Financial Services

Governance infrastructure for autonomous trading and financial commitment decisions.

Every freeze decision, fire-sale trigger, and liquidity injection — cryptographically recorded before execution, independently replayable by regulators without access to your systems.

DORABasel IIIMiFID II

The problem

Autonomous trading systems, credit scoring models, and risk engines make thousands of decisions per day — but the hardest decisions are the commitment decisions: freeze assets, execute a fire-sale, inject liquidity.

Each commitment must be auditable, each model change must be governed, and regulators require evidence that governance occurred before the action, not a summary written months later.

Today's financial institutions have fragmented risk feeds and post-hoc logging. Neither answers the regulator's question: was the system mathematically incapable of committing unless the evidence justified it?

The Financial Commitment Firewall

RTR sits between fragmented risk signal sources and high-stakes institutional actions. Five financial signal feeds — credit, liquidity, market integrity, endpoint risk, and network coherence — feed into the RTR governance layer. No freeze, fire-sale, or liquidity injection proceeds unless all four invariants pass simultaneously:

Gate invariant: H ≤ Θ_H ∧ C ≥ Θ_C ∧ S ≥ Θ_S ∧ Q ≥ Θ_Q H = epistemic uncertainty (must be below risk policy bound) C = model coherence (must exceed agreement threshold) S = safety metric (VaR, drawdown, concentration — within bounds) Q = quorum (Byzantine-resistant signal source agreement)

This is not a dashboard. It is a mathematical commitment firewall.

Key actions governed

ActionRisk without governanceAGTS gate result
Freeze assets / limit withdrawals Auto-triggered on ambiguous signal → erodes depositor trust HOLD until uncertainty resolves; commitment requires model agreement
Fire-sale (forced liquidation) Cascading market impact if triggered on noise Gate prevents auto-commitment; prudential profile can mandate human override
Liquidity injection Misallocation if injection triggered without coherent evidence G2 Financial Validity requires compliance evidence before commitment

Gate mapping

GateEvidence typeFinancial application
G1 Semantic Validity Bootstrapped CI on model performance (H ≥ 0.40) Backtest confidence intervals on model update; CI must not span threshold
G2 Financial Validity Ablation delta across signal sources (C ≥ 0.40) Attribution of P&L change or risk spike to specific model parameter update
G3 Operational Validity Protected metric deltas (E ≤ 0.60) No degradation in VaR, drawdown limits, concentration ratios, liquidity coverage ratio
G4 Policy Admission Independent validation harness Evidence from independent model validation, not the trading system itself; ATTESTED classification required
G5 Cryptographic Finalization Sovereign Authority key ceremony Risk committee sign-off via HSM-backed Sovereign Authority; no soft authorization

Adversarial resistance

A naive governance gate commits when a majority of signal sources vote to proceed. The RTR gate commits only when all four invariants simultaneously pass. In adversarial scenarios:

AttackNaive outcomeRTR outcome
Byzantine signal source (network feed → 0.15) Majority still commits Quorum invariant fails → HOLD
Unsigned feed (tampered signal, missing signature) Accepted into vote Evidence classification fails G4 → HOLD
Threshold boundary (all sources at ~0.65, just below threshold) Majority commits Coherence invariant fails → HOLD
Coordinated deception (3 of 5 sources compromised) Majority commits G2 Financial Validity fails (no ablation basis) → HOLD

Closed loop in action

A credit model is authorized for deployment. During operation, the execution trace records a series of decisions. The variance record computes the drift between the authorized risk profile and the observed outcome distribution.

If variance exceeds omega_threshold: classification: BREACH omega_breach: true → visible to every monitor watching the log → without the monitor needing access to the bank's systems

A trading firm can replay any model-update authorization, showing the exact backtest results, the risk metrics before and after, and the risk committee approval signature. A regulator investigating a market event gets not a summary report written afterward, but the actual gate evidence from the moment of the decision.

Regulatory alignment

DORA Art. 8, 11, 25, 26

ICT risk management, business continuity, algorithmic trading controls, third-party ICT risk

Basel III Pillar 2 §763

Governance of model risk — AGTS provides the machine-readable evidence format

MiFID II algorithmic trading

Pre-trade risk controls, kill switches, evidence of governance before execution

ECB TRIM / SR 11-7

Targeted review of internal models — AGTS compliance report satisfies the evidence format gap

CFO/CRO positioning

With AGTS, you can prove this firewall will never auto-freeze deposits, trigger fire-sales, or inject liquidity unless the models agree and the policy says it's safe — and you can show that to regulators months later with a permalink to the exact gate evidence from the moment of the decision.

Model risk governance in 60 seconds → See the financial plugin API → Talk to us about financial services →