Red Flags and High-Risk AML Transactions: What Banking and Insurance Organizations Need to Watch
Live CPE Webinar • Monday, August 31, 2026 • 2 CPE Credits
Anti-Money Laundering compliance often fails in the same place that fraud detection fails:
The red flag was visible, but nobody recognized what it meant.
A suspicious transaction does not always look dramatic.
It may be:
A pattern of deposits just below reporting thresholds.
A customer using unusual identification.
A transaction inconsistent with the customer’s known business.
A policyholder who seems far more interested in surrender features than insurance protection.
A payment made by an unrelated third party.
An early policy termination that makes little economic sense.
A high-risk customer moving funds in ways that do not match expected activity.
The challenge is not simply knowing that red flags exist.
The challenge is knowing which ones matter, how to investigate them, and when they justify escalation or regulatory reporting.
Corporate Compliance Seminars’ Red Flags and High-Risk AML Transactions webinar is designed to help banking and insurance professionals develop exactly that skill. The live two-hour event is scheduled for Monday, August 31, 2026, and provides 2 CPE credits.
CCS focuses the program on money-laundering red flags, high-risk transactions, BSA requirements, CDD/KYC, AML alerts, fraud overlap, and suspicious activity reporting.
Red Flags Are Questions, Not Conclusions
One of the most important principles in AML compliance is this:
A red flag does not prove money laundering.
The FFIEC BSA/AML Manual expressly warns that the mere presence of a red flag is not itself evidence of criminal activity. Instead, it should trigger closer scrutiny to determine whether the activity is suspicious or lacks a reasonable business or legal purpose.
That is critical.
A strong AML professional does not see a $9,900 transaction and immediately conclude:
“Structuring.”
The professional asks:
What is the customer’s normal activity?
Are similar transactions occurring elsewhere?
What is the business purpose?
Is there a pattern?
Does the activity make economic sense?
What does the customer profile tell us?
AML is an evidence-based discipline.
Banking Example One: Structuring
Structuring remains one of the classic BSA red flags.
The FFIEC explains that a person may structure transactions across one or more financial institutions, one or more days, or in other ways for the purpose of avoiding reporting or recordkeeping requirements. But the FFIEC also cautions that multiple transactions below $10,000 do not automatically establish structuring; banks must review the surrounding facts and customer history.
Consider:
A business customer deposits:
$9,700 Monday
$9,850 Wednesday
$9,600 Friday
What should the bank do?
Not:
“Every deposit is below $10,000. No CTR issue.”
And not:
“Three deposits under $10,000. The customer is definitely structuring.”
Instead:
Investigate the pattern.
Ask:
Is this normal for the business?
Does the business generate significant cash?
Are similar deposits occurring at multiple branches?
Did the customer previously ask questions about reporting thresholds?
Are there related accounts?
The red flag starts the investigation.
It does not finish it.
Banking Example Two: Customer Activity Does Not Match the Profile
The FFIEC identifies numerous red flags involving customers whose transactions or background do not align with expected business activity, as well as customers who provide suspicious or incomplete identifying information.
Suppose a newly opened consulting company:
Claims to have very few employees.
Describes itself as providing local business consulting.
Begins receiving large international wires.
Immediately sends most of those funds to unrelated third parties.
The bank should ask:
Does the activity make sense for the stated business model?
That question lies at the heart of effective Customer Due Diligence.
Banking Example Three: The Customer Who Does Not Want to Explain the Business
The FFIEC specifically identifies reluctance to provide basic information about the nature and purpose of a business, expected account activity, officers, directors, or location as a potential red flag.
Imagine a business customer who:
Provides minimal ownership information.
Cannot clearly explain anticipated transactions.
Uses a complicated corporate structure.
Becomes irritated when the bank asks for beneficial ownership information.
None of these facts alone proves illicit activity.
Together, they may justify enhanced scrutiny.
Banking Example Four: High-Risk Activity Across Channels
Money launderers do not necessarily use one account, one branch, or one payment type.
Activity can move through:
Cash
Wires
ACH
Monetary instruments
Multiple accounts
Multiple branches
That means AML monitoring should not always analyze transactions one at a time.
Patterns matter.
The FFIEC’s current BSA/AML framework explicitly links customer risk, due diligence, and suspicious activity monitoring.
The question is not simply:
“Is this transaction unusual?”
It may be:
“Is the relationship unusual when viewed as a whole?”
Insurance AML Is Different—but the Risk Is Real
Insurance organizations do not face exactly the same AML exposure as banks.
FinCEN’s insurance AML rules apply to covered insurance products, particularly certain permanent life insurance policies, annuity contracts, and other products with cash-value or investment features. FinCEN requires covered insurance companies to maintain risk-based AML programs and report suspicious activity where appropriate.
That creates a different set of red flags.
Insurance Example One: The Customer Does Not Care About the Insurance
FinCEN specifically identifies as suspicious a customer who appears unconcerned about the investment performance of an insurance product but is highly interested in its early termination provisions.
That should trigger a basic question:
Why is this person buying the product?
Suppose a customer purchases a substantial cash-value policy.
During the sale, the customer asks little about:
Coverage
Beneficiaries
Investment returns
But repeatedly asks:
How soon can I surrender it?
How quickly can I receive the proceeds?
What penalties apply?
That is not proof of money laundering.
But it does not look like ordinary insurance behavior either.
Insurance Example Two: Early Termination at an Economic Loss
FinCEN also identifies early termination of an insurance product—especially when the customer accepts a financial penalty—as a potential AML red flag.
Why would someone willingly lose money?
One explanation could be that the customer values the ability to transform the funds more than the investment return.
Consider:
Customer purchases a covered product.
Customer pays a large premium.
Customer quickly surrenders the policy.
Customer accepts a surrender charge.
Proceeds emerge from a legitimate insurance company.
That deserves scrutiny.
Insurance Example Three: Unrelated Third-Party Payments
FinCEN highlights unusual payment methods and activity involving apparently unrelated third parties as potential suspicious activity.
For example:
A policy is owned by Customer A.
Premium payments come from Company B.
A surrender refund is directed to Person C.
The AML question becomes:
What is the relationship among these parties?
There may be a legitimate explanation.
The organization should understand it.
Insurance Example Four: Maximum Policy Loan Soon After Purchase
FinCEN specifically notes that a customer borrowing the maximum available amount soon after purchasing the insurance product may present a red flag.
Again, consider the economic logic.
If a customer purchases an insurance product and almost immediately extracts as much cash as possible, the transaction may warrant additional review.
The key is understanding whether the activity is consistent with the customer's:
Financial profile
Insurance objectives
Expected product use
Insurance Example Five: Reluctance to Provide Identifying Information
FinCEN also identifies customers who resist providing identifying information or provide minimal or seemingly fictitious information as potential red flags.
That should matter to insurers because a risk-based AML program depends on understanding who is involved in the transaction.
Insurance professionals should not simply think:
“We are not a bank, so KYC does not matter.”
Covered insurers need sufficient customer information to operate an effective AML program even though their regulatory framework differs from the bank Customer Identification Program structure.
Banking and Insurance Share the Same Core AML Questions
The products differ.
The core investigative logic is remarkably similar.
Ask:
Who is involved?
What activity is occurring?
Is it consistent with what we know about the customer?
Does it have a reasonable business or economic purpose?
Does the activity involve unusual parties, jurisdictions, timing, or payment methods?
Is there a pattern?
Does the activity require escalation?
That is the common thread.
Red Flags Need an Investigation Process
A mature AML system should move through a disciplined sequence:
Red Flag
↓
Alert
↓
Investigation
↓
Evidence
↓
Escalation
↓
Decision
↓
SAR Filing, if warranted
↓
Documentation
This is where many compliance systems fail.
Organizations may have excellent monitoring technology but weak investigation processes.
The result is:
Excessive alerts
Incomplete investigations
Poor documentation
Delayed escalation
Unsupported closure decisions
The CCS course specifically addresses managing AML alerts, investigations, suspicious activity, and regulatory reporting.
Policy Alone Is Not Enough
The FFIEC’s enforcement guidance makes an important point: simply having a written BSA/AML program is not enough. A bank can face problems when the program is not effectively implemented, particularly where deficiencies combine with suspicious activity, structuring, insider involvement, or systemic reporting failures.
This is an internal control lesson.
A written procedure saying:
“Investigate suspicious activity.”
does not establish that investigations are actually occurring.
The auditor or compliance professional should ask:
Show me.
Fraud and AML Are Closely Connected
Fraud generates proceeds.
Those proceeds frequently need to be moved, concealed, or converted.
That is why fraud and AML monitoring often overlap.
A customer involved in:
Business Email Compromise
Identity theft
Investment fraud
Healthcare fraud
Insurance fraud
may subsequently engage in transactions designed to move the proceeds.
AML professionals therefore need to understand fraud patterns as well as traditional money-laundering typologies.
CCS specifically includes the overlap between fraud and AML as a current compliance challenge.
Internal Audit Should Be Testing the AML Program
Internal Audit should not own AML compliance.
But it can ask hard questions about whether the program actually works.
For banking organizations:
Are high-risk customers identified?
Are customer profiles current?
Are transaction-monitoring rules reasonable?
Are alerts investigated timely?
Are structuring patterns identified?
Are SAR decisions documented?
For covered insurance organizations:
Has management identified the products subject to AML requirements?
Are relevant distribution channels included?
Are unusual policy transactions monitored?
Are suspicious surrender patterns investigated?
Are third-party payments evaluated?
Is the AML risk assessment current?
The control question is always:
Can management demonstrate that the program is operating as designed?
Human Judgment Still Matters
AML technology can identify patterns.
It cannot completely replace judgment.
A transaction may look suspicious statistically and be completely legitimate.
Another transaction may look ordinary individually but become suspicious when viewed in context.
That is why the FFIEC emphasizes understanding the surrounding circumstances and customer information when evaluating potential suspicious activity.
The analyst needs enough knowledge to ask:
Does this make sense?
AI Will Make AML Monitoring More Powerful—and More Complicated
Artificial intelligence can help financial organizations:
Identify unusual patterns
Prioritize alerts
Analyze large populations
Connect customer relationships
Detect anomalies
But AI creates control questions too:
Is the model producing excessive false positives?
What activity could it miss?
Who validates the model?
How are model changes controlled?
Can investigators explain why an alert was generated?
Automation should improve professional judgment.
It should not eliminate accountability.
What Participants Will Learn
Corporate Compliance Seminars’ Red Flags and High-Risk AML Transactions program covers key areas including AML/BSA fundamentals, sophisticated red flags, structuring and layering, high-risk transactions, CDD and KYC, regulatory reporting, AML alerts and investigations, fraud overlap, and current compliance challenges.
The program is designed to provide practical tools that attendees can immediately apply when analyzing suspicious activity.
Who Should Attend?
The program is particularly relevant for:
Banking professionals
Insurance professionals involved with covered insurance products
BSA Officers
AML professionals
Compliance Officers
Internal Auditors
Fraud investigators
Risk professionals
Finance professionals involved in AML controls
The program provides 2 CPE credits and focuses on practical identification and management of high-risk AML transactions.
The Bottom Line
Banks and insurance companies face different AML exposures.
But both need professionals who can look at a transaction and ask:
Does this make sense?
Then go further:
What do we know about this customer?
Is there a pattern?
What risk does this behavior suggest?
What additional information do we need?
Should this activity be escalated?
The biggest AML failure is not necessarily missing a transaction.
It can be seeing the red flag and failing to understand what it means.
Join Corporate Compliance Seminars on Monday, August 31, 2026, for Red Flags and High-Risk AML Transactions and strengthen your ability to identify, investigate, document, and escalate suspicious financial activity across both banking and insurance environments.
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