The weekly readout
Can we contain and recover from the combined effects of interacting agents?
Japan’s finance minister says G7 finance ministers and central bank governors agreed to tabletop exercises on AI-driven cyberattacks; design and dates are unspecified. These are research and planned policy signals, not a live failure or a new requirement.
01 / What happened
Central banks are modelling interaction, not just single agents.
BIS Project Agenti is testing a controlled payment simulator to see how agents with different objectives and strategies affect payment timing, liquidity demand, gridlock and shock propagation. It is controlled research, not a live-market result.
02 / Why it matters
Controls can fail through correlation.
Several agents may respond to the same signal and shift payment timing or liquidity demand together. A failure in a shared payment or orchestration service could compound the outcome. The September Financial Policy Committee record says recent frontier-AI test-environment incidents reinforce the need to prepare for cyber and operational risks, and warns that interconnected vulnerabilities may crystallise together. BIS Project Agenti is controlled research, not a live-market result or a new requirement.
03 / What to do
Simulate a common shock and a shared-service loss.
Ask payments and resilience owners to test a common liquidity shock with the loss of a shared payment or orchestration service. Measure payment delays, containment and minimum-service recovery, then record the first recovery step that fails.
04 / Evidence
Ask for evidence of the combined outcome.
Retain agent objectives, shared inputs, payment queues, liquidity usage, dependency failures, intervention points and recovery times. State which assumptions came from the simulator and which outcomes were observed in the firm’s own exercise.
- The payment simulator models system participants with different objectives and strategies.
- Agents with different objectives may still react to a shared signal and shift payment timing or liquidity demand together.
- Test a common liquidity shock alongside loss of a shared payment or orchestration service, then measure containment and minimum-service recovery.
- Record the first recovery step that fails and assign it to the payments or resilience owner.
Question
If several agents react to the same liquidity signal, what evidence shows their combined behaviour will not create avoidable delays or gridlock?
Ask for the scenario assumptions, shared signals and payment outcomes needed to test the combined behaviour of system participants.
Evidence
A scenario showing agent objectives, shared signals, queue effects, liquidity buffers and the intervention trigger.
Ask for the simulator assumptions and a firm-specific result from a test that includes a common shock.
Source trail
BIS, Bank of England, Japan Ministry of Finance, Financial Stability Board, CNIL and primary company sources
The judgement is an editorial interpretation. The G7 exercises are planned; the FSB describes its final practices as a practical toolkit.
Reading the signals
Different decisions require different evidence
Separate controlled research from observed outcomes, map shared dependencies, and test recovery when agents respond to the same shock.
Collective behaviour
Individually sound decisions can still interact badly.
Use the project’s variables—payment timing, liquidity use, queue effects and shock propagation—to shape a firm-specific scenario. Keep simulator assumptions separate from evidence observed in the firm’s own test.
Governance reference
The FSB’s final sound practices are a toolkit, not a new rule.
The FSB describes its 12 sound practices as a practical toolkit that financial institutions can tailor and integrate into existing frameworks. Boards and senior management are encouraged to use them when refining AI governance, risk management and controls; the release presents no new rule.
Independent assurance
Access terms shape what an external evaluator can establish.
Anthropic says six METR researchers have employee-like access to internal tools and risk-assessment material. METR can publish its findings and Anthropic says it cannot veto publication, though it can require redaction of defined categories such as customer data, privileged material and model architectures. This is a provider-specific arrangement, not a sector-wide standard.
Executive challenge
Three questions from the week
Carry one into a committee, 1:1 or control review.
- If several agents react to the same liquidity signal, what evidence shows their combined behaviour will not create avoidable delays or gridlock?
- Which critical payment or orchestration service would stop several agents at once, and can minimum service be restored if the normal control plane is unavailable?
- What independent evidence supports the provider’s claims about agent performance, limitations and safeguards in the workflow we plan to use?