London-based G.H. Financials has gone live with Baton Systems’ intraday liquidity management platform, bringing cash balances, margin requirements and collateral positions across more than 100 nostro, CCP and carry broker accounts into a single near-real-time view. The independent clearing firm, which processes over 800 million futures contracts a year for professional traders, deployed Baton’s Balance Manager and Exposure Manager capabilities across 17 currencies, multiple legal entities and several time zones, with key account connectivity established within eight weeks of the project starting.
The deployment consolidates data that G.H. Financials previously had to pull together from separate systems and reporting cycles. Reconciling cash positions against initial and variation margin obligations at each CCP and carry broker had meant working across multiple portals and reports, leaving the firm without a continuous picture of where its funds and obligations sat during the trading day. Baton’s platform now provides the firm with a single view incorporating margin requirements, collateral on deposit and any excess or deficit against pledged collateral at each venue, time-stamped and updated as venues release new information.Freeing trapped liquidityFor G.H. Financials, the deployment addresses challenges that have grown alongside the business, as the firm is now a member of more than 20 exchanges, operating from offices in London, Chicago, Hong Kong and Kolkata, with rising volumes sharpening the cost of an incomplete view. “With any business that grows quickly, you sometimes need to take a step back,” says Steve Plestis, Head of Sales at G.H. Financials, in conversation with TradingTech Insight. “Yesterday’s records are today’s averages, especially with the volatility we’ve seen.”
That fragmentation carried a direct funding cost. “If you don’t have a real-time view, then by definition you’ve got a suboptimal liquidity scenario – you have cash sitting in places it doesn’t necessarily need to be,” says Plestis. With the platform live, the firm can see at any point where its cash is held, whether it needs to be there, and in which currency, allowing it to move funds more deliberately and hold less against the same set of obligations. As a non-bank FCM operating with zero debt and no leverage, G.H. Financials cannot absorb funding inefficiency onto a balance sheet, and freeing trapped liquidity translates into headroom to take on business. “By being more efficient in the liquidity space, we’re able to provide more capacity to our clients,” notes Plestis.The platform draws granular balance and transaction data directly from Swift messages, allowing the firm to monitor individual payments and receipts and to fold incoming cash into its regulatory capital calculations, something Plestis says had previously been difficult to do with the necessary speed.
Connectivity and configuration
For Baton, the work extended infrastructure the firm already runs for banks and larger FCMs rather than building a new stack. “We haven’t built something specific to G.H. Financials,” says Alex Knight, Head of EMEA at Baton Systems. The Balance Manager, exposure management, data normalisation and modular deployment components were already part of the platform; the project centred on configuring them for the firm’s account coverage, entity structure and venue connectivity, and on connecting to accounts and counterparties Baton had not previously integrated. Knight describes FCMs as an important and distinct market segment, and says the components deployed for the segment are largely the same ones the firm uses across its broader base of bank clients.
The implementation timeline of eight weeks covered the critical connectivity. Bank data came in via Swift, mapped into Baton’s canonical model; CCP data drew on direct connectivity the firm had already built, subject to documentation approvals; and carry broker data, along with a small number of CCPs, was consumed through files that G.H. Financials passed to Baton over SFTP. The firm’s finance and treasury operations teams worked alongside Baton to validate the data mappings against G.H. Financials’ own structures.
Building for the future
Both firms position the deployment as groundwork for a market moving towards always-on trading and tokenised collateral, while stopping short of claiming either capability is in place. “The install as it stands right now is not required to support tokenised collateral,” says Knight. “We’ve got readiness for tokenised collateral, and readiness for agentic AI use against the platform.” The argument the firm makes is that the operational demands of programmable, always-on markets raise the bar for control rather than lowering it. “Neither tokenisation nor AI removes the need for operational control. In fact, they increase it,” Knight says. “Faster, programmable, always-on markets can only work when a firm has an authoritative, real-time view of the location of all its assets and obligations.” On agentic AI, Knight is clear about where Baton sits: “We’re not a provider of agentic AI; we’re a facilitator.”
The timing tracks a wider shift in when markets trade. CME Group launched 24/7 trading for its cryptocurrency futures and options on 29 May 2026, and has extended round-the-clock access to selected metals and energy contracts, moving weekend risk into hours when traditional collateral movement does not operate. Plestis says G.H. Financials is watching that shift on behalf of clients weighing participation in the new products. ” 24/7 has been a topic of discussion across the industry for a good year or so now, with the CME’s recent introduction of its 24/7 product,” he says. “While we’re not yet live with tokenisation for the movement of collateral, we’re watching very closely and ready to act as and when we need to.” The mechanics of weekend markets are what make the question concrete: “When you consider that we may need to move collateral over a weekend, the only way that can happen is through a tokenised version,” Plestis says. “That’s why it’s been incredibly important for us to have a platform we can deploy relatively quickly if we need to.”
The consolidated data set also opens a use case the firm did not have before. With historic intraday and end-of-day data now in one place, G.H. Financials can begin to analyse where it holds cash and how much it needs to hold. “Now that we’re getting that data, we can analyse it, track it and start to understand – potentially using AI – what the optimum buffer is to hold in a certain location or currency,” Plestis says, pointing to buffer optimisation as a task its risk and client service teams could take on as the data accumulates. Whether the industry’s move towards weekend trading and tokenised collateral arrives quickly enough to test that readiness remains, for now, a question for G.H. Financials’ clients to answer.
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