A conversation with Brian Allis, Jochen Kuehn and Simon Brown. 

Data is central to an asset manager’s investment process. 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.

Brian Allis, SVP, Global Client Management, UK Investment Services, Jochen Kühn, SVP and Head of Coverage, Central and Northern Europe, and Simon Brown, SVP and Head of Alpha Platform Sales, EMEA sat down with Frank Smietana, Head of Thought Leadership at State Street Alpha to discuss how asset managers are rethinking their operating models to address data management challenges and support new opportunities during a of time of rapid and intense change across the industry.

Frank Smietana Frank Smietana

Head of Thought Leadership,
State Street Alpha

Brian Allis Brian Allis

SVP, Global Client Management, UK Investment Services, State Street

Jochen Kühn Jochen Kühn

SVP, Head of Coverage, Central and Northern Europe, State Street

Simon Brown Simon Brown

SVP, Head of Alpha Platform Sales, EMEA, State Street

“Asset managers are leveraging data in a number of ways as they look to modernize their operating models, better serve investors and meet growing regulatory requirements.”

FRANK: What headwinds are asset managers facing as they look to modernize their operating models, comply with growing regulations, and address evolving investor requirements and demographics?

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 5 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 effect 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.

 

Frank:  We’ve touched on private assets as a diversifier. What data related challenges do clients face as they add private assets to their portfolios?

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.

 

“The ability to offer private investments at scale requires a fundamental rethink of infrastructure and processes.”

 

SIMON: 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 lineup to clients, there’s also significant operational and risk challenges to solve for.

 

Frank: Increased regulatory reporting requirements also depend on significant volumes of data from multiple sources. How are firms dealing with the data management challenges to support those requirements?

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.

 

Frank: Looking to the future, how do you see the use and management of data evolving for asset managers, and what will differentiate best in class organizations?

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.

 

“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.”

 

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 reevaluate their operating models and retire accumulated technology debt will be well positioned to thrive in an environment of constant change.

 

Frank: State Street has long understood the potential of helping firms leverage their data more effectively. What is State Street Alpha and how is it changing the data management landscape for investment firms?

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 life cycle 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.

 

“This ability to extract data-driven insights in near real-time represents a fundamental paradigm shift for the industry.”

 

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, be they portfolio management and risk models, applications, or services.

A conversation with Andrew Wilson, Brian Allis, Jochen Kuehn and Simon Brown. 

Data is central to an asset manager’s investment process. 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.

Frank Smietana Frank Smietana

Head of Thought Leadership
State Street Alpha

Andrew Wilson Andrew Wilson

SVP, Regional Head of Asset Managers Segment, EMEA, State Street

Brian Allis Brian Allis

SVP, Global Client Management, UK Investment Services, State Street

Jochen Kühn Jochen Kühn

SVP, Head of Coverage, Central and Northern Europe, State Street

Simon Brown Simon Brown

SVP, Head of Alpha Platform Sales, EMEA, State Street

Andrew Wilson, SVP and Regional Head of Asset Managers Segment EMEA, Brian Allis, SVP, Global Client Management, UK Investment Services, Jochen Kühn, SVP and Head of Coverage, Central and Northern Europe, and Simon Brown, SVP and Head of Alpha Platform Sales, EMEA sat down with Frank Smietana, Head of Thought Leadership at State Street Alpha to discuss how asset managers are rethinking their operating models to address data management challenges and support new opportunities during a of time of rapid and intense change across the industry.

 

“Asset managers are leveraging data in a number of ways as they look to modernize their operating models, better serve investors and meet growing regulatory requirements.”

 

FRANK: What headwinds are asset managers facing as they look to modernize their operating models, comply with growing regulations, and address evolving investor requirements and demographics?

ANDREW: 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 5 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 effect 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.

ANDREW: 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.

 

Frank:  We’ve touched on private assets as a diversifier. What data related challenges do clients face as they add private assets to their portfolios?

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.

 

“The ability to offer private investments at scale requires a fundamental rethink of infrastructure and processes.”

 

ANDREW: 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 lineup to clients, there’s also significant operational and risk challenges to solve for.

 

Frank: Increased regulatory reporting requirements also depend on significant volumes of data from multiple sources. How are firms dealing with the data management challenges to support those requirements?

ANDREW: 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.

SIMON: 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.

 

Frank: Looking to the future, how do you see the use and management of data evolving for asset managers, and what will differentiate best in class organizations?

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.

 

“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.”

 

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.

ANDREW: 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 reevaluate their operating models and retire accumulated technology debt will be well positioned to thrive in an environment of constant change.

 

Frank: State Street has long understood the potential of helping firms leverage their data more effectively. What is State Street Alpha and how is it changing the data management landscape for investment firms?

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 life cycle 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.

 

“This ability to extract data-driven insights in near real-time represents a fundamental paradigm shift for the industry.”

 

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.

ANDREW: 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, be they portfolio management and risk models, applications, or services.

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The material presented is for informational purposes only. The views expressed in this material are the views of the author, and are subject to change based on market and other conditions and factors, moreover, they do not necessarily represent the official views of Charles River Development and/or State Street Corporation and its affiliates.