features that a model can use
- List methods to label transactions as fraudulent or not
- Deconstruct the components of a model
- Identify key metrics for evaluating machine learning models
- Examine common types of drift that can impact a model's performance
- Define model scores
- Differentiate between raw scores and calibrated scores
- Explain decision thresholds
- Summarize how thresholds can be combined with rules and manual review to make decisions
Certificate
By completing/passing this course, you will attain the certificate MRC Education Certificate of Completion
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