Baton Systems introduces portfolio optimisation to improve collateral allocation
27 October 2026 UK
Image: Nichaphat/stock.adobe.com
Baton Systems, a provider of post-trade processing solutions, has introduced a portfolio optimisation capability for collateral managers, treasury teams, and clearing operations.
It is designed to identify economically efficient, operationally achievable allocations across a portfolio of cash and securities and a portfolio of obligations, rather than optimising one margin requirement at a time.
Baton's optimiser uses multiple optimisation models including mixed integer linear programming, stochastic programming, and multi-period optimisation to assess multiple assets and obligations simultaneously.
It combines a consolidated view of collateral sources and uses with normalised eligibility schedules, concentration limits, internal policies, asset economics, and venue-specific delivery constraints.
Teams can weigh objectives such as reducing delivery cost, preserving high-quality liquid assets, or limiting the number of movements, then compare scenarios before choosing an allocation.
The selected outcome can flow into Baton's instruction and movement workflows, connecting analysis to action.
Baton Systems says the capability is modular, allowing firms to begin with eligibility, optimisation, or execution and expand over time without replacing their existing books and records.
Arjun Jayaram, founder and CEO of Baton Systems, says: “Collateral optimisation only creates value when the answer is economically sound and operationally executable.
“Our advanced capability brings portfolio-wide decision-making together with the eligibility intelligence and movement workflows firms need to act.
“It gives clients a practical way to lower the cost of collateral, protect scarce liquidity, and reduce unnecessary operational activity, while working with the systems and relationships they already rely on.”
It builds on Baton's established Core-Collateral infrastructure, including real-time inventory and eligibility information, and automated movement workflows across connected venues.
The same framework can support straightforward central counterparty use cases initially and more complex, multi-venue optimisation as firms mature.
It is designed to identify economically efficient, operationally achievable allocations across a portfolio of cash and securities and a portfolio of obligations, rather than optimising one margin requirement at a time.
Baton's optimiser uses multiple optimisation models including mixed integer linear programming, stochastic programming, and multi-period optimisation to assess multiple assets and obligations simultaneously.
It combines a consolidated view of collateral sources and uses with normalised eligibility schedules, concentration limits, internal policies, asset economics, and venue-specific delivery constraints.
Teams can weigh objectives such as reducing delivery cost, preserving high-quality liquid assets, or limiting the number of movements, then compare scenarios before choosing an allocation.
The selected outcome can flow into Baton's instruction and movement workflows, connecting analysis to action.
Baton Systems says the capability is modular, allowing firms to begin with eligibility, optimisation, or execution and expand over time without replacing their existing books and records.
Arjun Jayaram, founder and CEO of Baton Systems, says: “Collateral optimisation only creates value when the answer is economically sound and operationally executable.
“Our advanced capability brings portfolio-wide decision-making together with the eligibility intelligence and movement workflows firms need to act.
“It gives clients a practical way to lower the cost of collateral, protect scarce liquidity, and reduce unnecessary operational activity, while working with the systems and relationships they already rely on.”
It builds on Baton's established Core-Collateral infrastructure, including real-time inventory and eligibility information, and automated movement workflows across connected venues.
The same framework can support straightforward central counterparty use cases initially and more complex, multi-venue optimisation as firms mature.
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