The problems this exists to solve.
How it works for your team, day to day.
Examiner-ready evidence, continuously
Every AI interaction is logged, policy-mapped, and exportable against NYDFS Part 500, DORA, and SR 11-7 expectations. When the exam letter arrives, the AI section becomes a filter-and-export exercise instead of a quarter-long project.
MNPI and client data stopped at the prompt
Classifiers for material non-public information patterns, client identifiers, and account data run inline at sub-38ms. Deal names, restricted tickers, and client PII are redacted before a prompt leaves the desk — in the browser, in desktop AI apps, and in the IDEs on the quant floor.
Deploys inside bank constraints
SSO through your identity provider, MDM push through your existing endpoint estate, data residency by region, and no new inline network device for your architecture review board to assess. Procurement receives SOC 2 Type II and ISO 42001 documentation on request.
The questions we hear most.
How is MNPI actually detected?
Layered classifiers: restricted-list matching for names and tickers, pattern detection for deal and position data, and contextual models for unstructured material information — all evaluated inline before the prompt transmits, with the redaction preserved in the audit trail.
Where does our data reside?
Regional residency options are available, and inspection happens inline — prompt content is processed for policy evaluation, not retained for model training.
Does this help with DORA?
Yes — AI tools your workforce uses fall inside DORA's ICT-risk perimeter for EU financial entities. AccuroAI provides the usage register, control evidence, and incident trail that scope expects.
Will inspection add latency on the trading floor?
Inspection runs at sub-38ms p99 — below human perception. No workflow we cover routes order flow through AccuroAI; we govern AI prompts, not trading systems.