Mr. Sanctions

Month: December 2025

  • 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.

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  • 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?

    —

    ,

  • 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

    —

    ,

  • Will you get value out of this?

    From the new The Mr. Sanctions Difference page:

    So, I asked some friends and co-workers for some feedback about this site, and a former co-worker asked me what the purpose of it was. I recognized this was a real gap – after all, while “Mr. Sanctions” is catchy, should folks read it, and why?

    In fact, even naming this page was a bit of a challenge. I considered “Why Read Mr. Sanctions?”, but part of me didn’t want to make this a marketing “sell” – other than informing folks. For the same reason, “Is this for me?” and the like ended up in the trash can (Mac guys don’t use Recycle Bins).

    So… is this for you? Depends on what you’re looking for, of course.

    I am not a lawyer nor do I work for the U.S. Treasury and the like. What I have been for much of my career is someone who tries to make the complexity of sanctions accessible. And that’s really what this site strives to be: a way to read sanctions-related info in a more easy-to-digest way, removing layers of complexity, reformatting information so the pieces you care about are easier to identify, and using summarization to provide quicker reads. Of course, we provide the links to the original in case you want more detail. 

    This is also a working space for leveraging AI tools (most notably, Google Gemini) to find insights and trends. The ability of these tools to scour for information and organize it is impressive – no way could I have come up with the insights derived about Executive Order 14024 by myself.

    As you may have seen, my first attempt to find parallels between enforcement actions wasn’t awful, but could surely use refinement. As I’ve already seen, trying to build all the most basic models is, at best, a matter of trial and error. And, as my wife reminds me, the more you direct a model, and the less you leave it free to “experiment”, the more predictable the results are. I will be sharing the technical details, like my prompts, for those who want to experiment on their own dime.

    Oh, and the image on the home page? Also Gemini – but the first output had 2 left hands and 1 right hand Easy enough to fix, but it gave me a chuckle.

    —

  • Please allow me to introduce myself…

    From the About Mr. Sanctions page:

    So, remember Mr. Watchlist? 

    First, a confession: when I stopped posting there, I didn’t hold onto the domain name and, as is typically the case, someone swooped in and is holding it hostage.

    But, perhaps more importantly, MrWarchlist.com was a little too broad. Sanctions has always been my first love, so it only makes sense that, when I recently decided I wanted to blog again, it was only natural to cut out that which did not spark joy. So, goodbye to AML stuff, anti-bribery and corruption stuff, unauthorized firm stuff…

    Now, will this be different in other ways? Yeah – I want to leverage some of the AI tools to pull out some insights from the available online info, and post that value-added info alongside the actual regulatory text. Some of the stuff is pretty basic: I got a prompt working where you can nicely pull out what changed in those OFAC listings (I hate trying to compare them). Other insights are more aligned with my love of enforcement actions: finding not only trends in yearly actions and across regulators (although it’s still really only OFAC and OFSI at this point), but also trying to find what previous actions the new one is most like. Won’t that be fun? I sure think so.

    OMG – I just realized some of you actually have no idea who I am. I’m Eric A. Sohn, formerly CAMS and CGSS-certified, formerly a frequent author for industry publications and an occasional presenter to conferences and customer groups. While I currently manage some sanctions analysts for a firm which supports the securities industry, I have done stints in VendorWorld for Accuity (as a professional services consultant) and Dow Jones (authoring a weekly sanctions newsletter, doing a vendor selection for name matching software, and being the pre-sales SME). And I am diving back into the professional association world, having just joined ACSS.

    In my spare time, I an a rabid Philadelphia Eagles fan, and spend lots of time walking and playing with my 5-year old rescue dog (Pug/Shih Tau/Pekingese mix). The family: wife of 32+ years, and two adult offspring.

    —

  • Does Gracetown seem familiar?

    I always like to see echoes in enforcement actions, where something from this year is similar to the faces and factors of an earlier one. Some particular facts might be unique, but there are definite patterns.

    So, I built an Gemini prompt to compare the latest action against all previous actions since 2012 (when the Enforcement Guidelines started showing up in the enforcement releases), find the best fit in each year’s actions, then rank those.

    Yes, I will post the actual method I provided to Gemini – here are the results of this first attempt:

    Based on the procedure provided, I have identified the most recent OFAC enforcement action as of December 5, 2025, which is the action against Gracetown, Inc. (issued Dec 4, 2025).

    I have compared this “Anchor Case” against the enforcement actions from each year (2012–2025) to find the single best fit for that year. Below is the ranking of these yearly “best fits,” ordered from the strongest overall match to the weakest match.

    The Anchor Case (Reference for Comparison)

    • Entity: Gracetown, Inc.
    • Date: December 4, 2025
    • Determination: Egregious, Non-Voluntarily Self-Disclosed (Non-VSD).
    • Duration: > 2 Years (April 2018 – May 2020).
    • Key Behaviors: Willfulness/Recklessness; Ignoring explicit warnings (received direct OFAC notice regarding designated owner); Dealing in blocked property.

    Ranked Best Fits (2012–2025)

    1. 2019: UniCredit Group Banks

    • Date: April 15, 2019
    • Fine: $611,000,000
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): Strong. UniCredit operated accounts for blocked parties (IRISL) and ignored sanctions risks similar to Gracetown’s disregard of its owner’s designation. Both involved ignoring the blocked status of a known counterparty.
      • Mismatched Factors: UniCredit involved wire stripping (altering payment messages), which Gracetown did not explicitly do (Gracetown accepted payments via loan arrangements).

    2. 2014: BNP Paribas SA

    • Date: June 30, 2014
    • Fine: $963,619,900
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): Strong. BNP willfully ignored the status of sanctioned entities (Sudan, Iran, Cuba) and continued processing payments, paralleling Gracetown’s willful receipt of payments from a blocked owner.
      • Mismatched Factors: The scale of BNP’s systemic wire stripping was more complex than Gracetown’s property management violations.

    3. 2023: Binance Holdings, Ltd.

    • Date: November 21, 2023
    • Fine: $968,618,825
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): Strong. Binance management knew of the violations and willfully allowed them to continue, ignoring internal and external “warnings” about sanctions compliance, similar to Gracetown ignoring the OFAC notice.
      • Mismatched Factors: Binance’s lack of cooperation was noted as more severe (misleading regulators) compared to Gracetown’s standard posture.

    4. 2015: Schlumberger Oilfield Holdings, Ltd.

    • Date: August 7, 2015
    • Fine: $232,706,600
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): “Facilitation” of transactions for blocked parties. Schlumberger U.S. personnel facilitated business for Iran/Sudan, similar to Gracetown personnel managing property for a blocked oligarch.
      • Mismatched Factors: None significant; a very close procedural match.

    5. 2017: ZTE Corporation

    • Date: March 7, 2017
    • Fine: $100,871,266
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): ZTE received warnings and created an elaborate system to hide conduct. Gracetown also received a specific notice (the OFAC blocking notice) and continued dealing.
      • Mismatched Factors: ZTE involved a “Lack of Cooperation” (Factor 2) that was extreme (lying to federal investigators), whereas Gracetown’s cooperation was not flagged as deficient to that extent.

    6. 2018: Société Générale S.A.

    • Date: November 19, 2018
    • Fine: $53,966,916
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): Ignored warnings and processed payments for blocked parties.
      • Mismatched Factors: General banking sector behaviors (omitting data) vs. corporate property management.

    7. 2012: ING Bank N.V.

    • Date: June 12, 2012
    • Fine: $619,000,000
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): Management knowledge and willfulness.
      • Mismatched Factors: Factor 9 (Mitigating) — ING had substantial remediation credit which slightly alters the weighted comparison.

    8. 2013: Weatherford International

    • Date: November 26, 2013
    • Fine: $91,000,000
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): Export of goods/services to blocked countries; failure to heed compliance gaps.
      • Mismatched Factors: Less emphasis on “ignoring specific warnings from OFAC” compared to Gracetown.

    9. 2016: National Oilwell Varco (NOV)

    • Date: November 14, 2016
    • Fine: $5,976,028
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): Senior management approved dealings with Iran.
      • Mismatched Factors: The fine size and context (subsidiaries) are very similar to Gracetown, but the specific “ignoring of a blocking notice” was less central than in Gracetown.

    10. 2022: Bittrex, Inc.

    • Date: October 11, 2022
    • Fine: $24,280,829
    • Match Analysis:
      • Matched Factors: Egregious (Factor 1); Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Behavioral Match (Factor 4): Failure to screen/block (reckless disregard).
      • Mismatched Factors: Bittrex cooperated (Factor 2 was neutral/positive), whereas Gracetown was egregious partly due to the specific willfulness of ignoring the notice.

    11. 2025: IPI Partners, LLC (Comparison within same year)

    • Date: December 2, 2025
    • Fine: $11,485,352
    • Match Analysis:
      • Matched Factors: Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Mismatched Factors: Egregiousness (Factor 1) — IPI was determined to be Non-Egregious, making it a significantly worse match than the historical egregious cases.
      • Note: Gracetown (Dec 4) and IPI (Dec 2) are days apart, but the Egregiousness determination makes them dissimilar under your procedure.

    12. 2021: Mashreqbank PSC

    • Date: November 9, 2021
    • Fine: $100,000,000 (Settlement)
    • Match Analysis:
      • Matched Factors: Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Mismatched Factors: Egregiousness (Factor 1) — OFAC determined this case was Non-Egregious (despite the large fine, it was processed under non-egregious penalty caps due to cooperation). This fails the most important factor.

    13. 2020: BitGo, Inc.

    • Date: December 30, 2020
    • Fine: $98,830
    • Match Analysis:
      • Matched Factors: Non-VSD (Factor 8); Duration > 2 Years (Factor 5).
      • Mismatched Factors: Egregiousness (Factor 1) — Determined Non-Egregious. The violations were “reckless” but did not rise to the egregious penalty tier.

    14. 2024: State Street Bank and Trust Company

    • Date: July 26, 2024
    • Fine: $7,452,501
    • Match Analysis:
      • Matched Factors: Non-VSD (Factor 8).
      • Mismatched Factors: Egregiousness (Factor 1) — Determined Non-Egregious. Duration (Factor 5/6/7) — These violations were largely distinct processing errors rather than a multi-year sustained scheme like Gracetown. This is the weakest match as it lacks the “willful” behavioral characteristics.

    Summary of Factor Matches (Gracetown vs. Best Fits)

    FactorDescriptionBest Matches (2014, 2019, 2023)Weakest Matches (2020, 2021, 2024)
    1Egregious?MATCH (Yes)MISMATCH (No – Non-Egregious)
    2Cooperation?MATCH (Mixed/Satisfactory)MATCH (Satisfactory)
    3Aggravating (Weighted)MATCH (High score: Willful, Reckless, Management Knowledge)MISMATCH (Lower score: System errors, technical failures)
    4BehaviorsMATCH (Ignored warnings, obfuscation)MISMATCH (Screening tool errors, no active concealment)
    5Duration > 2 YrsMATCHVARIES (Often match, but context differs)
    8Self-Reported?MATCH (Non-VSD)MATCH (Non-VSD)

    So, how do you think the model did?

    —

  • OFSI’s Cyber sanctions additions, refrormatted

    Based on the Office of Financial Sanctions Implementation (OFSI) update for the Cyber sanctions regime dated 04/12/2025, the following additions have been made.

    Individuals

    • Boris Alekseyevich ANTONOV
      • Group ID: 17227
      • Name (non-Latin script): Борис Алексеевич АНТОНОВ
      • Nationality: Russia
      • Address: Russia
      • Other Information: (UK Sanctions List Ref): CYB0104.
      • UK Statement of Reasons: The Secretary of State considers that there are reasonable grounds to suspect that as part of Unit 26165, Boris ANTONOV has been involved in relevant cyber activity in that he was responsible for, engaging in, providing support for, or promoting the commission, planning or preparation of relevant cyber activity. Such activity that Boris ANTONOV has been involved in undermines, or is intended to undermine, the integrity, prosperity or security of the United Kingdom or a country other than the United Kingdom.
      • Gender: Male
      • Listed on: 04/12/2025
      • Last Updated: 04/12/2025
    • Anatoliy Vladimirovich ISTOMIN
      • Group ID: 17228
      • Name (non-Latin script): Анатолий Владимирович ИСТОМИН
      • Nationality: Russia
      • Address: Russia
      • Other Information: (UK Sanctions List Ref): CYB0105.
      • UK Statement of Reasons: The Secretary of State considers that there are reasonable grounds to suspect that as part of Unit 26165, Anatoliy Vladimirovich ISTOMIN has been involved in relevant cyber activity in that he was responsible for, engaging in, providing support for, or promoting the commission, planning or preparation of relevant cyber activity. Such activity that Anatoliy Vladimirovich ISTOMIN has been involved in undermines, or is intended to undermine, the integrity, prosperity or security of the United Kingdom or a country other than the United Kingdom.
      • Gender: Male
      • Listed on: 04/12/2025
      • Last Updated: 04/12/2025
    • Igor Andreyevich BOCHKA
      • Group ID: 17229
      • Name (non-Latin script): Игорь Андреевич БОЧКА
      • a.k.a: BOCHKA, Igor, Andreevich
      • Nationality: Russia
      • Address: Russia
      • Other Information: (UK Sanctions List Ref): CYB0106.
      • UK Statement of Reasons: The Secretary of State considers that there are reasonable grounds to suspect that a member of GRU Unit 26165, Igor Andreyevich BOCHKA has also been involved in relevant cyber activity in that he has been responsible for, engaging in, providing support for, or promoting the commission, planning or preparation of relevant cyber activity. Such activity that Igor Andreyevich BOCHKA has been involved in undermines, or is intended to undermine, the integrity, prosperity or security of the United Kingdom or a country other than the United Kingdom.
      • Gender: Male
      • Listed on: 04/12/2025
      • Last Updated: 04/12/2025
    • Aleksey Andreyevich UMETS
      • Group ID: 17230
      • Name (non-Latin script): Алексей Андреевич УМЕЦ
      • Nationality: Russia
      • Address: Russia
      • Other Information: (UK Sanctions List Ref): CYB0107.
      • UK Statement of Reasons: The Secretary of State considers that there are reasonable grounds to suspect that as part of Unit 26165, Aleksey Andreyevich UMETS has been involved in relevant cyber activity in that he was responsible for, engaging in, providing support for, or promoting the commission, planning or preparation of relevant cyber activity. Such activity that Aleksey Andreyevich UMETS has been involved in undermines, or is intended to undermine, the integrity, prosperity or security of the United Kingdom or a country other than the United Kingdom.
      • Gender: Male
      • Listed on: 04/12/2025
      • Last Updated: 04/12/2025
    • Pavel Vyacheslavovich YERSHOV
      • Group ID: 17231
      • Name (non-Latin script): Павел Вячеславович ЕРШОВ
      • Nationality: Russia
      • Other Information: (UK Sanctions List Ref): CYB0108.
      • UK Statement of Reasons: The Secretary of State considers that there are reasonable grounds to suspect that as part of Unit 26165, Pavel Vyacheslavovich YERSHOV has been involved in relevant cyber activity in that he has been responsible for, engaging in, providing support for, or promoting the commission, planning or preparation of relevant cyber activity. Such activity that Pavel Vyacheslavovich YERSHOV has been involved in undermines, or is intended to undermine, the integrity, prosperity or security of the United Kingdom or a country other than the United Kingdom.
      • Gender: Male
      • Listed on: 04/12/2025
      • Last Updated: 04/12/2025
    • Nikolay Yuryevich KOZACHEK
      • Group ID: 17232
      • Name (non-Latin script): Николай Юрьевич КОЗАЧЕК
      • Nationality: Russia
      • Other Information: (UK Sanctions List Ref): CYB0109.
      • UK Statement of Reasons: The Secretary of State considers that there are reasonable grounds to suspect that as part of Unit 26165, Nikolay Yuryevich KOZACHEK has been involved in relevant cyber activity in that he has been responsible for, engaging in, providing support for, or promoting the commission, planning or preparation of relevant cyber activity. Such activity that Nikolay Yuryevich KOZACHEK has been involved in undermines, or is intended to undermine, the integrity, prosperity or security of the United Kingdom or a country other than the United Kingdom.
      • Gender: Male
      • Listed on: 04/12/2025
      • Last Updated: 04/12/2025
    • Denis Igorevich DENISENKO
      • Group ID: 17233
      • Name (non-Latin script): Денис Игоревич ДЕНИСЕНКО
      • Nationality: Russia
      • Other Information: (UK Sanctions List Ref): CYB0110.
      • UK Statement of Reasons: The Secretary of State considers that there are reasonable grounds to suspect that Russian GRU 29155 Officer Senior Lieutenant Denis Igorevich DENISENKO is or has been responsible for, engaging in, providing support for, or promoting the commission, planning or preparation of relevant cyber activity. Additionally, DENISENKO remains associated with a GRU unit, which is a person who is or has been so involved in such activity. The activity that DENISENKO is or has been involved in undermines, or is intended to undermine, the integrity, prosperity or security of the United Kingdom or a country other than the United Kingdom.1
      • Gender: Male2
      • Listed on: 04/12/2025345
      • Last Updated: 04/12/2025678
    • Dmitriy Yuryevich GOLOSHUBOV91011
      • Group ID: 17234121314
      • Nam15e (non-Latin script): Дмитрий Юрьевич ГОЛОШУБОВ1617
      • Nationality: Russia1819
      • Other Information: (UK Sanctions List Ref): CYB0111.2021
      • UK Statement of Reasons:22 The Secretary of State 23considers that there are reasonable grounds to suspect that Russian GRU 29155 Officer Dmitriy Yuryevich GOLOSHUBOV is or has been responsible for, engaging in, providing support for, or promoting the commission, planning or preparation of relevant cyber activity. Additionally, GOLOSHUBOV remains associated with a GRU unit, which is a person who is or has been so involved in such activity. The activity that GOLOSHUBOV is or has been involved in undermines, or is intended to undermine, the integrity, prosperity or security of the United Kingdom or a country other than the United Kingdom.
      • Gender: Male
      • Listed on: 04/12/2025
      • Last Updated: 04/12/2025

    —

    ,

  • OFSI Russia sanctions additions, reformatted

    Based on the Annex to Notice_Russia_041225.pdf, here are the additions to the consolidated list, reformatted as requested:

    Based on the Office of Financial Sanctions Implementation (OFSI) update provided, here are the additions to the Russia financial sanctions regime, reformatted as requested.

    Entities

    1. THE MAIN DIRECTORATE OF THE GENERAL STAFF OF THE ARMED FORCES OF THE RUSSIAN FEDERATION (GRU)

    • Group ID: 17235
    • Name (non-Latin script): Гла́вное управле́ние Генера́льного шта́ба Вооружённых сил Росси́йской Федера́ции
    • a.k.a: (1) GRU (2) Main Directorate (3) Main Intelligence Directorate
    • Address: Khoroshevskoye Shosse, 76, Moscow, Russia.
    • Other Information: (UK Sanctions List Ref): RUS3149. Financial sanctions imposed in addition to an asset freeze: Trust services. Date trust services sanctions imposed: 04/12/2025. (UK Statement of Reasons): The Secretary of State considers that there are reasonable grounds to suspect THE MAIN DIRECTORATE OF THE GENERAL STAFF OF THE ARMED FORCES OF THE RUSSIAN FEDERATION (GRU) is an involved person under the Russia (Sanctions) (EU Exit) Regulations 2019 based on the following ground: THE MAIN DIRECTORATE OF THE GENERAL STAFF OF THE ARMED FORCES OF THE RUSSIAN FEDERATION (GRU) is or has been involved in destabilising Ukraine or undermining or threatening the territorial integrity, sovereignty or independence of Ukraine.
    • Listed on: 04/12/2025 UK Sanctions List
    • Date Designated: 04/12/2025
    • Last Updated: 04/12/2025

    Supplemental Information: The GRU is Russia’s foreign military intelligence agency. This designation sanctions the agency in its entirety. The UK government stated this action was taken in response to the GRU’s “ongoing campaign of hostile activity,” including the 2018 Salisbury Novichok poisonings and malign activities across Europe and Ukraine.

    Individuals

    1. Yuriy Alekseevich SIZOV

    • Group ID: 17236
    • Name (non-Latin script): Юрий Алексеевич СИЗОВ
    • DOB: 17/02/1988
    • POB: St Petersburg, Russia
    • Nationality: Russia
    • National Identification Number: 784805190577
    • National Identification Details: Tax identification number1
    • Position: GRU officer2
    • Other Information: (UK Sanctions List Ref): RUS3150. Financial sanctions imposed in addition to an asset freeze: Trust services. Date trust services sanctions imposed: 04/12/2025. (UK Statement of Reasons): Yuriy Alekseevich SIZOV is an involved person under the Russia3 (Sanctions) (EU Exit) Regulations 2019 on the basis that he is or has been destabilising Ukraine or undermining the territorial security and sovereignty of Ukraine by engaging in, providing support for,4 or promoting actions which destabilise Ukraine or undermine or threaten the territorial 5integrity, sovereignty or ind6ependence of Ukraine.
    • (Gender): Male
    • Listed on: 04/12/2025 UK Sanctions List
    • Date Designated: 04/12/2025
    • Last Updated: 04/12/2025

    Supplemental Information: Yuriy Sizov is identified as a GRU officer. He is reported to be part of a team (Unit 29155) involved in organizing sabotage operations in Western countries, working in coordination with other sanctioned officers like Denis Smolyaninov.

    2. Vladimir LIPCHENKO

    • Group ID: 17237
    • Name (non-Latin script): Владимир ЛИПЧЕНКО
    • DOB: 28/09/1974
    • a.k.a: (1) VLODEK (2) WLODEK
    • Nationality: Russia
    • Passport Number: 4015400649
    • Passport Details: Russian passport number
    • Position: GRU officer
    • Other Information: (UK Sanctions List Ref): RUS3151. Financial sanctions imposed in addition to an asset freeze: Trust services. Date trust services sanctions imposed: 04/12/2025. (UK Statement of Reasons): Vladimir LIPCHENKO is an involved person under the Russia (Sanctions) (EU Exit) Regulations 2019 on the basis that he is or has been destabilising Ukraine or undermining the territorial secur7ity and sovereignty of Ukraine by engaging in, providing support for, or promoting actions which destabilise Ukraine or undermin8e or threa9ten the territorial integrity, sovereignty or independence of Ukraine.101112
    • (Gender): Male131415
    • Listed on: 04/12/2025 UK Sanctions List161718
    • Date Designated: 04/12/2025192021
    • Last Updated: 04/12/2025222324

    Supplemental Information: Vladimir Lipchenko is a GRU officer wh25o also uses the alias “Vlodek” (or Wlodek). Reports indicate he works under the command of Denis Smolyaninov and has been involved in orchestrating sabotag26e activiti27es in the West.

    3. Denis Alexandrovich SMOLYANINOV

    • Group ID: 17238
    • Name (non-Latin script): Денис Александрович СМОЛЯНИНОВ
    • Title: Colonel
    • DOB: 26/08/1976
    • POB: Chelyabinsk, Russia
    • Nationality: Russia
    • National Identification Number: 672904784466
    • National Identification Details: Tax identification number
    • Position: GRU officer
    • Other Information: (UK Sanctions List Ref): RUS3152. Financial sanctions imposed in addition to an asset freeze: Trust services. Date trust services sanctions imposed: 04/12/2025. (UK Statement of Reasons): Denis Alexandrovich SMOLYANINOV (hereafter SMOLYANINOV) is an involved person under the Russia (Sanctions) (EU Exit) Regulations 2019 on the basis that: a) SMOLYANINOV is or has28 been obtaining a benefit from the Government of Russia, and is involved in destabilising Ukraine or b) SMOLYANINOV is 29or ha30s been destabilising Ukraine or undermining the territorial security and sovereignty of Ukraine by engaging in, providing support for, or promoting actions which destabilise Ukraine or undermine or threaten the territorial integrity, sovereignty or independence of Ukraine, namely the coordina31tion of hostile activities.32
    • (Gender): Male33
    • Listed on: 04/12/2025 UK Sanctions List34
    • Date Designated: 04/12/202535
    • Last Upd36ated: 04/12/2025

    Supplemental Information: Colonel Denis Smolyaninov is a high-ranking officer in the GRU’s Unit 29155. He has been accused by European intelligence agencies of recruiting “disposable agents” (often criminals) to carry out sabotage attacks, such as arson at DHL logistics hubs in the UK and Germany. He was also specifically named by the UK government as being responsible for plotting a terror attack on Ukrainian supermarkets.

    —

    ,

  • Today’s OTSI One-Year Anniversary Overview – Simplified

    To know more, read the full PDF report.

    Overview of the Office of Trade Sanctions Implementation (OTSI)

    The Office of Trade Sanctions Implementation (OTSI) is a new government body launched in October 2024 as part of the Department for Business and Trade. Its primary job is to make sure trade sanctions are followed properly. While HM Revenue & Customs (HMRC) handles criminal enforcement and goods crossing the UK border, OTSI focuses on “civil enforcement.” This means they handle fines and penalties for businesses that break the rules regarding:

    • Providing services that are under sanction.
    • Moving or acquiring sanctioned goods or technology outside the UK.
    • Services related to moving these goods, such as insurance or shipping.

    OTSI also helps businesses understand the rules to prevent mistakes before they happen.

    Managing Permissions and Enforcing Rules

    A major part of OTSI’s work involves granting special permissions, known as licences, that allow businesses to carry out trade that would otherwise be banned.

    • Permissions (Licensing): In its first year, OTSI received 60 applications for these licences. Most were for professional or business services related to the sanctions on Russia. It takes about 82 working days on average to get a decision. So far, 12 licences have been granted (either fully or partially), while others were refused, withdrawn, or found to be unnecessary.
    • Enforcing the Law: OTSI investigates when companies or individuals are suspected of breaking trade sanctions. They have received 146 reports of potential rule-breaking, largely from the financial services sector. While no monetary fines have been issued yet, several investigations are underway, and some cases have been passed to HMRC for criminal investigation.
    • Whistleblower Protection: New laws were introduced in 2025 to protect employees who report sanctions violations to the government, ensuring they are safe from unfair treatment at work.

    Working with Businesses and Partners

    OTSI does not work in isolation. A significant amount of effort has gone into building relationships to make sanctions more effective.

    • Supporting Business: The office has held over 200 meetings, workshops, and webinars to help UK businesses understand their obligations. They have also released simple guides to help companies spot “red flags” where someone might be trying to get around the rules.
    • Global and Local Cooperation: OTSI works closely with international allies—such as the US, EU, and Japan—to ensure sanctions are coordinated globally. Within the UK, they collaborate with other agencies like the Foreign Office and the National Crime Agency to share intelligence and improve enforcement.

    Looking Ahead

    The report outlines several goals for the future as OTSI expands its role:

    • More Help for Businesses: They plan to offer more targeted advice and expand their “roadshows” to reach businesses across the UK, not just in London.
    • Taking on More Responsibilities: In early 2026, OTSI will take over the responsibility for licensing export sanctions (except for military-related “strategic” exports).
    • Smarter Enforcement: The office plans to improve how it uses data and intelligence to proactively find and stop rule-breaking, rather than just waiting for reports to come in.

    —

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