In today’s highly competitive market, Fund Treasury departments are being asked to execute the seemingly impossible task of meaningfully bending the cost curve of their operations, while balancing ever-increasing regulatory requirements, business risks, and product complexities. To meet these challenges, Olmstead believes that fund oversight must transform from a traditional process-based operating environment to a data-centric, risk oriented control model.
Most Fund Treasurers we speak with believe their current operations are manually intensive leaving the team with less time to perform value-added analysis critical to the business. The staff spends a significant portion of their time manually adjusting spreadsheets and preparing the data versus analyzing the results and assessing key risks.
In order to truly evolve their operating models, Olmstead collaborates with our clients to help evaluate the critical factors that impact the development and implementation of their future state vision. We recommend Treasurers ask themselves questions such as:
- Do we have a clear point of view on the reliability, lineage, and accuracy of all the data needed to perform our functions?
- Do we understand how our data is being consumed by the broader organization?
- Do we understand how emerging Fintech and the latest business intelligence tools are being leveraged to move people from processors to analysts?
- Have we optimized our service provider relationships?
- Do we have an organizational track record of successfully introducing transformation?
Data and Technology Empowerment
At the forefront of this evolution is improving data and embracing emerging technologies. In empowering their teams to be more data-centric, Treasurers need to understand how artificial intelligence, machine learning, and robotics can eliminate manual risky processes and enable predictive analytics. Recent industry examples include utilizing AI to extract information from regulations to identify new regulatory reporting requirements or creating exception-based dashboards to identify processing errors and missed SLAs. Another element of technology that can drive value is the service providers’ rapidly evolving data, portal, and API capabilities. Olmstead has often discovered that taking a fresh look at these new tools, that are not always fully deployed or optimized by asset managers, can result in significant opportunities to increase oversight efficiency.
Maximizing fund service provider relationships is another lever for consideration. As Olmstead’s Joseph DeRice recently outlined in Evolving Trends in Service Provider Oversight, leading firms are seeking to better leverage the provider’s control environment and additional outsourcing capabilities as a means of gaining scale. Understanding not just what a service provider is responsible for, but how they are executing, can enable an asset manager to evaluate processes across the entire ecosystem. This fresh look can unlock value by identifying redundant tasks and clarifying how oversight models can be tailored to deliver true risk mitigation including enhancing NAV validation and contingency.
Talent and Skill Sets
Finally, the movement to a data-centric operating model will rely on leadership commitment and new skill sets. While there is no substitute for the expertise the Treasurer’s staff traditionally possesses, there is an opportunity to augment their capabilities with more technologically oriented team members who work to structure data, improving efficiency and helping identify risk. The combination of business and technical domain expertise can build a powerful model that moves the team from processors to analysts.
The role of fund oversight will be increasingly complex given the overarching industry challenges. At Olmstead, we combine our deep industry knowledge and pragmatic experience with leading edge technology to help clients transform their operating models by re-imagining how data, emerging technology, and an analyst driven framework can enable the challenge of driving down costs while enhancing the value of their risk and oversight models.
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