Suspicious Transaction Reporting (STR) - US

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Suspicious Transaction Reporting (STR) - US

Coursera · Beginner ·📊 Data Analytics & Business Intelligence ·3mo ago

Key Takeaways

Introduces Suspicious Transaction Reporting requirements in the US for anti-money laundering and counter-terrorist financing compliance

Original Description

Suspicious Transaction Reporting (STR) is a crucial component of anti-money laundering and counter-terrorist financing compliance, enabling financial institutions to detect and report activities that may indicate financial crime. This course provides a practical, scenario-driven introduction to STR requirements in the United States, with a focus on recognizing suspicious behavior, meeting regulatory obligations, and supporting effective compliance outcomes. You will learn the basics of suspicious activity and attempted transactions, understand how to apply the Reasonable Grounds to Suspect (RGS) threshold, and identify red flags using facts, context, and behavioral indicators. The course places special emphasis on MSB-specific warning signs and common patterns associated with money laundering and terrorist financing risks. Additionally, the course walks you through the end-to-end SAR filing process, including documentation standards, recordkeeping and retention requirements, and the importance of avoiding illegal customer tip-offs. Through concise readings, interactive activities, and realistic scenarios, you will build confidence in assessing activity, making reporting decisions, and applying STR principles consistently. Designed for frontline staff, compliance professionals, and AML teams, this course equips learners with the knowledge and practical skills needed to fulfill STR responsibilities effectively.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
What I Learned Reading Chapter 1 of “Designing Data-Intensive Applications” (2nd Edition)
Learn the importance of data distribution, trust, and responsibility in designing data-intensive applications
Medium · Data Science
📰
Do Countries Really Name Their Streets After the Same Handful of Heroes?
Explore how street names vary across cities using Python to analyze patterns and heroes' names
Medium · Python
📰
The Product Does Not Sell Itself: Why Commodity Businesses Need Loyalty Analytics
Commodity businesses need loyalty analytics to drive customer retention and growth, as the product alone is not enough to guarantee sales
Medium · Data Science
📰
Filters in Power BI
Learn to use filters in Power BI to refine report data and improve business insights
Dev.to · Seenivasan A
Up next
How to Use VLOOKUP and XLOOKUP in Excel | Step-by-step Guide
Jotform
Watch →