Beyond digital transformation
18 Mar 2026
Joel Kornblum, head of Business Development and Relationship Management with RBC Investor Services, dives into how leveraging partnerships, proprietary development, and AI together, can help deliver competitive advantage through an integrated operating model
Image: RBC Investor Services
In an industry where digital transformation has become table stakes, leading asset servicers are discovering that competitive advantage no longer stems from a single technology strategy.
Instead, the most successful firms are those that leverage the latest and greatest solutions wherever they may find them — either through best-in-breed partnerships, proprietary platform enhancements, or leveraging artificial intelligence to enhance every aspect of their operating model.
This integrated approach represents a fundamental shift from the traditional binary decision-making on whether to build or buy that has dominated asset servicing strategy discussions.
Rather than choosing between developing capabilities in-house or outsourcing to specialised vendors, organisations are recognising that sustainable competitive advantage requires a continuous review of client needs and solutions development with a focus on finding the right technology — sourced externally, built in-house or developed using large language models and emerging AI capabilities.
As transaction volumes surge and regulatory requirements grow more complex, asset servicers face mounting pressure to deliver faster, more accurate service.
Meeting these challenges requires an operating model that leverages external innovation while maintaining the flexibility and control of proprietary solutions and AI.
Partnership as innovation
In a market characterised by rapid technological evolution and increasingly specialised client needs, sophisticated asset servicers recognise that building every capability in-house is neither practical nor strategically optimal.
The emergence of fintech providers with deep expertise in specific domains has created opportunities for established institutions to enhance their service offerings through targeted partnerships that deliver capabilities faster and often more cost-effectively than internal development alone.
The recent collaboration between RBC Investor Services and FundGuard exemplifies how strategic partnerships can accelerate capability deployment in highly specialised areas.
The initiative introduces a next-generation derivatives platform designed to provide clients with enhanced processing capabilities, robust reporting tools, and flexible data access — addressing a critical need in an area where derivatives complexity continues to escalate.
The platform offers advanced capabilities for derivatives processing alongside streamlined access to key data, enabling clients to efficiently and flexibly manage their derivatives exposure.
The partnership reflects a broader industry recognition that specialised vendors like FundGuard, with focused expertise in investment accounting and derivatives processing, can often deliver capabilities more rapidly than traditional build approaches.
Instead of simply adding more personnel, firms are now looking to implement better processes and leverage specialised vendors. For example, partnering with companies like Equilend for asset lending allows RBC Investor Services to benefit from their expertise and thought leadership.
This approach improves transparency and operational flows, ultimately enhancing the overall asset servicing experience.
The strategic value of such partnerships extends beyond mere speed to market:
Reduced development costs: By collaborating with best-of-breed providers, asset servicers can access deep domain expertise and technology stacks that would require significant time and investment to replicate internally. This approach allows organisations to focus on their core competencies while leveraging external innovation.
Leveraging continuous innovation: Partnerships with technology-forward vendors enable asset servicers to benefit from continuous innovation cycles without bearing the full burden of research and development costs. As fintech providers enhance their platforms, partners gain access to evolving capabilities that reflect emerging client demands.
Derisking new technology adoption: Rather than committing to long-term internal developments that could become obsolete before completion, organisations can leverage partnerships to test new capabilities and validate client demand — all while maintaining the option to bring capabilities in-house if strategic considerations change over time.
Enhancing proprietary solutions
While partnerships provide access to specialised external capabilities, successful asset servicers recognise that certain elements of their service offering require proprietary development to deliver unique value and maintain competitive differentiation. Strategic internal development allows organisations to create highly customised solutions that align precisely with their specific client base, operational model, and strategic positioning — areas where off-the-shelf solutions may fall short.
For example, RBC Investor Services’ approach to ETF servicing demonstrates how targeted proprietary development can enhance operational excellence and client outcomes.
They have invested significantly in system improvements designed to strengthen its automated controls framework, resulting in decreased processing time while maintaining the accuracy standards.
The decision to develop capabilities internally stems from several strategic considerations. Regular technology upgrades enable organisations to streamline processes with reduced outsourcing, maintaining tighter control over service quality and operational resilience. For high-volume, mission-critical operations like ETF servicing, this level of control proves essential in delivering consistent client experiences and managing operational risk.
Proprietary developments include automated functionality for portfolio composition file (PCF) and trades burst file creation — critical elements of ETF processing that directly impact speed and accuracy. By developing these capabilities internally, we can tailor the automation precisely to its operational workflows and client requirements while maintaining the flexibility to adapt rapidly as market practices evolve.
But this commitment to internal development does not operate in isolation. The integration of Bloomberg Basket — a market-leading tool — into the ETF ecosystem demonstrates how proprietary development and strategic partnerships can work together. While Bloomberg provides specialised market data and basket trading capabilities, internal developments enhance how that data flows through operational processes and surfaces to clients.
Internal developments like these present several benefits:
Client service excellence: Cross-organisational relationship-building ensures that every level of the organisation — from senior leadership to operations staff — prioritises client engagement. This commitment manifests through proactive action on client feedback, rapidly implementing system upgrades and service enhancements tailored to evolving ETF demands.
Flexible configuration: Adaptable processes enable reporting solutions that align precisely with client requirements — capabilities that would be difficult to achieve through standardised external platforms. This is especially true for first-time ETF issuers, where dedicated launch support provides critical guidance and resources, easing market entry through services refined through internal development and operational expertise.
At the operational core lies a ringfenced ETF operations team based in Toronto, delivering end-to-end servicing with low attrition, deep expertise and extended shift coverage to ensure uninterrupted client-facing support. When paired with strategic technology advancements such as automated controls and insourced processing, this model elevates service reliability and responsiveness, setting a new industry benchmark for ETF administration.
AI: The intelligence layer
While partnerships provide specialised capabilities and internal development delivers customised solutions, AI represents a third element of modern asset servicing innovation — serving as an intelligence layer that improves data quality and enables proactive risk management across the entire operational spectrum.
For RBC, this is not a new frontier — the broader enterprise has been investing in AI long before it became an industry buzzword, most notably through Borealis AI, a dedicated research institute established in 2016. This sustained commitment is reflected in RBC’s number-three global ranking in the 2025 Evident AI Index for AI maturity, underscoring a strong foundation of governance, security and investment.
As part of the broader RBC enterprise, RBC Investor Services accrues the benefits of this massive scale, leveraging billions of dollars in enterprise technology.
To operationalise this potential, RBC Investor Services is establishing a delivery team model that provides the necessary foundation — infrastructure, culture and talent — to deliver AI solutions that sit between client self-servicing and business operations. In the immediate term, the focus is on developing specific AI use cases.
One such use case is helping RBC Investor Services solve a fundamental industry challenge: the friction of data ingestion. Historically, custodians have been stuck managing multiple channels of client data, requiring manual capture and processing. AI capabilities can flip this dynamic by delivering immediate benefits — such as automated data aggregation, narrative generation and streamlined processing — that translate directly into client value.
There is no need for clients to adhere to rigid templates or change their behaviours. Instead, intelligent systems ingest data in the formats clients already use, understanding intent and validating completeness instantly.
But as foundational as data management is to operating models, it is a common challenge for many asset managers and owners. A successful data management function today requires a robust governance model that ensures data is safe, accurate and trusted by clients. From data access and architecture to accountability and ownership, RBC Investor Services’ recent ‘Getting Data Right’ whitepaper lays out what’s holding asset owners and managers back from delivering value through data and what forward-looking leaders are doing to move ahead.
But while AI has many uses, it is important not to rely solely on it. The integration of AI into asset servicing operations requires careful orchestration, balancing the technology’s disruptive potential against the continued importance of human expertise and oversight.
Successful implementation depends on strong foundational elements: robust data governance frameworks and modernised infrastructure capable of supporting advanced analytics.
Successful AI integration requires addressing multiple dimensions simultaneously — from governance frameworks to regulatory compliance to client experience design.
Asset servicers must navigate the delicate balance between leveraging AI’s capabilities and maintaining the human judgment that remains essential in complex, high-stakes financial operations.
As we continue to build out these capabilities, we are committed to understanding our clients’ current operational workflows and identifying exactly where they are experiencing friction, ensuring that our AI roadmap solves real operational bottlenecks rather than just deploying technology for its own sake.
The integrated approach
No single innovation pathway suffices in addressing the full spectrum of client needs and competitive challenges. As the asset servicing industry navigates mounting transaction volumes, evolving regulatory requirements, and rising client expectations, the organisations that thrive will be those that master the orchestration of multiple innovation pathways.
The future belongs to those that build integrated operating models capable of leveraging the best of partnership innovation, proprietary development and AI in service of superior client outcomes.
Instead, the most successful firms are those that leverage the latest and greatest solutions wherever they may find them — either through best-in-breed partnerships, proprietary platform enhancements, or leveraging artificial intelligence to enhance every aspect of their operating model.
This integrated approach represents a fundamental shift from the traditional binary decision-making on whether to build or buy that has dominated asset servicing strategy discussions.
Rather than choosing between developing capabilities in-house or outsourcing to specialised vendors, organisations are recognising that sustainable competitive advantage requires a continuous review of client needs and solutions development with a focus on finding the right technology — sourced externally, built in-house or developed using large language models and emerging AI capabilities.
As transaction volumes surge and regulatory requirements grow more complex, asset servicers face mounting pressure to deliver faster, more accurate service.
Meeting these challenges requires an operating model that leverages external innovation while maintaining the flexibility and control of proprietary solutions and AI.
Partnership as innovation
In a market characterised by rapid technological evolution and increasingly specialised client needs, sophisticated asset servicers recognise that building every capability in-house is neither practical nor strategically optimal.
The emergence of fintech providers with deep expertise in specific domains has created opportunities for established institutions to enhance their service offerings through targeted partnerships that deliver capabilities faster and often more cost-effectively than internal development alone.
The recent collaboration between RBC Investor Services and FundGuard exemplifies how strategic partnerships can accelerate capability deployment in highly specialised areas.
The initiative introduces a next-generation derivatives platform designed to provide clients with enhanced processing capabilities, robust reporting tools, and flexible data access — addressing a critical need in an area where derivatives complexity continues to escalate.
The platform offers advanced capabilities for derivatives processing alongside streamlined access to key data, enabling clients to efficiently and flexibly manage their derivatives exposure.
The partnership reflects a broader industry recognition that specialised vendors like FundGuard, with focused expertise in investment accounting and derivatives processing, can often deliver capabilities more rapidly than traditional build approaches.
Instead of simply adding more personnel, firms are now looking to implement better processes and leverage specialised vendors. For example, partnering with companies like Equilend for asset lending allows RBC Investor Services to benefit from their expertise and thought leadership.
This approach improves transparency and operational flows, ultimately enhancing the overall asset servicing experience.
The strategic value of such partnerships extends beyond mere speed to market:
Reduced development costs: By collaborating with best-of-breed providers, asset servicers can access deep domain expertise and technology stacks that would require significant time and investment to replicate internally. This approach allows organisations to focus on their core competencies while leveraging external innovation.
Leveraging continuous innovation: Partnerships with technology-forward vendors enable asset servicers to benefit from continuous innovation cycles without bearing the full burden of research and development costs. As fintech providers enhance their platforms, partners gain access to evolving capabilities that reflect emerging client demands.
Derisking new technology adoption: Rather than committing to long-term internal developments that could become obsolete before completion, organisations can leverage partnerships to test new capabilities and validate client demand — all while maintaining the option to bring capabilities in-house if strategic considerations change over time.
Enhancing proprietary solutions
While partnerships provide access to specialised external capabilities, successful asset servicers recognise that certain elements of their service offering require proprietary development to deliver unique value and maintain competitive differentiation. Strategic internal development allows organisations to create highly customised solutions that align precisely with their specific client base, operational model, and strategic positioning — areas where off-the-shelf solutions may fall short.
For example, RBC Investor Services’ approach to ETF servicing demonstrates how targeted proprietary development can enhance operational excellence and client outcomes.
They have invested significantly in system improvements designed to strengthen its automated controls framework, resulting in decreased processing time while maintaining the accuracy standards.
The decision to develop capabilities internally stems from several strategic considerations. Regular technology upgrades enable organisations to streamline processes with reduced outsourcing, maintaining tighter control over service quality and operational resilience. For high-volume, mission-critical operations like ETF servicing, this level of control proves essential in delivering consistent client experiences and managing operational risk.
Proprietary developments include automated functionality for portfolio composition file (PCF) and trades burst file creation — critical elements of ETF processing that directly impact speed and accuracy. By developing these capabilities internally, we can tailor the automation precisely to its operational workflows and client requirements while maintaining the flexibility to adapt rapidly as market practices evolve.
But this commitment to internal development does not operate in isolation. The integration of Bloomberg Basket — a market-leading tool — into the ETF ecosystem demonstrates how proprietary development and strategic partnerships can work together. While Bloomberg provides specialised market data and basket trading capabilities, internal developments enhance how that data flows through operational processes and surfaces to clients.
Internal developments like these present several benefits:
Client service excellence: Cross-organisational relationship-building ensures that every level of the organisation — from senior leadership to operations staff — prioritises client engagement. This commitment manifests through proactive action on client feedback, rapidly implementing system upgrades and service enhancements tailored to evolving ETF demands.
Flexible configuration: Adaptable processes enable reporting solutions that align precisely with client requirements — capabilities that would be difficult to achieve through standardised external platforms. This is especially true for first-time ETF issuers, where dedicated launch support provides critical guidance and resources, easing market entry through services refined through internal development and operational expertise.
At the operational core lies a ringfenced ETF operations team based in Toronto, delivering end-to-end servicing with low attrition, deep expertise and extended shift coverage to ensure uninterrupted client-facing support. When paired with strategic technology advancements such as automated controls and insourced processing, this model elevates service reliability and responsiveness, setting a new industry benchmark for ETF administration.
AI: The intelligence layer
While partnerships provide specialised capabilities and internal development delivers customised solutions, AI represents a third element of modern asset servicing innovation — serving as an intelligence layer that improves data quality and enables proactive risk management across the entire operational spectrum.
For RBC, this is not a new frontier — the broader enterprise has been investing in AI long before it became an industry buzzword, most notably through Borealis AI, a dedicated research institute established in 2016. This sustained commitment is reflected in RBC’s number-three global ranking in the 2025 Evident AI Index for AI maturity, underscoring a strong foundation of governance, security and investment.
As part of the broader RBC enterprise, RBC Investor Services accrues the benefits of this massive scale, leveraging billions of dollars in enterprise technology.
To operationalise this potential, RBC Investor Services is establishing a delivery team model that provides the necessary foundation — infrastructure, culture and talent — to deliver AI solutions that sit between client self-servicing and business operations. In the immediate term, the focus is on developing specific AI use cases.
One such use case is helping RBC Investor Services solve a fundamental industry challenge: the friction of data ingestion. Historically, custodians have been stuck managing multiple channels of client data, requiring manual capture and processing. AI capabilities can flip this dynamic by delivering immediate benefits — such as automated data aggregation, narrative generation and streamlined processing — that translate directly into client value.
There is no need for clients to adhere to rigid templates or change their behaviours. Instead, intelligent systems ingest data in the formats clients already use, understanding intent and validating completeness instantly.
But as foundational as data management is to operating models, it is a common challenge for many asset managers and owners. A successful data management function today requires a robust governance model that ensures data is safe, accurate and trusted by clients. From data access and architecture to accountability and ownership, RBC Investor Services’ recent ‘Getting Data Right’ whitepaper lays out what’s holding asset owners and managers back from delivering value through data and what forward-looking leaders are doing to move ahead.
But while AI has many uses, it is important not to rely solely on it. The integration of AI into asset servicing operations requires careful orchestration, balancing the technology’s disruptive potential against the continued importance of human expertise and oversight.
Successful implementation depends on strong foundational elements: robust data governance frameworks and modernised infrastructure capable of supporting advanced analytics.
Successful AI integration requires addressing multiple dimensions simultaneously — from governance frameworks to regulatory compliance to client experience design.
Asset servicers must navigate the delicate balance between leveraging AI’s capabilities and maintaining the human judgment that remains essential in complex, high-stakes financial operations.
As we continue to build out these capabilities, we are committed to understanding our clients’ current operational workflows and identifying exactly where they are experiencing friction, ensuring that our AI roadmap solves real operational bottlenecks rather than just deploying technology for its own sake.
The integrated approach
No single innovation pathway suffices in addressing the full spectrum of client needs and competitive challenges. As the asset servicing industry navigates mounting transaction volumes, evolving regulatory requirements, and rising client expectations, the organisations that thrive will be those that master the orchestration of multiple innovation pathways.
The future belongs to those that build integrated operating models capable of leveraging the best of partnership innovation, proprietary development and AI in service of superior client outcomes.
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