Institutionalisation Is About Staying Power

By: Mel Sutton, ALTALLO - Founder

Published: 2026-06-05 · Read time: 9 min · Category: Interview

Leo LaForce of Opus Fund Services on why operational excellence, transparency and a modern data architecture now decide which managers attract and retain institutional capital.

[HOST]: The industry often equates institutionalisation with meeting minimum standards. Where do you see the gap between firms that are compliant and those that are genuinely institutional in how they operate?

[GUEST]: Looking at the question through the lens of emerging managers, institutionalization is ultimately about staying power. Ensuring your policies, processes, and controls are high enough quality to give investors the confidence you can execute your strategy consistently and true to the way you say you will. So they don't feel there are compromises they have to make in order to invest in a fund. Those managers that are genuinely institutional have a complete operating model, including operational infrastructure, risk management maturity, and governance framework. In short, a complete business, not just investment management.

[HOST]: Operational due diligence has become significantly more forensic in recent years. What are investors asking today that they were not five years ago, and what is driving that shift?

[GUEST]: Institutionalized operations are now table stakes for managers looking to scale to the hundreds of millions or billions. Investors now have rigorous expectations for a fund manager to be investable. A manager's operational roadmap can no longer be an afterthought. Operational due diligence (ODD) will highlight all the potential risks that the investor is not getting compensated for taking. In the current environment, if two funds have similar performance but one is operationally solid and the other has operational gaps, investors will choose "solid" 100% of the time. ODD is no longer just a checklist-driven exercise but instead drills down into all aspects of manager resiliency, including service providers, third-party oversight, cybersecurity, and use of AI.

[HOST]: Many fund managers still rely on layered systems and manual processes behind the scenes. At what point does that become a structural risk rather than just an operational inconvenience?

[GUEST]: Strong operations can be a meaningful differentiator for managers, particularly in this tight capital environment where performance alone isn't enough to stand out anymore. When there are multiple managers with similar strategies, track records, or pedigrees, whichever manager can clearly articulate their operating model, its ability to scale, and to mitigate operational risks, will have the edge. The cleaner the manager's data architecture and more systematic their process controls are, the more compelling that story will be. Again, through that emerging managers lens, managers who invest in a robust operational foundation early on, and can clearly communicate it, will be in a stronger position to attract and retain institutional capital.

[HOST]: You emphasise transparency not just in outputs but in underlying processes. How is the definition of transparency evolving from an investor's perspective?

[GUEST]: Transparency is more critical than ever, and another area where a manager who can provide a "Prove It Button" has an edge. Transparency helps build credibility and trust that the people, processes, and controls do what the manager says they do. From an operational perspective, investors now want to validate cash controls, valuation policy adherence, independent reconciliations, calculations of the NAV, allocations and fees, and investor statement reporting. All with consideration on how that work actually gets done and how straight through this lifecycle is. And confirm that the operational infrastructure and controls they see today will still be effective in the future as a manager grows.

[HOST]: There has historically been a tension between customisation for investors and operational scalability. Is that still a real trade off, or has technology fundamentally changed that dynamic?

[GUEST]: It comes down to operating model. A clean data architecture, such as a single data warehouse design, enforces accuracy and makes it easier to provide investors with real-time accuracy to their data, versus a fragmented data model that brings higher risks of discrepancies and requires someone to stitch that data together. The other is digitalization, which now helps provide personalized investor experiences across the lifecycle at scale without compromising controls. Digital subscriptions are a good example. Investors now can complete subscription documents online through tailored smart forms that guide them through only the relevant questions and documentation requests. They can also now easily configure their own statements, using independently produced data from the fund administrator, with the analytics and timeframes that matter to them. Technology has certainly improved investor UX and access to critical data faster in the ways they want to consume it.

[HOST]: Automation is often positioned as an efficiency play. In your experience, where does it create strategic advantage rather than just cost savings?

[GUEST]: Investors are looking for managers to demonstrate automation-driven efficiencies, enabling their team to focus on value-added activities versus performing manual tasks. Many managers are now taking a "quantamental" approach to front office activities, using AI and automations to do the initial idea generation and fundamental analysis, freeing up their investment team to then apply their human expertise and make final portfolio decisions. This same approach is analogous to the back office as well, across areas like trade matching and settlement, portfolio reconciliations, compliance monitoring, and investor communications. Redirecting people's time toward actions that enhance performance, portfolio or operational, and deepen relationships with investors.

[HOST]: Emerging managers and established firms start from very different positions, one building from scratch and the other managing legacy complexity. Are their operational priorities beginning to converge?

[GUEST]: Nowadays, thanks to technology, institutionalization is more about structure, repeatability, transparency and governance and less about size or lifecycle stage. Operational excellence is increasingly, and should be, a priority for every manager. Do your operations support your investment strategy or constrain it? That's the bottom line. Proper service provider selection can help address this and enable emerging managers to leapfrog and evidence institutional-quality infrastructure and investor servicing capabilities from Day One within a variable cost structure. In many ways, with the turnkey technology solutions on offer, emerging managers have a competitive edge in being able to build "first time right" with tools that more easily adapt and keep pace with change. But the right partners, especially the fund administrator, can help managers of any stage reduce their operational complexity by delivering a centralized enterprise data model, consolidated modern technology stacks, and integrated digital workflows that embed transparency and easy oversight across the operational and investor lifecycles.

[HOST]: Data fragmentation remains a persistent issue across the industry. How important is having a single source of truth in practice, and what are the consequences of not having one as firms scale?

[GUEST]: The traditional benefits of having a single source of truth still do, and always will, persist. Having a centralized data warehouse "golden copy" enforces accuracy, empowers more confident decision-making, and enables easier oversight. The more fragmented a manager's data structure, the more potential for errors, doubt, and operational risk. That is not a scalable formula. A single data source is also increasingly important in terms of the ability to adopt and evolve many of the exciting technologies such as robotic processing and agentic AI. The simpler and straightforward your data architecture, the easier it is to develop, train, deploy, and adapt intelligent automations. And if you cannot meaningfully embed AI into your operations as a manager (or service provider) you will definitely be left behind.

[HOST]: You have been recognised for both technology and client service. In a market where many providers lean heavily toward one or the other, how should managers think about that balance when selecting a partner?

[GUEST]: Historically fund administrators scaled linearly, as they add clients they need to add more headcount. Because behind the scenes, many processes were manual and/or spreadsheet dependent and in almost all cases humans had to operate the technology. Now with intelligent automations, technology itself (robotics, agentic AI) can operate the systems and perform the traditional "maker" roles. Freeing human employees to focus on oversight ("checker") and invest the time savings in proactively servicing clients. But to be able to adopt AI and automations at scale, you must have the right operating model as the foundation: single data source architecture, clean process hygiene (STP), and streamlined non-legacy technology. Also, the in-house knowhow to develop, deploy, and adapt agentic AI. Outsourcing your automations will invariably pose governance and potentially data privacy issues. So, managers should think about how well a fund administrator can demonstrate a suitable operating model that will enable them to have the long-term capacity to service their clients with the attention they deserve.

[HOST]: Looking ahead, as investor expectations continue to rise, where do you see the next layer of differentiation coming from for fund managers beyond performance alone?

[GUEST]: The managers that can tell the best complete story, demonstrating both investment and operational excellence. The ability to prove they are an institutional-quality business and sustainable partner for investors over the long-term. Able to manage money in a controlled, consistent, scalable way. And that requires the foundational modern operating model we've been discussing, whether it's their own or co-sourced with a fund administrator partner. Centralized data architecture, a streamlined technology stack with integrated digital workflows, systematic process controls, and embedded transparency across the operational and investor lifecycles for efficient oversight. That's a winning story that resonates with institutional allocators and inspires long-term confidence.