Mr. Sanctions

Category: Enforcement

  • What did Exodus Movement agree to do with its compliance program?

    Based on the OFAC enforcement release and settlement agreement regarding Exodus Movement, Inc., here is a summary of the Compliance Commitments (often found in Section 2 or labeled as a specific point in the agreement terms):

    • Sanctions Compliance Program: Exodus agrees to maintain a comprehensive sanctions compliance program for at least five years.
    • Management Commitment: The company will ensure senior management support and the provision of adequate resources to the compliance function.
    • Risk Assessment: Exodus will conduct periodic risk assessments to identify and mitigate sanctions risks specific to its business.
    • Internal Controls: The company must implement and maintain written policies and procedures, including effective sanctions screening (such as IP blocking/geoblocking) and escalation protocols for potential matches.
    • Testing and Audit: Exodus is required to perform independent testing and audits to ensure the effectiveness of its compliance program.
    • Training: The company commits to providing regular (at least annual) sanctions compliance training to relevant employees.
    • Compliance Investment: Exodus has specifically agreed to invest $630,000 in additional sanctions compliance controls and measures.
    • Reporting: A senior executive must submit annual certifications to OFAC for a period of five years, confirming that the company is meeting these compliance obligations.

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  • December 16, 2025: OFAC Settles with Exodus Movement

    What Happened

    Exodus Movement, Inc. (“Exodus”), a U.S. company that makes software wallets for digital assets, has agreed to pay $3,103,360 to settle potential violations of U.S. sanctions against Iran.

    Between October 2017 and January 2019, Exodus allowed users in Iran to use its software to manage and trade digital currency. While Exodus didn’t process the trades itself (it used third-party partners), it earned fees from the transactions.

    The main issue was that Exodus staff knew some users were in Iran—a sanctioned country—but helped them anyway. When Exodus’s partners blocked these users to comply with the law, Exodus customer support told the users to use a VPN (Virtual Private Network) to hide their location and bypass the blocks. All of this happened even though Exodus’s own rules said people in sanctioned countries couldn’t use the app, but the company didn’t have a real system in place to check or stop them.

    The Penalty

    Exodus agreed to pay $3,103,360 to resolve the matter. The total maximum possible penalty was much higher, but the final amount was reduced because Exodus cooperated and fixed the problems.

    Breakdown of Violations

    There were 254 total violations, split into two types:

    • 12 Egregious Violations: These were the most serious cases where staff actively helped users evade sanctions. The base penalty for these was calculated at the legal maximum, totaling $4,532,400.
    • 242 Non-Egregious Violations: These were the standard transaction violations where users in Iran simply used the wallet without specific evasion advice.

    Aggravating and Mitigating Factors

    OFAC determined the final penalty by weighing “Aggravating Factors” (bad behavior that raises the fine) against “Mitigating Factors” (good behavior that lowers the fine).

    Aggravating Factors

    • Helping users trick the system
      • General Factor A: Willful or Reckless Violation of Law
      • Exodus staff knew their partners had blocked Iranian users for legal reasons but willfully advised those customers to use VPNs to get around the security controls.
    • Management knew about the risks
      • General Factor A: Awareness of Conduct
      • Company leadership and staff were generally aware of U.S. sanctions and knew that their partners were restricting access to Iran, but they continued to support these users anyway.
    • Undermining the purpose of sanctions
      • General Factor D: Harm to Sanctions Objectives
      • By helping people in a sanctioned country trade digital assets, Exodus defeated the purpose of the sanctions (which is to block access to the U.S. financial system) and sabotaged the compliance work of its partners.

    Mitigating Factors

    • Clean track record
      • General Factor B: Administrative License; Prior Notice of Penalty or Penalty
      • Exodus has not received a penalty notice or a finding of violation from OFAC in the five years preceding the earliest date of the transactions.
    • Fixing the compliance program
      • General Factor F: Remedial Response
      • Exodus took serious steps to prevent this from happening again, including installing software to block users from sanctioned regions (geo-blocking) and training its staff on compliance rules.
    • Cooperating with investigators
      • General Factor G: Cooperation with OFAC
      • Exodus worked closely with OFAC during the investigation, providing documents and information that helped resolve the case efficiently.

    What are the Takeaways?

    Compliance Considerations

    • Start Early: Companies, especially startups in fintech and crypto, must build sanctions compliance into their business model from day one, not wait until they are large.
    • Don’t Help Evasion: Customer support staff should never advise users on how to bypass security controls (like suggesting VPNs). This is considered a willful violation.
    • Technology Matters: Simply having “Terms of Use” that ban sanctioned users is not enough; companies need technical controls (like IP blocking) to actually stop them.
    • Check Your Partners: If you rely on other companies (like exchanges) to provide services, ensure your compliance standards match theirs so you don’t become a loophole.

    Other resources

    For more information on how to set up a proper compliance program, OFAC recommends reviewing:

    • A Framework for OFAC Compliance Commitments: A guide on the five essential parts of a sanctions compliance program.
    • Sanctions Compliance Guidance for the Virtual Currency Industry: Specific instructions for crypto companies on how to follow U.S. sanctions laws.

    Mr. Sanctions’ Note: This settlement required some tweaking of the prompt I use to produce these summaries for the non-expert. This was for two reasons:

    • The fact that there were both egregious and non-egregious violations caused the original prompt to treat everything as non-egregious. As revised, the summary now shows the effect on the base penalty of those egregious items.
    • Probably at least partly due to the previous point, the aggravating factors list included two separate, but related, items: willful behavior in the case of the egregious violations, and reckless behavior with regard to the rest.

    Even with this, Gemini missed the (admittedly minor) mitigating factor of not having a recent enforcement history. Luckily, when I told it that it had missed it and that it should be added back, it did so.

    BTW, here are the Enforcement Release:

    20251216_exodusDownload

    and the Settlement Agreement (which you get pretty rarely – generally only when there is egregious conduct):

    20251216_exodus_settlementDownload

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  • Can you be worse than terse?

    My Business Writing professor said you couldn’t, but I don’t know. I asked Gemini to produce a summarized version of the OFAC Enforcement Guidelines, and this is what I got back:

    This document acts as the “Sentencing Guidelines” for violating U.S. economic sanctions (OFAC rules). If you or your company trade with a banned country, terrorist, or sanctioned entity, this guide dictates your punishment.

    Here is the condensed version of how it works:

    1. The Spectrum of Punishment

    When you break the rules, the outcome ranges from a slap on the wrist to a major blow:

    • No Action: They drop the case.
    • Cautionary Letter: A formal warning (“Don’t do it again”).
    • Finding of Violation: A permanent mark on your record, but no money is owed.
    • Civil Monetary Penalty: You are fined cash.

    2. The “Scorecard” for Fines

    If they decide to fine you, they don’t pick a random number. They use a formula:

    • Base Fine: They start with a standard amount based on the dollar value of the illegal transaction.
    • Adjustments: They raise or lower that amount based on General Factors:
      • Fine Increases: If you did it on purpose (willful), were reckless, tried to hide it, or have a history of breaking rules.
      • Fine Decreases: If you cooperated, had a compliance program in place to stop it (but it failed), and took immediate steps to fix the error.

    3. The “Golden Rule” (Voluntary Self-Disclosure)

    This is the most critical part of the document. If you find your own mistake and tell the government about it before they catch you, your base penalty is automatically cut in half (50% off).

    The Bottom Line:

    OFAC treats honest mistakes much differently than reckless law-breaking. If you mess up: Confess early, cooperate fully, and fix the problem to minimize your penalty.

    So, I thought some important detail was missing, so I modified the prompt a few times:

    Summarize https://www.ecfr.gov/current/title-31/subtitle-B/chapter-V/part-501/appendix-Appendix%20A%20to%20Part%20501 in layperson-friendly terms. Include discussion of the penalty process, the General Factors which go into the calculation of the penalty, including any subcategories under each General Factor, and the Penalty Grid, which is based on egregiousness of the conduct and voluntary self-disclosure. Include the entire Applicable Schedule Amount table, and the current statutory maximum fines under TWEA, IEEPA, and the Kingping Act. Include a short introduction, and a short section of takeaways.

    and got back the following:

    Here is a summary of Appendix A to Part 501 of Title 31 (Economic Sanctions Enforcement Guidelines), broken down into layperson-friendly terms.

    Introduction

    This document is the official “rulebook” used by the Office of Foreign Assets Control (OFAC)—the agency that enforces U.S. sanctions (like those against Iran, Russia, or terrorist groups). It explains exactly how the government decides on the punishment when an individual or company violates these sanctions. It is designed to make penalties predictable, consistent, and transparent.

    The Penalty Process

    When OFAC suspects a violation, they follow a formal legal process. They do not simply send a bill; you have opportunities to explain yourself.

    1. Investigation: OFAC gathers evidence, often by issuing a subpoena (a legal demand for documents) or by reviewing a voluntary self-disclosure you submitted.
    2. Initial Determination: OFAC reviews the facts and chooses an outcome:
      • No Action: The case is dropped.
      • Cautionary Letter: A formal warning. No fine is issued, but you are told to fix your compliance mistakes.
      • Finding of Violation: A formal record that you broke the law, but without a monetary fine.
      • Civil Monetary Penalty: A cash fine.
    3. Pre-Penalty Notice: If they choose to fine you, they send this notice first. It explains what you did wrong and the proposed fine amount.
    4. Response: You usually have 30 days to reply. You can argue that you are innocent or admit the mistake and argue for a lower fine based on the “General Factors” (see below).
    5. Final Penalty Notice: After reading your response, OFAC issues the final fine.
    6. Settlement: At almost any stage, you can negotiate a settlement to resolve the case (usually for a lower amount) without going through the full legal fight.

    General Factors (The “Scorecard”)

    OFAC uses these factors to judge how “bad” the violation was. These are the levers that raise or lower your penalty.

    A. Willful or Reckless Violation of Law (Intent)

    • Willfulness: Did you know it was illegal and do it anyway?
    • Recklessness: Were you careless? Did you ignore red flags?
    • Concealment: Did you try to hide the evidence?
    • Pattern of Conduct: Was this a one-time accident or a habit?
    • Management Involvement: Did senior managers know?

    B. Awareness of Conduct (Knowledge)

    • Actual Knowledge: Did you know the transaction was happening?
    • Reason to Know: Should you have known? Was the info readily available?

    C. Harm to Sanctions Program Objectives (Impact)

    • Economic Benefit: Did money or goods actually reach the sanctioned target?
    • Implications for U.S. Policy: Did your action embarrass the U.S. or help an enemy?
    • License Eligibility: If you had just asked for permission first, would OFAC have said “yes”? (If so, the harm is lower).

    D. Individual Characteristics

    • Commercial Sophistication: Are you a large, global bank (held to a high standard) or a small local business?
    • Size & Financial Condition: Can you afford the fine?
    • Sanctions History: Have you been in trouble with OFAC in the last 5 years?

    E. Compliance Program

    • Did you have an internal system (software/rules) to prevent this?
    • Was that system appropriate for your company’s size?

    F. Remedial Response (Fixing It)

    • Did you stop the violation immediately?
    • Did you investigate yourself to find the root cause?
    • Did you implement new controls to ensure it never happens again?

    G. Cooperation with OFAC

    • Voluntary Self-Disclosure: Did you turn yourself in? (This is the most critical factor).
    • Responsiveness: Did you answer OFAC’s questions quickly and honestly?
    • Tolling Agreements: Did you agree to extend the statute of limitations to give OFAC more time?

    H. Timing: How long ago did this happen?

    I. Other Enforcement: Did another agency (like a banking regulator) already fine you?

    J. Future Compliance: Will a fine here serve as a good deterrent for others?

    The Penalty Grid

    OFAC calculates the “Base Penalty” using a matrix based on two questions:

    1. Was the conduct Egregious (severe/willful)?
    2. Did you Voluntarily Self-Disclose (confess)?
    ScenarioDefinitionBase Penalty Calculation
    1. Non-Egregious + DisclosedYou made a mistake and told OFAC yourself.50% of the Transaction Value (Capped at $188,850 per violation).*
    2. Non-Egregious + No DisclosureYou made a mistake, but OFAC caught you.The “Applicable Schedule Amount” (See table below).
    3. Egregious + DisclosedYou did it on purpose, but you confessed.50% of the Statutory Maximum.
    4. Egregious + No DisclosureYou did it on purpose and OFAC caught you.The Statutory Maximum.

    *Note: For very small violations in Scenario 1, the penalty is capped at much lower amounts based on the schedule.

    Applicable Schedule Amount Table

    This table is used for Non-Egregious cases (mistakes) where you did not voluntarily disclose. The fine is based on the value of the illegal transaction.

    Transaction ValueApplicable Schedule Amount (Base Penalty)
    Less than $1,000$1,000
    $1,000 to $10,000$10,000
    $10,000 to $25,000$25,000
    $25,000 to $50,000$50,000
    $50,000 to $100,000$100,000
    $100,000 to $200,000$200,000
    $200,000 or moreThe Statutory Maximum (See below)

    Current Statutory Maximum Fines (2025)

    For “Egregious” cases (or high-value non-egregious cases), the penalty is the “Statutory Maximum.” These amounts are adjusted annually for inflation. As of January 15, 2025, the maximums per violation are:

    • IEEPA (International Emergency Economic Powers Act): The greater of $377,700 or twice the value of the transaction. (This covers most sanctions programs like Iran, Russia, and Terrorism).
    • TWEA (Trading With the Enemy Act): $111,308. (Primarily covers Cuba).
    • Kingpin Act (Foreign Narcotics Kingpin Designation Act): $1,876,699.

    Takeaways

    • Honesty Saves Money: Voluntarily self-disclosing a violation automatically cuts the base penalty calculation in half.
    • Intent is Expensive: The difference between “Egregious” (reckless) and “Non-Egregious” (mistake) is massive—often the difference between a $10,000 fine and a multi-million dollar fine.
    • Compliance is a Shield: Even if you fail, having a compliance program in place lowers your penalty under the “General Factors.”
    • Cooperate: Hiding documents or delaying the investigation is considered “Concealment” and will dramatically increase your fine.

    Depending on what level of detail you need for your role, you may be able to deal with the ultra-condensed version. But it’s a cautionary tale about asking AI tools to summarize without knowing the source material and knowing what you want to see come back. And I suspect the Goldilocks result is really a combination of the two responses… but that’s just me.

    What do you think?

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  • The OFAC Enforcement road less traveled

    Many of us, if not most of us, skip the part of the Federal Register that explains why the Enforcement Guidelines (the eCFR version is much easier on the eyes) came to be, and the comment period prior to its publication. Here’s a simplified version of those sections from the Federal Register version:

    1. Background

    Why was this document written?

    The Office of Foreign Assets Control (OFAC) enforces economic sanctions (punishments) against foreign countries, terrorists, and drug traffickers to protect U.S. national security.

    • The Catalyst: In 2007, the President signed a new law (the IEEPA Enhancement Act) that drastically increased the maximum fines for breaking sanctions rules. Because the potential fines became so much higher, OFAC needed to create a clear, written set of rules explaining exactly how they decide whether to fine someone and how much that fine should be.
    • The History: OFAC had tried to create these guidelines before (proposing versions in 2003 and 2006). In 2008, they published a temporary (“interim”) version of these rules. This document is the final version, incorporating feedback they received from the public and industry groups.

    2. Comments and Responses

    After publishing the temporary rules in 2008, OFAC received feedback from banks, trade groups, and lawyers. Here is a summary of what those groups asked for (“Comments”) and how OFAC answered (“Responses”).

    A. Voluntary Self-Disclosure (Confessing)

    • Comment: Industry groups wanted OFAC to clearly define what counts as “voluntarily” telling on yourself. They also wanted to know exactly how much “credit” they would get for it.
    • Response: OFAC clarified the definition. Most importantly, they confirmed that if you genuinely confess a violation before the government finds out, your base penalty will be reduced by 50%. They view this as a major incentive for honesty.

    B. Risk-Based Compliance (Internal Rules)

    • Comment: Companies asked OFAC to clarify what a “good” compliance program looks like. They were worried they would be punished for not having a perfect system, even if they were a small business.
    • Response: OFAC agreed that “one size does not fit all.” A small charity doesn’t need the same complex software as a global bank. OFAC said they will judge a company’s compliance program based on its specific size and risk profile.

    C. Cooperation

    • Comment: Commenters wanted to know if they would get credit for cooperating with an investigation even if they didn’t turn themselves in (voluntary self-disclosure).
    • Response: Yes. OFAC added a specific point stating that substantial cooperation—like quickly providing documents or signing agreements to extend deadlines—can lower your fine, even if you didn’t confess first.

    D. Determining the Fine (Penalty Calculation)

    • Comment: Many people were confused about how OFAC calculates the “value” of a transaction to set the fine (e.g., if a bank processes a $100 illegal check, is the value $100?).
    • Response: OFAC kept its method but provided more clarity. Generally, the fine is based on the dollar value of the illegal transaction. They also clarified that they distinguish between “egregious” (reckless/bad) cases and simple mistakes. Egregious cases get much higher fines.

    E. Sanctions History (Your Permanent Record)

    • Comment: Companies were worried that a mistake they made 20 years ago would count against them today.
    • Response: OFAC agreed to a limit. They stated that, generally, they will only look at your “Sanctions History” for the last 5 years. If you haven’t had a violation in 5 years, a new mistake is treated as a “first offense” (which gets a lower penalty).

    F. Foreign Laws and Secrecy

    • Comment: Global companies pointed out that some foreign countries have laws that make it illegal to share customer data with the U.S. government. They feared being fined by OFAC for failing to provide information that was legally blocked abroad.
    • Response: OFAC said they will consider this on a case-by-case basis. However, they expect companies to try their hardest to get the information to OFAC legally. You can’t just use foreign laws as an easy excuse to hide information.

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  • December 9, 2025: Settlement Agreement between the U.S. Department of the Treasury’s Office of Foreign Assets Control and An Individual

    The OFAC Recent Actions notice included the following Enforcement Release, simplified and reimagined:

    What Happened

    A U.S. individual, referred to as “U.S. Person-1,” has agreed to pay a settlement of $1,092,000 to resolve civil liability for alleged violations of sanctions related to Ukraine and Russia.

    • Who: The individual is an attorney and former U.S. government official.
    • When: The violations occurred between 2018 and 2022.
    • What: U.S. Person-1 served as the fiduciary (a person entrusted to manage assets) for a family trust belonging to a sanctioned Russian oligarch.
    • The Issue: By managing this trust, the individual provided services and dealt in property linked to the sanctioned oligarch, which is prohibited under U.S. sanctions laws.

    The Penalty

    The total settlement amount is $1,092,000. The maximum possible penalty for these violations was over $6.2 million, but the final amount was determined by analyzing specific aggravating and mitigating factors.

    Aggravating and Mitigating Factors

    • Aggravating Factors (Reasons the penalty was higher):
      • Ignoring Warning Signs despite Legal Advice:
        • General Factor: Reckless Disregard / Reason to Know
        • Explanation: Although the individual sought legal advice, they should have realized that the continued involvement of the oligarch’s “Proxy” meant the oligarch still controlled the trust. Relying on legal advice was not a sufficient excuse when obvious signs of control were present.
      • Undermining the Purpose of Sanctions:
        • General Factor: Harm to Sanctions Objectives
        • Explanation: The individual’s actions allowed a sanctioned Russian oligarch to continue accessing the U.S. financial system. This gave the trust an “air of legitimacy” and allowed its assets to grow significantly, directly countering the goal of the sanctions.
    • Mitigating Factors (Reasons the penalty was lower):
      • Clean Disciplinary Record:
        • General Factor: No Prior OFAC Actions
        • Explanation: The individual had not received a penalty or finding of violation from OFAC in the five years leading up to these events.
      • Helping the Investigation:
        • General Factor: Cooperation
        • Explanation: The individual provided “substantial cooperation” to OFAC during the investigation.

    Penalty Basis

    The final penalty amount reflects OFAC’s decision that while the violations were not voluntarily self-disclosed (the person didn’t turn themselves in), the case was non-egregious (not the most serious type of violation).

    What are the Takeaways?

    • Gatekeepers are at High Risk: Professionals who manage money or legal structures—like attorneys, accountants, and investment advisors—are “gatekeepers.” They are at high risk of being used by sanctioned individuals to hide assets and evade the law.
    • Paperwork isn’t Enough: Sanctions laws look at the “practical and economic realities,” not just legal formalities. Even if a trust looks independent on paper, if a sanctioned person really controls it, it is blocked.
    • Strict Liability: You can be fined even if you didn’t intend to break the law. “Well-meaning” professionals can inadvertently break sanctions if they don’t guard against these risks carefully.
    • Know Your Risk: U.S. persons in the trust and corporate services industry must thoroughly understand sanctions risks. If a sanctioned person is (or was) involved in a structure, extra caution is required.

    The usual “Other resources”

    • OFAC Resources: The Office of Foreign Assets Control provides guidelines, FAQs, and search tools (like the SDN List) to help individuals and businesses check if they are dealing with sanctioned parties.
    • Contacting OFAC: If you are unsure about a transaction or a client’s status, you can contact OFAC directly for guidance or apply for a specific license to authorize certain activities.

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  • How did it do it?

    Lastly, I asked Gemini to tell me what it decided to do, given the broad guidelines I gave it:

    Here is the explanation of the calculation methods used for each of the six factors. These methods combine the logic you provided (tiers, ratios, and comparisons) into a consistent scoring algorithm.

    Overview: The Tiered Weighting System

    Before calculating individual factors, every “General Factor” mentioned in an enforcement action is assigned a weight based on its importance tier. This ensures that matching on “Willfulness” (Tier 1) counts for more than matching on “Future Compliance” (Tier 4).

    • Tier 1 (High Weight): Factors A (Willful/Reckless), B (Awareness/Management), C (Harm to Sanctions Program).
    • Tier 2 (Medium-High Weight): Factors D (Individual Characteristics), E (Compliance Program).
    • Tier 3 (Medium Weight): Factors F (Remedial Response), G (Cooperation).
    • Tier 4 (Low Weight): Factors H, I, J, K (Other factors like timing, penalties, etc.).

    Factor 1: Generalized Behaviors

    How similar are the specific actions taken by the violators?

    This factor uses a Weighted Ratio Calculation:

    1. Identify Behaviors: We list the generalized behaviors for both the Target and the Comparison Action (e.g., “Wire Stripping,” “Ignoring Subpoena,” “Screening Failure”).
    2. Tier Assignment: Each behavior is linked to the General Factor it represents (e.g., “Ignoring Subpoena” = Factor A/Tier 1; “Screening Failure” = Factor E/Tier 2).
    3. Scoring Matches:
      • If a behavior appears in both actions: Add Positive Points (Weighted by Tier).
      • If a behavior appears in only one action: Add Negative Points (Weighted by Tier).
    4. Ratio Adjustment: We calculate the percentage of total behaviors that match.
      • Formula: (Count of Matching Behaviors / Total Distinct Behaviors).
      • If the ratio is high (e.g., 60%+), the final score is boosted. If low (e.g., 30%), the score is penalized.

    Example: Matching on “Willful Disregard” (Tier 1) provides a massive score increase. Matching on “No Sanctions Software” (Tier 2) provides a moderate increase.

    Factor 2: Aggravating Factors

    How similar are the reasons OFAC cited for increasing the penalty?

    This follows the same Weighted Ratio Calculation as Factor 1, but specifically for the aggravating factors listed in the enforcement release (e.g., “Reckless disregard,” “Management knowledge,” “Large entity”).

    1. Comparison: Compare the list of Aggravating Factors in the Target vs. the Comparison Action.
    2. Weighting: Apply the Tier weights (A-C get highest points).
    3. Ratio: Calculate the Match / Total ratio.
      • Goal: A high score here means both violators aggravated the situation in the same way (e.g., both involved senior management).

    Factor 3: OFAC Penalty Grid Placement

    Are the cases legally classified the same way?

    This factor uses a “Waterfall” Logic Tree. It does not use weights or ratios; it assigns a fixed score based on where the cases fall on the standard OFAC 2×2 Penalty Matrix (Egregious/Non-Egregious vs. VSD/Non-VSD).

    1. Check for Exact Quadrant Match:
      • IF Target Quadrant == Comparison Quadrant: Score = Highest (100%)
    2. Check for “Egregious” Alignment:
      • ELSE IF both are Egregious: Score = High (80%)
    3. Check for “Non-VSD” Alignment:
      • ELSE IF both are Non-Voluntarily Self-Disclosed: Score = Medium-High (60%)
    4. Check for “Non-Egregious” Alignment:
      • ELSE IF both are Non-Egregious: Score = Medium-Low (40%)
    5. Check for “VSD” Alignment:
      • ELSE IF both are Voluntarily Self-Disclosed: Score = Low (20%)
    6. No Match:
      • ELSE: Score = Lowest (0%)

    Factor 4: Cooperation

    Did both parties cooperate (or fail to cooperate) to the same degree?

    This factor is a Dependent Variable. It relies on the calculation of Factor 1.

    1. Determine Cooperation Level: Label both actions as either “Substantial Cooperation” or “Lack of Cooperation” (excluding Voluntary Self-Disclosure, which is handled in Factor 3).
    2. Check for Match:
      • IF both are “Substantial Cooperation” OR both are “Lack of Cooperation”: Match = True.
      • ELSE: Match = False.
    3. Calculate Score:
      • IF Match = True: Take the raw score calculated for Factor 1 and multiply by 0.70.
      • IF Match = False: Score is 0 or negative.

    Why this matters: This ensures that “Cooperation” is weighted heavily but is always slightly less influential than the core “Behavior” (Factor 1).

    Factor 5: Period of Time

    Did the violations last for a similar duration?

    This factor uses a Tiered Proximity Score.

    1. Assign Time Tiers:
      • Long: > 3 Years
      • Medium: 1 to 3 Years
      • Short: < 1 Year
    2. Compare Tiers:
      • IF Target Tier == Comparison Tier: Score = Highest (e.g., both are Medium duration).
      • ELSE IF Tiers are Adjacent (e.g., Medium vs. Long): Score = Intermediate.
      • ELSE (e.g., Short vs. Long): Score = Lowest.

    Factor 6: Mitigating Factors

    Did both parties receive credit for the same mitigating behaviors?

    This uses the Weighted Ratio Calculation (same as Factors 1 and 2), but applied to Mitigating Factors (e.g., “First offense,” “Cooperation,” “Remedial measures”).

    1. Comparison: Compare the list of Mitigating Factors.
    2. Weighting: Apply Tier weights.
      • Note: Most Mitigating Factors fall into Tier 2 (Compliance Program) or Tier 3 (Remedial Response).
    3. Ratio: Calculate the Match / Total ratio.
      • Impact: If both parties were “First Offenders” (Tier 4/General Factor I) or had “Clean Records,” this score increases. If one had a clean record and the other was a repeat offender, the score decreases.

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  • Inquisitive Little Beast

    So, after my analysis of the Gracetown action, Gemini decided I hadn’t looked hard enough into it, and it asked me:

    Next Step: Would you like me to drill down into the specific “General Factor” tiers (A, B, C) for the top match to see exactly which regulatory lines were crossed?

    Of course, I said Yes, and got the following response:

    Here is the drill-down into the Tier 1 General Factors (A, B, and C). These factors carry the highest weight in the OFAC Enforcement Guidelines and were the primary drivers for matching Gracetown, Inc. with An Individual (King Holdings LLC).

    Both cases are characterized by Egregious conduct and a lack of voluntary self-disclosure, but the specific regulatory lines crossed in Tier 1 reveal why they are near-identical regulatory twins.

    Tier 1 Comparison: The Core Violation

    General Factor A: Willful or Reckless Violation of Law

    This factor assesses whether the violation was a simple mistake, reckless negligence, or an intentional act to circumvent the law.

    • Target: Gracetown, Inc. (2025)
      • Behavior: The company received a specific Cease and Desist / Blocking Notice from OFAC regarding the property in question but proceeded to facilitate the sale regardless.
      • Assessment: This is the definition of Willfulness. It was not merely “ignoring red flags” (recklessness); it was the active disregard of a direct government order.
      • Pattern Match: High.
    • Match: An Individual (King Holdings LLC) (2025)
      • Behavior: The individual received an administrative subpoena and a Cautionary Letter from OFAC inquiring about the blocked assets. Instead of freezing them, the individual hastened the transfer of titles to obscure ownership.
      • Assessment: Like Gracetown, this was Willful conduct. The violation occurred after and in spite of direct OFAC intervention.
      • Pattern Match: High.

    Why this matters: Most enforcement actions (like Epsilon or Binance) involve systemic failures or ignoring general warnings. It is rare to find two cases where the violator ignored a specific, named notice from OFAC. This shared trait creates the strongest possible match score.

    General Factor B: Awareness of Conduct

    This factor looks at who knew about the violation—was it a rogue employee, or was senior management/the principal involved?

    • Target: Gracetown, Inc.
      • Level: Senior Management. The decision to ignore the OFAC notice was made by the Chief Operating Officer and General Counsel.
      • Details: Emails showed they discussed the notice and decided to “risk it” to close the deal.
      • Pattern Match: High.
    • Match: An Individual (King Holdings LLC)
      • Level: Owner/Principal. Since the violator was an Individual acting through an LLC, the “Management” was the perpetrator himself.
      • Details: The individual personally signed the transfer documents knowing they were in violation.
      • Pattern Match: High.

    Why this matters: In both cases, the violation was driven from the very top. There was no “breakdown in communication” or “software error” to blame. The decision-makers were the law-breakers.

    General Factor C: Harm to Sanctions Program Objectives

    This factor measures the actual economic benefit to the sanctioned party and the impact on U.S. foreign policy.

    • Target: Gracetown, Inc.
      • Impact: The transaction liquidated $12 million in real estate for a Designated Russian Oligarch (SDN), directly providing fresh capital to a blocked person.
      • Assessment: Significant Harm. It undermined the core purpose of the Russia-related sanctions program (denying revenue).
    • Match: An Individual (King Holdings LLC)
      • Impact: The transfers unblocked approximately $4.6 million in assets, allowing the SDN to move funds offshore.
      • Assessment: Significant Harm. While the dollar value is lower than Gracetown, the nature of the harm (liquidity for an SDN) is identical.

    Why this matters: Both actions resulted in actual funds reaching an SDN. This distinguishes them from cases like Binance (where the harm was largely volume/systemic risk) or Epsilon (where the harm was providing goods to a jurisdiction, rather than cash to a specific enemy).

    Summary of Tier 1 Alignment

    Tier 1 FactorGracetown, Inc.An Individual (King Holdings)Match Strength
    A: WillfulnessIgnored Direct OFAC NoticeIgnored Direct OFAC SubpoenaExact
    B: AwarenessSenior Management DirectedOwner/Principal DirectedExact
    C: HarmLiquidated Assets for SDNUnblocked Assets for SDNStrong

    Conclusion: The “Best Fit” model selected King Holdings not just because of the penalty grid (Factor 3), but because Factor A (Willfulness) acts as a unique fingerprint. Very few entities ignore a direct letter from the US Treasury; the fact that both Gracetown and King Holdings did so makes them statistical siblings in this enforcement model.

    —

    ,

  • What did I get, and could I have done better?

    I wasn’t sure how to really weight the first 3 factors in my analysis… so I tried it 3 different ways. Here’s the prompt that ran my model:

    Run the best fit procedure for all years from 2012 up to and including the current year. Rank the 3 best fits from best fit to worst fit.

    Then create, in tabular format, the following details of the matched enforcement action:

    1. Label and  List  the name of the penalized parties
    2. Label and List the date of the enforcement action notice
    3. Label and list the amount of the fine, each on its own line
    4. Finally, explain each factor that matched and how well it matched, and each factor which didn’t match well. List the two sets of factors separately.

    Do this 3 times:

    1. Weight  Factors 1, 2 and 3 identically
    2. Weight  Factor 1 higher than Factor 2 and Factor 2 higher than Factor 3
    3. Weight Factor 2 higher than Factor 1 and Factor 1 higher than Factor 3

    At the end of each run, explain the models and calculations created and the weights used

    and this is what I got back:

    Based on the procedure you defined, I have compared the most recent OFAC enforcement action (Target) against the corpus of enforcement actions from 2012 through the present day.

    The target action used for this analysis is:

    • Target: Gracetown, Inc.
    • Date: December 4, 2025
    • Characteristics: Violations of Russia-related sanctions (dealing in blocked property of Oleg Deripaska); Egregious; Not Voluntarily Self-Disclosed (Non-VSD); Willful disregard of explicit OFAC notice.

    Below are the results of the 3 runs using the specified weighting models, followed by the ranking of the 3 best fits.

    Ranking of the 3 Best Fits

    1. Best Fit:An Individual (King Holdings LLC) (2025)
      • Reasoning: This action is a near-perfect statistical twin to the target. Both involve willful dealing in blocked real estate/property connected to Russian oligarchs, both involved ignoring direct notices/subpoenas from OFAC, and both occupy the same “Egregious / Non-VSD” quadrant.
    2. Second Best Fit:Epsilon Electronics, Inc. (2014)
      • Reasoning: Despite the age gap, Epsilon is one of the few historical cases that strongly matches the “Egregious / Non-VSD” classification with a similar pattern of ignoring clear warning signs (red flags) regarding export destinations, mirroring Gracetown’s ignoring of the OFAC notice.
    3. Third Best Fit:Binance Holdings, Ltd. (2023)
      • Reasoning: While the scale differs (crypto/billions), it matches the critical Factor 3 (Egregious / Non-VSD) and Factor 1 (Willful behavior / Systemic disregard). It outscores other recent non-egregious cases (like IPI Partners) because the “Egregious” classification carries significant weight in the Penalty Grid factor.

    Run 1: Equal Weighting

    Model: Factors 1, 2, and 3 are weighted identically (1.0).

    • Calculation Note: Factor 4 is calculated at 70% of Factor 1 (0.7). Factors 5 and 6 are standard weight.

    Match 1: An Individual (King Holdings LLC)

    DetailsValue
    Penalized PartyAn Individual (acting through King Holdings LLC)
    DateNovember 24, 2025
    Fine Amount$4,677,552

    Factor Analysis

    Matching Factors (Strong Match)Non-Matching / Weak Factors
    Factor 1 (Behaviors): Score: High.
    Perfect match on “Ignoring Warnings” (General Factor A). Both parties received actual notice from OFAC and willfully ignored it to continue dealing in blocked property.    		Factor 5 (Period Length): Score: Medium.
    Target violation period was ~2 years (Tier 2). Match violation period was ~1 year (Tier 2/3 border). Slight variance in duration tiers.
    Factor 2 (Aggravating): Score: High.
    Matches on Willfulness (Tier 1) and Harm to Sanctions Program (Tier 1).    		Factor 6 (Mitigating): Score: Low.
    Both had zero valid mitigating factors (beyond tolling agreements), essentially a “null match” which contributes little positive score.
    Factor 3 (Penalty Grid): Score: Maximum.
    Both are Egregious and Not Voluntarily Self-Disclosed. Same quadrant.
    Factor 4 (Cooperation): Score: High.
    Both failed to cooperate substantially (Target delayed reporting; Match submitted false certifications).

    Match 2: Epsilon Electronics, Inc.

    DetailsValue
    Penalized PartyEpsilon Electronics, Inc.
    DateJuly 18, 2014
    Fine Amount$4,073,000

    Factor Analysis

    Matching Factors (Strong Match)Non-Matching / Weak Factors
    Factor 3 (Penalty Grid): Score: Maximum.
    Both classified as Egregious and Not Voluntarily Self-Disclosed.    		Factor 1 (Behaviors): Score: Medium.
    Match involved “ignoring red flags” (General Factor B) rather than “ignoring actual OFAC notice” (General Factor A). Similar intent, but different mechanism.
    Factor 2 (Aggravating): Score: High.
    Matches on Recklessness/Willfulness (Tier 1).    		Factor 5 (Period Length): Score: Low.
    Epsilon’s violations spanned ~4 years (Tier 1), whereas Target was ~2 years (Tier 2). Adjacent tiers receive intermediate score.

    Match 3: Binance Holdings, Ltd.

    DetailsValue
    Penalized PartyBinance Holdings, Ltd.
    DateNovember 21, 2023
    Fine Amount$968,618,825

    Factor Analysis

    Matching Factors (Strong Match)Non-Matching / Weak Factors
    Factor 3 (Penalty Grid): Score: Maximum.
    Both classified as Egregious and Not Voluntarily Self-Disclosed.    		Factor 1 (Behaviors): Score: Low.
    Target was “dealing in blocked property.” Match was “failure to implement compliance/AML controls.” Different generalized behaviors.
    Factor 2 (Aggravating): Score: Medium.
    Matches on Willfulness, but Binance had significant “Management Awareness” (General Factor B) which was less central to Target’s specific notice violation.    		Factor 4 (Cooperation): Score: Low.
    Binance eventually cooperated significantly (settlement). Target cooperation was deficient.

    Run 2: Behavior Dominant

    Model: Factor 1 (Behaviors) > Factor 2 > Factor 3.

    • Weights: F1 (3.0), F2 (2.0), F3 (1.0).
    • Effect: This model emphasizes what they did (ignoring notices, dealing in property) over the final penalty classification.

    Match 1: An Individual (King Holdings LLC)

    DetailsValue
    Penalized PartyAn Individual (acting through King Holdings LLC)
    DateNovember 24, 2025
    Fine Amount$4,677,552

    Factor Analysis

    Matching Factors (Very Strong Match)Non-Matching / Weak Factors
    Factor 1 (Behaviors): Score: Extremely High (Weighted 3x).
    The specific behavior of ignoring a direct OFAC notice is unique to these two cases. This tripled weight pushes this match far ahead of all others.    		Factor 5 (Period Length): Score: Medium.
    Minor mismatch in duration (1 year vs 2 years) is negligible compared to the massive behavior score.
    Factor 4 (Cooperation): Score: High.
    Weighted at 70% of Factor 1 (so 2.1x). Both demonstrated poor cooperation/bad faith.

    Match 2: Epsilon Electronics, Inc.

    DetailsValue
    Penalized PartyEpsilon Electronics, Inc.
    DateJuly 18, 2014
    Fine Amount$4,073,000

    Factor Analysis

    Matching Factors (Good Match)Non-Matching / Weak Factors
    Factor 2 (Aggravating):Score: High (Weighted 2x).
    Reckless conduct matches well.    		Factor 1 (Behaviors): Score: Moderate (Weighted 3x).
    Epsilon ignored general red flags, not a specific OFAC cease-and-desist/notice. The 3x weight on this factor widens the gap between Epsilon and the “Individual” match above.

    Match 3: Binance Holdings, Ltd.

    DetailsValue
    Penalized PartyBinance Holdings, Ltd.
    DateNovember 21, 2023
    Fine Amount$968,618,825

    Factor Analysis

    Matching Factors (Moderate Match)Non-Matching / Weak Factors
    Factor 3 (Penalty Grid): Score: Low Impact (Weighted 1x).
    The perfect grid match helps less here.    		Factor 1 (Behaviors): Score: Low (Weighted 3x).
    Systemic compliance failure (Binance) vs. Specific transactional violation (Target). The heavy weighting on behavior punishes this match significantly.

    Run 3: Aggravating Factor Dominant

    Model: Factor 2 (Aggravating) > Factor 1 > Factor 3.

    • Weights: F2 (3.0), F1 (2.0), F3 (1.0).
    • Effect: This model emphasizes the nature of the violation (Willfulness, Harm to Sanctions Program, Awareness) over the specific actions.

    Match 1: An Individual (King Holdings LLC)

    DetailsValue
    Penalized PartyAn Individual (acting through King Holdings LLC)
    DateNovember 24, 2025
    Fine Amount$4,677,552

    Factor Analysis

    Matching Factors (Strong Match)Non-Matching / Weak Factors
    Factor 2 (Aggravating): Score: Very High (Weighted 3x).
    Both cases hit Tier 1 General Factors (A, B, C) for Willfulness and Awareness. The 3x weight cements this as the top rank.    		(No significant weaknesses relative to other candidates)

    Match 2: Epsilon Electronics, Inc.

    DetailsValue
    Penalized PartyEpsilon Electronics, Inc.
    DateJuly 18, 2014
    Fine Amount$4,073,000

    Factor Analysis

    Matching Factors (Strong Match)Non-Matching / Weak Factors
    Factor 2 (Aggravating): Score: High (Weighted 3x).
    Epsilon’s “Reckless disregard” scores similarly to Gracetown’s “Willful disregard” in Tier 1. This model favors Epsilon more than Run 2 did.    		Factor 3 (Penalty Grid): Score: Low Impact (Weighted 1x).
    The perfect grid match contributes less to the total score.

    Match 3: Binance Holdings, Ltd.

    DetailsValue
    Penalized PartyBinance Holdings, Ltd.
    DateNovember 21, 2023
    Fine Amount$968,618,825

    Factor Analysis

    Matching Factors (Moderate Match)Non-Matching / Weak Factors
    Factor 2 (Aggravating): Score: High (Weighted 3x).
    Binance had massive aggravating factors regarding “Management Awareness” (General Factor B). This weights heavily here, potentially bringing it closer to Epsilon in score.    		Factor 1 (Behaviors):Score: Moderate (Weighted 2x).
    Still a mismatch on the specific behavioral mechanics.

    Summary of Models and Weights

    • Model 1 (Equal Weight): Used a baseline of 1.0 for Factors 1, 2, and 3. Factor 4 was calculated as 0.7 * Factor 1 Score. This model provided a balanced view where the “Penalty Grid” (Egregious/Non-VSD) played a significant role in elevating Epsilon and Binance.
    • Model 2 (Behavior Weighted): Used weights F1=3.0, F2=2.0, F3=1.0. This model strongly favored An Individual (King Holdings) because it was the only case that shared the specific behavior of “Ignoring an OFAC Notice.” It penalized Binance heavily for having different underlying behaviors.
    • Model 3 (Aggravating Weighted): Used weights F2=3.0, F1=2.0, F3=1.0. This model focused on “Willfulness” and “Awareness.” It brought Epsilon and Binance closer to the top because all three cases involved high-level willfulness (Tier 1 General Factors), regardless of the specific transaction type.

    At the end of the day, I think there’s value in all 3 approaches, as they answer different questions.

    What do you think?

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    ,

  • A better way to skin the cat: focus on priorities, not formulas

    I quickly realizes that trying to figure out the best algorithm or the best equations was not a smart way to proceed. So, instead, this model relies on me telling Gemini what I thought was important, and what I did not:

    This is a procedure for finding the best match between the most recent OFAC enforcement action and all the enforcement actions in a given year.

    Compare the Enforcement action document from the most recent settlement or imposition of Civil Monetary Penalty (i.e. ignore Findings of Violation) to each  enforcement action document in the time frame specified, other than the most recent enforcement action (e.g. do not compare the most recent enforcement action to itself). Omit any enforcement action which does not appear to refer to the enforcement process from the OFAC Enforcement Guidelines, and omit any Findings of Violation.

    General Factors should be considered in tiers, in descending order of influence on the match result. In each tier, all General Factors should be considered to have approximately the same importance and weight in the resulting model. 

    Tier 1 (highest weight/importance): General Factors A, B, and C

    Tier 2: General Factors D, E

    Tier 3: General Factors F, G

    Tier 3 (lowest importance/weight): General Factors H, I , J, K

    determine which is the closest comparison, based on the following factors:

    Factor 1: A comparison of the generalized behaviors (e.g. ignoring warnings from other parties, both internal and other non-regulatory parties, like banks who reject payments for sanctions reasons; wire stripping; falsification of documents or changing information to something misleading to third parties) noted in the enforcement release. Each matching behavior increases the result of this comparison, while each behavior that only one action represents decreases its value. Additionally, each factor must be weighted based on the General Factor the behavior is most associated with. So, matching on having no compliance program means a lot less than matching on Willful Behavior.

    Additionally, the ratio of General Factors to non-matching Factors should adjust the result – so that a 60% ratio should produce a higher overall result, all other factors being equal, than a 30% ratio.

    Factor 2: A comparison of the General Factors noted in the enforcement release relating to the aggravating factors noted. Each matching General Factor increases the result of this comparison, while each General Factor  that only one action represents decreases its value. 

    Additionally, the ratio of General Factor-weighted matching behaviors to non-matching factors should adjust the result – so that a 60% ratio should produce a higher overall result, all other factors being equal, than a 30% ratio.

    All comparisons and calculations should take into consideration the tier of each General Factor

    Factor 3: compare where each action falls on the OFAC Penalty Grid:

    If the quadrant is the same, the score is the highest.

    ELSE If both are “egregious”, the score is less than the previous..

    ELSE If both are “not voluntarily self-reported”, the score is less than the previous.

    ELSE If both are “non-egregious”, the score is less than the previous..

    ELSE If both are “voluntarily self-reported”, the score is less than the previous.

    ELSE the score is the lowest

    Factor 4: was there a lack of cooperation, other than lack of voluntary self-disclosure, in both enforcement actions, or was there substantial cooperation, in both enforcement actions?

    Weight Factor 4 at 70% of Factor 1

    Factor 5: Compare the periods of time of the violating behavior in both enforcement actions 

    Period Length Tier 1: longer than 3 years

    Period Length Tier 2: between 1 and 3 years

    Period Length Tier 3: shorter than 1 year

    If both actions are in the same tier, score this the highest

    ELSE If the actions are in adjacent tiers, give this an intermediate score

    ELSE score this the lowest

    Factor 6: A comparison of the General Factors noted in the enforcement release relating to the mitigating factors noted. Each matching General Factor increases the result of this comparison, while each General Factor  that only one action represents decreases its value. 

    Additionally, the ratio of General Factor-weighted matching behaviors to non-matching factors should adjust the result – so that a 60% ratio should produce a higher overall result, all other factors being equal, than a 30% ratio.

    All comparisons and calculations should take into consideration the tier of each General Factor

    Take no action on this information until prompted further.

    Notice that while I gave relative scoring, I did very little, if any, hard-coding.

    Next: my results

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    ,

  • Learning the hard way: my first AI prompt for comparing Enforcement Actions

    I first tried to figure out, on my own, how to figure out the “best fit” between OFAC enforcement actions. Here’s that first prompt:

    This is a procedure for finding the best match between the most recent OFAC enforcement action and all the enforcement actions in a given year.

    Compare the Enforcement action document from the most recent settlement or imposition of Civil Monetary Penalty (i.e. ignore Findings of Violation) to each  enforcement action document in the time frame specified, other than the most recent enforcement action (e.g. do not compare the most recent enforcement action to itself). Omit any enforcement action which does not appear to refer to the enforcement process from the OFAC Enforcement Guidelines.

    determine which is the closest comparison, based on the following factors, in descending order of importance:

    Factor 1: A weighted average of the generalized behaviors (e.g. ignoring warnings from other parties, both internal and other non-regulatory parties, like banks who reject payments for sanctions reasons; wire stripping; falsification of documents or changing information to something misleading to third parties) noted in the enforcement release. In this model, each matching behavior is weighted at 100%, and each behavior that is documented in one enforcement action but not the other is weighted at 20%.

    Factor 2: Three times the sum of the number of matching  General Factors that correlate to the aggravating factors listed between the two enforcement actions, less the number of General Factors for either action which did not match. So, if Action 1 had 4 General Factors, Action 2 had 3 General Factors, and 2 were matching, the score would be 3*2 (for the matching factors – 2 (for Action 1’s non-matching factors) – 1 (for Action 2’s non-matching factor). If the result is less than 0, change it to 0.

    Weight Factor 2 at 85% of Factor 1.

    Factor 3: were the behaviors in both enforcement actions  egregious or non-egregious?

    Weight Factor 3 at 75% of Factor 1

    Factor 4: was there a lack of cooperation, other than lack of voluntary self-disclosure, in both enforcement actions, or was there substantial cooperation, in both enforcement actions?

    Weight Factor 4 at 70% of Factor 1

    Factor 5: Was the period of time of the violating behavior in both enforcement actions longer than 2 years in duration

    Factor 6: Was the period of time of the violating behavior in both enforcement actions longer than 1 years in duration but shorter than 2 years in duration

    Factor 7: Was the period of time of the violating behavior in both enforcement actions  shorter than 2 years in duration

    Weight Factor 5 at 50% of Factor 1

    Weight Factor 6 at 45% of Factor 1

    Weight Factor 7 at 40% of Factor 1

    Factor 8: were the violations in both enforcement actions self-reported or not?

    Weight Factor 8 at 30% of Factor 1

    Factor 9:  Three times the sum of the number of matching  General Factors that correlate to the mitigating factors listed between the two enforcement actions, less the number of General Factors for either action which did not match. So, if Action 1 had 4 General Factors, Action 2 had 3 General Factors, and 2 were matching, the score would be 3*2 (for the matching factors – 2 (for Action 1’s non-matching factors) – 1 (for Action 2’s non-matching factor). If the result is less than 0, change it to 0.

    Weight Factor 8 at 25% of Factor 1

    Take no action on this information until prompted further.

    One thing I figured out early on was that last line – breaking up a long prompt into pieces and tell Gemini that I was not done yet.

    This seems to have produced OK results – this is actually one of a number of early attempts.

    Next post: an improved model that relies on the smarts of the AI model rather than my own

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