Personalised investing is quickly becoming an essential component of modern investment services, but how can firms find the perfect version?
Gone are the days of the one-size fits all approach to investing. Tech giants, like Netflix and Amazon, have had knock-on effects on the financial services sector. Their simplicity, coupled with the ability to provide customers with personalised recommendations, has led to consumers wanting their financial service providers to act the same.
More people are getting involved with their financial future, leveraging WealthTech tools that allow them to access opportunities that were previously out of reach. Whether they are using simple trading apps to manage a portfolio themselves or through a traditional wealth management firm, consumers want to be treated as an individual. A recent report from Publicis Sapient found that 58% of investors it surveyed want to leverage personalised financial planning.
But the question is, what does the perfect personalised investing service look like?
According to Kidbrooke co-founder Fredrik Davéus, the perfect personalised investing experience should be effortless, relevant and empowering.
He said, “From the client’s perspective, it’s about understanding how each financial decision can be explained and how it optionally can fit into their broader life goals.
“The service should understand relevant parts of the client’s financial context: savings, pensions, mortgages, protection, giving clear, actionable insights in plain language, not rules of thumb or standardised “truths” but real-time calculations based on their exact circumstances. Whether the client interacts through an app, an advisor or a chatbot, they should experience consistent, evidence-based guidance.”
Yohan Lobo, Industry Solutions Manager for Financial Services at M-Files, also shared their opinion on the perfect investing service. He emphasised the importance of being effortless, as well as the need for transparency.
He said, “Every document, statement and piece of advice is relevant, timely, and easy to access. People want to feel like their advisors understand not just their assets, but their goals and life stage.
“M-Files helps make that possible by ensuring advisors always have the right information at their fingertips—securely, contextually, and AI-enriched. That means no delays in answering client questions, no friction in onboarding, and no risk of misalignment. This type of experience helps build trust and loyalty.”
Common mistakes
In principle, establishing personalised investing services sounds easy, just ensure a customer has relevant recommendations. However, there are several hurdles that can trip firms up along the way.
One of the biggest could be mistaking customisation for personalisation, Davéus explained, “Changing a dashboard layout or offering pre-set portfolio templates is not the same as tailoring investment advice to an individual’s actual financial reality.”
True personalisation, he continued, relies on the ability to aggregate and model the entire context of a financial query, including the relevant future outcomes. However, many systems lack this ability due to legacy data infrastructure.
“Unfortunately, many systems today still operate in silos, focusing narrowly on investments without factoring in liabilities, protection, or real-world goals. This means there is a built-in inflexibility in traditional systems not able to support the personalisation that is expected by today’s clients.”
The solution, according to Davéus, is to combine analytics with explainable, regulator-ready technology. Firms should invest in platforms that unify relevant data, apply scenario modelling and present outcomes in an understandable and compliant way.
Another potential mistake that firms make when it comes to personalisation is not getting the underlying infrastructure fixed, making the personalisation service fail to operate at its full potential. Lobo said, “I have heard that firms may equate personalisation with segmentation—age, income, or portfolio size. But true personalisation requires integrating all fragmented data and documents across portfolios, compliance checks, and other interactions.
“Most advisors still spend too much time searching through silos for relevant information which makes interactions reactive rather than proactive. With M-Files, firms can connect the dots across unstructured content helping advisors to tailor recommendations on the spot.”
This leads into some of the barriers that are preventing firms from implementing personalisation. Data silos, legacy systems and fragmented data architectures mean firms cannot always unify client records across various departments. This leaves a fragmented view of the client.
Another barrier expressed by both Lobo and Davéus was the regulatory complexity. They noted that firms fear automation could undermine accountability. However, by ensuring there is effective transparency, firms can ensure recommendations can be trusted and defended under scrutiny, if needed.
One barrier Lobo highlighted was operational inefficiency. “Without AI-driven automation, too much advisor time is lost to admin and document chasing instead of building relationships.”
He continued, “M-Files helps address these barriers by integrating seamlessly with existing systems, ensuring compliance-ready audit trails and automating document-heavy tasks, freeing advisors to focus on value-added conversations.”
One final barrier, which was noted by Davéus was cultural inertia. “Many institutions still treat analytics as a back-office function, rather than a customer-facing enabler of engagement.”
He offered some guidance on how firms can overcome all these barriers. “To overcome these barriers, we need to view analytics as a shared foundation for both digital and human channels, the “engine room” of a scalable, compliant and personalised service.”
A difference between generations
While all generations want to have personalisation, that doesn’t mean their expectations are the same. Firms will need to ensure they are able to provide the right type of service that each client wants, or they risk losing them to a competitor.
Davéus noted, “Generational expectations define how personalisation should be delivered. Younger investors expect immediacy, clarity and digital self-service, while older generations may prefer guided conversations with an advisor. But many older customers also value digital self-service solutions, so you need to be attuned to the nuances here.”
Lobo echoed a similar sentiment. He noted that millennials and Gen Z prefer a digital-first, self-service and real-time insights approach. While older generations still prioritise trusted relationships and tailored advice that isn’t compromised through technology.
The challenge with supporting such different expectations is that the underlying analytics need to be identical. Davéus said, “That’s the power of an omnichannel approach: firms can offer multiple interaction styles while ensuring that every recommendation stems from the same analytical core. This consistency builds trust and bridges generations, rather than dividing them.”
The solution is to find the right partner. For instance, M-Files offers AI-powered search and contextual insights that can support both the investor and the advisor managing a portfolio.
Firms are embedding technology across more workflows and innovation is transforming capabilities rapidly. Many wealth management firms are still in the early stages of building personalised services and what they have today will look very different to what they have in five years’ time. Looking ahead, both Lobo and Davéus offered their opinions on the future of personalisation.
Lobo stated, “The future of personalised investing will be shaped by how well firms manage information, not just assets. Personalisation thrives on context, and context comes from unifying documents, data, and communications into a single, intelligent layer.
“M-Files envisions a world where wealth managers use AI not just to analyse portfolios but to ensure every client touchpoint—every document, every conversation—is relevant, compliant, and deeply personal.”
Similarly, Davéus concluded, “Personalisation is fast becoming a regulatory expectation under frameworks like Consumer Duty. To deliver it effectively, financial institutions must rethink their infrastructure. You can’t simply add an AI layer on top of existing tools, but you have to embed explainable analytics and personal relevance into the very architecture of advice and product design.
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