Firm Profile:
U.S.-based RIA managing ~$150MM in AUM, focused on small- and mid-cap equity strategies with a growing base of family office and institutional investors.
Introduction
Emerging RIAs managing between $100–$250MM in AUM often reach a stage where growth begins to outpace the infrastructure that once supported it. At this point, firms are typically operating with lean teams, where investment professionals span multiple roles across research, execution and operations. Trading workflows are often supported by basic OMS functionality and a combination of manual processes, with broker relationships and liquidity access evolving organically over time.
This model is effective in the early stages of a firm’s development, but it becomes increasingly strained as AUM grows and trading activity becomes more complex. Larger order sizes, more frequent rebalancing and expanding strategy sets begin to place pressure on both execution quality and internal bandwidth. At the same time, allocator expectations shift. Execution is viewed as a core component of the investment process—one that must demonstrate scalability, consistency and adherence to best execution standards.
Against this backdrop, firms of this size face a familiar but critical question: how to scale execution capabilities in line with AUM growth without scaling overhead in parallel.
The Challenge
In this case, an emerging RIA had begun to experience strong performance in a small- and mid-cap equity strategy, driving increased interest from family offices, model platforms and institutional consultants. As inflows accelerated, so did the complexity of its trading activity. Order sizes grew beyond prior norms and became more sensitive to market impact – particularly in less liquid names – while execution required coordination across multiple brokers and venues, especially during rebalances and new position initiations.
Execution responsibilities were distributed across investment professionals, with portfolio managers directly involved in trade placement, allocation and post-trade reconciliation. This created a persistent trade-off between managing positions and managing execution, with time increasingly diverted away from core functions like research and portfolio construction.
At the same time, execution itself was constrained by both infrastructure and access. Its OMS lacked deep integration with execution venues and required manual intervention across the trade lifecycle, limiting its ability to scale efficiently. A relatively narrow broker network, combined with inconsistent access to crossing networks, reduced visibility into available liquidity and made it more difficult to source liquidity efficiently.
In practice, this often meant breaking up orders, working trades over longer time horizons or relying on a narrower set of counterparties—introducing both execution risk and operational friction.
Allocator due diligence reinforced these pressures. Institutional prospects began to probe more deeply into execution capabilities, asking how liquidity was sourced, how best execution was measured and whether the current model could support larger ticket sizes without introducing additional market impact. It became clear that the firm’s existing approach—while sufficient at a smaller scale—would not support continued growth.
Taken together, these factors introduced not only operational inefficiency, but strategic risk. Execution was emerging as a bottleneck in both day-to-day portfolio management and the firm’s ability to confidently scale AUM.
The Solution: Outsourced Trading with CAPIS
For this RIA, expanding its internal model would require more than incremental upgrades. Building an in-house trading desk would involve hiring dedicated personnel, investing in market data and transaction cost analysis tools, establishing connectivity to multiple venues and introducing redundancy for coverage and business continuity—representing a meaningful shift in the firm’s cost structure.
Rather than pursuing a full internal buildout, the firm elected to adopt a supplemental and outsourced trading model, engaging CAPIS to function as an extension of its investment team.
Through CAPIS, the firm gained immediate access to a well-established network of over 100 broker relationships, alongside connectivity to institutional trading venues including Liquidnet, Luminex and other crossing networks. This expanded reach improved the firm’s ability to source liquidity across market capitalizations and execute larger orders with greater efficiency. With multi-asset capabilities spanning equities, fixed income and derivatives, as well as 24/6 global coverage —including a dedicated overnight desk—the firm was able to operate with a level of continuity that would have been difficult to replicate internally.
At the same time, CAPIS supported the evolution of the firm’s technology stack. Drawing on experience across numerous OMS implementations, the team helped align the firm’s OMS with its workflow requirements while introducing a more mature, institutional-grade execution environment. Trade lifecycle processes—from order entry through allocation, booking and reporting—were streamlined, reducing manual intervention.
Operationally, this shift reduced the burden on internal resources by streamlining post-trade processes and simplifying middle- and back-office coordination. As a result, the firm was able to scale trading activity without expanding headcount or building additional infrastructure.
CAPIS operates under a pure agency model, ensuring that all trading activity is aligned solely with the client’s objectives, without conflicts tied to proprietary trading or internal liquidity pools. This preserved full control over investment decisions while enhancing execution outcomes.
The engagement was also consultative in nature. CAPIS worked with the firm to align execution strategy, broker relationships and commission management practices with its existing preferences, including accommodating client-directed trading and CSA programs.
The Result
The impact of the transition was immediate. Execution became more consistent, supported by deeper liquidity access and a more cohesive workflow. With expanded access to crossing networks and a broader broker network, the firm was able to source liquidity more efficiently for larger orders, reducing variability in execution outcomes and improving confidence when trading in less liquid names.
Internal resources were no longer consumed by the mechanics of trade execution and post-trade processing, allowing the investment team to refocus on core activities such as research, portfolio construction and client relationships.
From a cost perspective, the firm avoided the need to hire additional trading or operations personnel. Instead, it was able to align execution capabilities with growth while maintaining a lean operating model, avoiding the fixed costs associated with trading desk buildout, technology expansion and ongoing operational support.
Strategically, the firm was better positioned in conversations with allocators. Execution capabilities could be articulated with greater clarity and supported by institutional-grade processes, access to liquidity and transparent reporting. This proved particularly valuable in diligence conversations.
As a result, the firm was able to scale AUM without introducing proportional increases in cost or operational complexity, while reinforcing its credibility as an institutional-quality manager. Looking ahead, the firm was primed to pursue new opportunities —including larger allocations, additional mandates and expanded strategies— without concern that infrastructure would hold back growth.
Conclusion
For emerging RIAs, growth often exposes the limits of a lean operating model. The question is not simply whether to scale, but how to do so efficiently and sustainably.
By adopting a supplemental and outsourced trading model, firms can bridge the gap between ambition and infrastructure, achieving institutional-quality execution while preserving focus on alpha generation.
In doing so, execution is transformed from a bottleneck into a scalable, embedded capability—one that supports growth without requiring the buildout traditionally associated with it.