Head of Thought Leadership, State Street AlphaSM
Head of Global Client Management, UK Investment Services, State Street
Head of Coverage, Central and Northern Europe, State Street
Head of Alpha Platform Sales, EMEA, State Street
An effective data management strategy can help firms uncover new insights, better serve emerging stakeholder requirements, and bring new products to market faster.
But firms face several data related challenges. The sheer volume of data can be overwhelming. Fragmented, siloed data makes it difficult to maintain an enterprise-wide, single source of truth. Aggregating and reconciling data from multiple sources is time-consuming and complex, hindering investment decision-making and increasing operational costs.
In a discussion moderated by Frank Smietana, head of Thought Leadership at State Street AlphaSM, Brian Allis, head of Client Management, UK Investment Services, Jochen Kühn, head of Coverage, Central and Northern Europe, and Simon Brown, head of Alpha Platform Sales, EMEA explore how asset managers are rethinking their operating models to address data management challenges and support new opportunities during a time of rapid and intense change across the industry.
Simon: The asset management industry is going through one of the most intense periods of change that I’ve seen over the last 20 years. When you look at the current macro environment, investment managers are faced with the challenge of stabilizing flows while implementing growth agendas. And they need to serve the evolving needs of their investors in an environment of increasing regulatory oversight.
At the same time, many firms are saddled with complex and fragmented infrastructure that’s been created or acquired over years to serve individual investment teams. This creates significant “technology debt” across the organization. As a result, firms are actively assessing their business plans and looking at the next five to 10 years to determine if their current operating model can deliver on their longer-term goals.
We are in discussion with many investment managers on how we can partner and help them affect transformational change to improve their operating environment, support the launch of new investment products and better serve their clients in a scalable and sustainable manner.
Jochen: Asset managers have multiple obligations to their investors and regulators that they currently address with a patchwork of disparate systems and data sources. It’s very difficult to change this operating environment. Firms struggle with the complexity of managing and maintaining so many applications and data models. Instead of investing in their growth agenda, clients are spending scarce resources keeping these complex environments running.
Brian: Asset managers face significant challenges. How do they differentiate themselves from competitors given the considerable overlap in product offerings? Secondly, particularly in Europe and the UK, firms have become increasingly disintermediated from their customer base. So they struggle to build a narrative that resonates with shifting investor demographics. While they’ve traditionally catered to older, financially conservative investors, they need to start thinking about younger, more digitally savvy clients.
Simon: As end investors become increasingly sophisticated, the asset classes, investment products and solutions on offer from an investment manager will continue to evolve. Many firms are considering how to extend their distribution into wealth channels to serve individual mass affluent and high net worth investors as well as their more traditional investor base.
The low interest rate regime that began in the wake of the global financial crises left investors chasing yield and looking for diversifying products and asset classes, like private equity. But not every asset manager can support those investment vehicles.
Lacking the requisite technology and expertise, many asset managers who traditionally supported only publicly traded assets face enormous barriers to onboarding private assets in a cost effective and scalable manner.
Brian: Sophisticated investors, such as private equity firms, have been amassing assets in this space for decades, leaving newcomers at a disadvantage when it comes to determining realistic valuations for these opaque and complex assets. Secondly, firms need to acquire the technology and expertise to manage private assets at scale. You can’t retrofit the existing infrastructure used to support public assets.
Simon: Private assets also present significant data challenges. They rely more on unstructured data and data that’s sourced less frequently. General partners distribute data in different formats depending on the underlying asset type.
The biggest challenge is getting access to all the required data and normalizing it so that it can be used to drive decision making. If they’re managing both public and private assets, firms need a unified view of holdings and exposures. That’s especially critical during times of market turmoil and liquidity shocks.
Managing private assets is the last bastion of the spreadsheet world. It’s typically a very fragmented set of infrastructures and counterparties assembled over many years. Each sub-asset class requires different valuation models and cash flow projections. Key data is contained in documents that must be parsed to extract salient information such as deal terms and lock up periods.
The ability to offer private investments at scale requires a fundamental rethink of infrastructure and processes. While there’s tremendous opportunity for firms to differentiate their product line-up to clients, there’s also significant operational and risk challenges to solve for.
Simon: Given the sheer scale, size and speed with which asset managers must adapt to regulatory change, we have observed a full range of responses: from emergency mode where they adopt only what’s needed to meet a regulatory deadline, to tactical where it’s well-thought-out but specific to a particular regulation, to strategic where they’re looking to leverage commonality of data elements across different regulatory reports.
The benefit of taking that more strategic approach is that firms can centralize the underlying data infrastructure and analytics, and then just focus on reporting to the various regulators, based on the individual requirements, using a common data model to address these different regulations. This saves time and helps ensure flexibility as these needs evolve over time.
Growing regulatory complexity requires firms to create new data domains as well as reporting formats. And that’s even more reason to have a scalable, future-proof operating model for data. To Andy’s point, many asset managers take very tactical solutions – but until you solve the big problem of creating a single, centralized repository encompassing all your data and designing a strategic data model, then every time a new requirement comes along, you build another silo and end up adding to that unsustainable technology debt. Once you solve the big challenge, the next regulatory reporting obligation simply requires adding a new domain to your existing data model.
Simon: I think of the evolution occurring in three stages. At the most basic level, data is siloed across multiple servers and individual workstations. It’s cumbersome to access data, and using it to support reporting, performance and risk functions requires multiple transformations. There’s massive duplication of effort and no ability to track data lineage.
Further along are firms with some level of organized data repositories, but limited ability to share data across teams without significant manual processing. Perhaps they have centralized public market data in one place and private market data in another. Alternatively, firms may have a single warehouse, but it is loaded with snapshots from various systems rather than being tightly integrated with the source, creating time disparities when comparing data in the warehouse across different source systems. Without a single source of truth, investment professionals grapple to reconcile multiple versions of the same data, and decision making is still hampered by excessive manual processing required to assemble a single view of the correct data.
The ideal state we see in this evolution is a centralized repository, accessible across the enterprise, with extensive data lineage and fit for purpose data views. These repositories offer self-service reporting and business intelligence tools that enable investment professionals to interact with their data, and uncover insights with just a few clicks.
In the future, investor meetings will be an interactive, dashboard-driven experience. Rather than scrambling to assemble static presentations, firms will be able to answer questions in real time, drill down to any level of detail required, accessing data from multiple domains.
Jochen: As firms get their data infrastructures in place, use of AI and machine learning will be pervasive, whether that’s to generate alpha, better serve clients, or to design new investment offerings. All of this requires consistent, accurate and complete data.
Simon: The ability to support growth agendas, whether by offering new products, expanding into new asset classes and geographies, or launching new business lines all require a robust and flexible data foundation. Forward-thinking asset managers that re-evaluate their operating models and retire accumulated technology debt will be well-positioned to thrive in an environment of constant change.
Simon: Alpha combines State Street’s software technology with our outsourced services, connected to a growing ecosystem of third-party data, analytics and application providers. Our front-to-back platform supports the entire investment lifecycle across asset classes, while our global technology teams build, validate and maintain hundreds of interfaces with those external providers. This enables asset managers to focus on extracting meaningful insights from their data, rather than expending scarce resources on undifferentiated and, frankly, expensive activities.
Jochen: Effective data management and delivery is central to our vision, underpinned by the Alpha Data Platform and Services. This foundation leverages a modern, cloud-native data repository, enabling firms to capture, curate and validate the massive volumes of data generated by their investment processes, and enrich it with externally sourced data. This ability to extract data-driven insights in near real-time represents a fundamental paradigm shift for the industry.
Simon: Alpha is groundbreaking. It affords asset managers the opportunity to create an integrated and optimized front-to-back operating model rather than merely connecting together a patchwork of different systems and counterparts, which has been the industry norm for decades. The platform allows optionality and interoperability, leveraging external and internal capabilities, including portfolio management, risk models, applications and services.