The Problem with Siloed Investment Products
Most financial institutions offer both robo advisory services and self-directed investing platforms. Few offer them as part of the same experience.
This matters more than it might appear. Clients who open a robo advisory account often build confidence over time and eventually want to make a direct investment in a specific stock or ETF. If the platform cannot accommodate this, they open a separate self-directed account elsewhere, often with a competitor.
The architecture that created this problem was not designed with malice. Robo advisory and self-directed investing evolved as separate products, built by separate teams, on separate technology stacks. But from the client's perspective, both are simply "investing". The institutional distinction feels arbitrary.
What Integration Actually Looks Like
We believe financial institutions should design investing experiences where clients are able to move between guided and autonomous approaches without friction, not because flexibility is fashionable, but because it reflects how people actually behave.
In practice, this means a client might allocate monthly contributions through a Robo Advisor while also holding a small position in a company they believe in. Both appear in the same portfolio view. Both draw on the same risk profile and financial context. The client does not need to learn two interfaces or reconcile two sets of performance data.
This is not about offering more products. It is about designing experiences that adapt to clients over time, supporting different levels of engagement without adding complexity.
The technical challenge is real: connecting execution venues, harmonizing data models, presenting coherent portfolio analytics across different instrument types. But the strategic question is more fundamental: does your digital wealth experience treat investing as a destination clients visit, or as a capability woven into their financial life?
Investing at Financial Moments
The most effective investing experiences we have helped build share a common characteristic: they meet clients in moments that already exist.
Surplus cash is the clearest example. When a salary payment, bonus, or annual payout increases a client's available balance, the institution already knows this. A well-designed experience can surface relevant options, whether that means topping up an existing Robo Advisor portfolio or highlighting a Self Investor opportunity, without requiring the client to navigate to a separate investing section.
This approach draws on behavioral research into "fresh start" effects. Dai, Milkman, and Riis demonstrated in their 2014 study that people are more likely to take action on aspirational goals at temporal landmarks, moments that feel like new beginnings. A salary payment is precisely such a moment. The question is whether your digital experience recognizes it.
We are not suggesting aggressive prompts or pressure tactics. Banks do not succeed by pestering clients. But there is a difference between pressure and presence. When investing options appear in context, with clear explanations and transparent risk information, clients can make informed decisions. When those options are buried three levels deep in a navigation menu, most clients never find them.
The Orchestration Layer
Connecting robo advisory and self-directed investing requires more than API integrations. It requires an orchestration layer that sits above infrastructure and determines how the experience feels to the client.
This is the layer where portfolio data becomes meaningful insight. Where risk metrics translate into language clients understand. Where guidance appears at relevant moments rather than generic intervals. Without this layer, even technically sophisticated platforms feel disjointed.
We designed InvestSuite's architecture around this principle. Self Investor and Robo Advisor are not separate products bolted together, they share a common experience framework that ensures consistency in how information is presented, how risk is communicated, and how performance is visualized.
Our Portfolio Optimizer uses deterministic mathematical optimization based on our iVaR methodology. Traditional robo advisors tend to construct portfolios based on Mean-Variance Optimization, developed by Harry Markowitz in 1952. This methodology requires accurate estimation of expected returns, volatilities and pairwise correlations. Portfolios constructed using this framework are extremely sensitive to regime changes, such as those caused by market crises, when these estimates break down (InvestSuite, "COVID-19 puts robo advisors to the test," 2020).
iVaR takes on a different approach. It captures what investors actually perceive as risk: the frequency, the magnitude, and the duration of losses. We build portfolios with the objective of minimizing drawdowns as well as minimizing the time to recovery.
The results matter. During the COVID-19 market crisis, German website brokervergleich.de compared the real-money performance of 20 B2C robo advisors from May 2019 through March 2020. A traditional 50/50 global equity/bond index lost 3.9% over the period. Yet, the vast majority of robo advisors underperformed it, some by a staggering 14 percentage points. The InvestSuite portfolio, tested with our own capital at a Dutch wealth manager client, returned -0.8%, outperforming all 20 competitors in the study (InvestSuite, "COVID-19 puts robo advisors to the test," 2020).
This shared foundation means clients receive coherent guidance regardless of which investing approach they use at any given moment.
A Note on Embedded Investing
Embedded investing has received considerable attention recently. The concept of integrating investment capabilities into non-financial platforms like retail apps or mobility services is genuinely interesting. But it serves a different need than what most financial institutions require.
Embedded investing is primarily relevant for platforms that want to offer investing as a secondary capability, not as a core service. A retail loyalty program might offer investment options for accumulated points. A gig economy platform might surface investing prompts when workers receive payments. These use cases rely on partnerships with licensed financial providers who handle execution, custody, and regulatory obligations.
For banks, wealth managers, and asset managers, the challenge is different. These institutions already hold the regulatory authorizations and client relationships. They do not need to embed investing. They need to integrate it more thoughtfully into experiences they already control.
We mention this distinction because the terminology has become muddled. "Embedded finance" and "seamless investing" are sometimes used interchangeably, but they describe different architectural and strategic choices. Clarity on which problem you are solving matters before selecting a solution.
Why Experience Quality Is Now the Differentiator
Access to investing is no longer scarce. Any client with a smartphone can open an investment account in minutes. The question financial institutions now face is not whether clients can invest, but whether they will choose to invest with you.
The answer increasingly depends on experience quality. Not aesthetics alone, though design matters, but coherence, context, and clarity. Does your digital wealth experience help clients understand what they own and why? Does it adapt to their evolving confidence and circumstances? Does it make investing feel like a natural part of their financial life rather than a separate, intimidating activity?
These questions have commercial implications. Institutions with fragmented investing experiences see lower engagement, higher dormancy, and eventual attrition as clients consolidate assets elsewhere. Institutions that design integrated journeys, connecting robo advisory and self-directed investing, surfacing opportunities at relevant moments, presenting information with genuine clarity, build relationships that endure.
We believe this is the strategic opportunity in digital wealth today. Not launching another product, but fundamentally rethinking how investing experiences are designed and delivered.
If you are exploring how to connect robo advisory and self-directed investing within your digital ecosystem, or how to surface investing at relevant moments in your client journey, we would be glad to discuss what we have learned from similar projects.
Sources:
Dai, H., Milkman, K. L., & Riis, J. (2014). The Fresh Start Effect: Temporal Landmarks Motivate Aspirational Behavior. Management Science, 60(10), 2563–2582. https://pubsonline.informs.org/doi/abs/10.1287/mnsc.2014.1901
InvestSuite, "COVID-19 puts robo advisors to the test" (2020). Available at: https://assets.investsuite.com/white-papers/covid-19/COVID-19-puts-robo-advisors-to-the-test.pdf
Brokervergleich.de robo advisor real-money test (2019-2020). Referenced in InvestSuite COVID-19 whitepaper.
