Market risk owns market risk. Credit owns credit. Treasury owns liquidity, finance owns capital and the path an event takes between them belongs to nobody.
The disciplines are mature; expertise was never the failure point, transmission is. A spot price move becomes a margin call, then a funding requirement, a counterparty exposure, capital consumption, inside one trading session, across four teams working from snapshots taken at different times on hierarchies that do not reconcile. Nobody owns that path; almost nobody can trace it. That is what we have built Atoti to change.
Every number already exists somewhere in the bank. What is missing is the ability to link them while the decision is still live.
The cost shows up in many ways. The cross-functional answer arrives after the decision. A hedge sized against one breached limit raises counterparty exposure or triggers a margin call elsewhere, so the fix becomes the next problem. And where single-name exposure cannot be consolidated across derivatives, financing, prime brokerage and committed facilities, the firm falls back on conservative limits, or walks away from business a competitor will write.
One suite
The Atoti Enterprise Risk Suite puts market risk, counterparty credit, xVA, FRTB and liquidity on one configuration API and data model across the trading book; liquidity, IFRS9 and IRRBB across the banking book. A scenario engine cascades shocks through every relevant metric; a Limits and Sign-Off module governs and audits the results. Share the hierarchies and multiple breaches resolve into one event with one root cause. This is not an upstream data problem. The layer that has to be common is where risk is aggregated and interpreted, so your existing FRTB and xVA engines carry on, and you add one stripe at a time.
Two answers, one engine
Breadth first, precision second, both at once. The Scenario Engine approximates dozens of scenarios in seconds off pre-computed sensitivities, accurate enough to show which portfolios and counterparties are worst hit, since nearly all the uncertainty is in the shock itself, because you aren't sure on the day quite what you are facing. In parallel, it reprices the few that matter in full, at regulatory accuracy. The approximations point at the problem; the precise numbers tell you what it is and how bad it gets. Firms that can only do the second still produce the first during an event in a spreadsheet, off platform, with no audit trail.
Where AI fits
Most firms run a handful of scenarios, because each one takes weeks to build and sign off. Agents change that arithmetic: dozens generated on the fly, mid-event, approximated in seconds. That is a far wider view of where you are exposed, and of how deep the hole goes and more findings than a team can triage in the time available. The engine stays the source of truth; agents query and explain it, and every assertion traces back to an aggregation that a human can reproduce and a regulator can audit. Deterministic hierarchies and tools make agents faster and less error-prone than on an ordinary database.
Atoti Intelligence runs against whichever LLM you have approved, inside your perimeter, and MCP lets your own agents query risk directly.
Where to start
Ask how long it takes your firm to answer a question that crosses these risk functions. Not how long the calculation runs, how long from the question to a defensible answer in front of the person who asked it. Most institutions have never measured it. If your number is uncomfortable, you are who we are building for.
Join us in London on October 21 at the Waldorf Hilton to see how a specialized AI agent, designed for risk, is changing the way risk teams work - grounded in your data, your measures, your hierarchies.
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