The US Treasury has announced coordinated enforcement actions imposing more than $1.21 billion in penalties against Bank of America for anti-money-laundering and sanctions failures. FinCEN assessed a $1.2 billion penalty, crediting a $750 million OCC penalty, while OFAC announced an $11.6 million settlement. The Treasury described the OCC assessment as the largest in the agency’s history.

Bank of America admitted in the FinCEN resolution that it wilfully violated the Bank Secrecy Act and failed to meet requirements covering its AML programme, foreign correspondent due diligence and suspicious activity reporting. Authorities said more than $5 billion in suspicious transactions was not reported on time, including more than $1 billion associated with national-security and priority illicit-finance risks.

The enforcement detail matters more than the headline number. Treasury said weaknesses included ineffective transaction monitoring, delayed escalation, insufficient training, watchlist-update failures and poor sanctions-alert calibration. The remedial order requires third-party review of monitoring, customer due diligence, correspondent banking and the data-governance framework supporting AML.

This is a warning against treating AI as a substitute for control ownership. Better models cannot repair unclear escalation duties, weak training, incomplete source data or a tolerance for unresolved alerts. Banks modernising financial-crime systems should test lineage, thresholds, investigator capacity and governance together, then preserve evidence that the control works under operational pressure.

Execution Level Governance- What audit-ready agent governance actually looks like
David Girvin, founder and CEO of Assury argues that model-in-the-loop review, AI governing AI, is fundamentally unreliable for regulated environments: even the best-performing models miss a meaningful share of violations, the reviewing model is typically provided by the same vendor being reviewed, and prompt injection or context poisoning can compromise both the acting agent and its supposed overseer simultaneously. He makes the case for deterministic, architecturally enforced controls instead, walking through Assury's approach of autonomy zones, session risk accumulation, and credential starvation, which lets a compromised agent be cut off from its tools instantly rather than relying on time-boxed access. The conversation touches on why David is sceptical of just-in-time credentialing as a solution for agent security more broadly, since agent sessions don't run on predictable human timescales, along with the current gap between how identity and security vendors are pitching agent protection and what he sees happening at the execution layer in practice. He also discusses the compliance and audit implications of probabilistic decision-making, arguing that regulated industries will increasingly need tamper-evident, hash-chained audit trails that can withstand scrutiny from auditors and regulators who are only beginning to understand agentic risk, and reflects on a named frontier lab's own published framework as an example of the gap between research and practitioner reality. Elsewhere, David reflects candidly on building a bootstrapped security company in an increasingly crowded market, why he turned down aggressive VC funding to stay in control of the product, and what a credible third-party assessment of his own gateway would need to look like given that Assury sits directly in the execution path for every customer's agents.
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