Despite being in the data age, many wealth management firms are yet to realise the full potential of their data.
An EY study in 2025 polled Chief Data Officers, Chief Technology Officers, IT Directors and Chief Operating Officers across wealth and asset management firms. Of the respondents, 74% believed their data was improving, but 79% believed poor data quality remained a pain point, with 45% noting an immature data culture a challenge.
As seen by the EY study, improving data quality has been on the agenda for wealth management firms. However, it is not a simple and quick fix that can solve the entire problem. Often priorities are placed and other areas are left a little behind. What are the internal data sets that are the most underutilised?
For Jurgen Vandenbroucke, PhD, managing director at everyoneINVESTED, behavioural interaction data are the most underused. This includes data collected from mobile and web journeys, such as choice patterns, time-to-decide, abandonment points and framing sensitivity. This information is vital at showing how clients think beyond static KYC fields. He added, “In recent deployments everyoneINVESTED implemented playful screenflows that produced high quality behavioral signals on the sensitivity to risk, loss, and information framing, with strong completion and click through performance. If underpinned by a sound methodology, such data may in addition pre-fill regulatory requirements and power personal defaults—shown to boost conversion in digital journeys.”
A similar opinion was held by Fredrik Davéus, CEO and co-founder of Kidbrooke, believing that many firms are not leveraging their customer-focused data. Davéus stated that client interaction data, including meeting notes, suitability assessments, portfolio rationales, emails, call transcripts and advisor commentary, were underutilised within wealth management.
He said, “This is incredibly rich information, but historically it’s been treated as unstructured “compliance exhaust” rather than a strategic asset. The challenge hasn’t been a lack of data, but a lack of contextual intelligence. Much of this information lives in silos (CRM systems, document repositories, adviser desktops), and isn’t standardised or connected to market data, product data, or outcomes. As a result, firms struggle to analyse it at scale.”
However, the landscape is changing and firms might be able to solve part of the challenge. Davéus noted that advanced analytics and natural language processing are giving firms the ability to structure and interpret unstructured data. He added, “When you can connect what advisors say, what clients ask, and what actually happens in portfolios, that data becomes actionable. Until recently, the technology simply wasn’t mature enough but now it is.”
Given the importance of personalisation in modern wealth management, it is vital for firms to improve how they use customer data. For instance, 66% of high net worth investors desire increased personalisation in their wealth management relationship, according to data from PwC, and 56% of investors are willing to pay more for a personalised service, an EY report found.
Despite this, firms are still struggling. Fincite founder & co-CEO Friedhelm A. Schmitt noted that wealth firms are sitting on this powerful data for personalisation, whether it is psychographic insights, context from advisor conversations, life events, notes, behaviour patterns, and more. They are just locked behind PDFs, emails and CRM notes. As such, many just take the easy route and leverage the data most readily available: holdings, transactions, market data and more.
As a result, they, “ignore the data that actually differentiates the client relationship,” he said. “The competitive advantage won’t come from more data, but from turning unstructured client intelligence into something the advisor can use at the moment of decision.”
This all comes back to the notion of poor data hygiene. Schmitt explained, “When I speak with Bank CIOs, the problems are shockingly fundamental: different date formats, inconsistent thousand separators, duplicated datasets with different update cycles, and systems that simply don’t talk to each other. If data isn’t consistent, accessible, or explainable, it cannot become a strategic asset.”
One of the reasons customer data has been left behind during digitalisation strategies could be down to firms not realising the true opportunity they offer. Hari Menon, Global Delivery & Business Head for Wealth, Capital Markets, and AI, at IntellectAI, explained, “Wealth management firms often overlook valuable data generated through daily operations, such as advisor rationale, client interactions, exception handling, and operational decisions, which capture critical intent and judgment. This information, like a client’s casually mentioned future need during a discovery meeting, is rarely structured for reuse or captured in formal client records.”
Often, this data is captured for audit or record-keeping purposes and not for large-scale integration and use, Menon added. “As long as data primarily serves to explain outcomes retroactively rather than to inform real-time decisions, its strategic impact will remain constrained.”
A solution to this is to build an ‘enterprise customer knowledge garden’, Menon said. This would offer a holistic, 360-degree view that integrates all structured and unstructured customer data. As an example, the system would push an advisor to call a client to check whether an issue with the app or portal from the previous day was resolved. By fostering a proactive service, firms can transform into an effective soft sales channel that deepens customer retention and paves the way for additional business, Menon explained.
Making the most out of data
Looking to the future, the firms that will see the most success will be those that leverage their customer data. Menon noted that growth will be tied to embedding data intelligence directly into the advisory process. “This will enable more adaptive portfolios, continuous suitability checks, and clearer client outcomes. The success of these models, however, fundamentally relies on the reliability of the underlying data. Crucially, the immense value of tacit knowledge is often overlooked; unlocking the full potential of data will occur when organisations begin to effectively capture and utilise this knowledge.”
Echoing this, Schmitt highlighted that success in the future will come from a three-level approach. At the foundation of this is personalisation and ensuring client insights are used to deliver more relevant advice, which improves advice and makes the client feel understood. This boosts engagement, retention and share-of-wallet, he noted. “This creates a flywheel: more relevance leads to more interaction leads to more data leads to even better relevance.”
Second is the advisor enablement. By improving data quality and access, advisors can have better conversations with greater context, more timely touchpoints and a stronger creditability signal. “This directly drives revenue because it increases both the quantity and quality of client interactions.”
The final layer is lead generation. He noted that wealth is a displacement market, where data can reveal churn signals, family and business relationships or life events that indicate switching potential.
Schmitt added, “In short: Today, data reduces cost. In the future, data will drive revenue, through personalization, advisor intelligence and smarter acquisition. The winners will be the firms that turn data into a self-reinforcing flywheel.”
Damage done
While ineffective use of data will create widespread challenges for firms, there are some areas where it will be particularly devastating. For Davéus the biggest damage will be to the long-term client retention. What makes this notably troublesome is that it is not always immediately visible.
He said, “Investment teams often have controls and benchmarks to catch data issues. Risk teams are naturally conservative and assume imperfect data. But when advisors don’t fully trust the data in front of them, or when insights are inconsistent across channels, the quality of client conversations suffers.”
Consequently, clients are provided with generic advice, rather than personalised guidance that adapts to changing client needs. Clients will begin to acknowledge there is a trouble with their wealth advisor, while they might not see it as a data problem, they will start to feel their advisor lacks the ability to provide them with relevant or timely support and seek a new provider, he explained.
“In wealth management, trust is built on data you can rely on. In WealthTech, data quality is becoming a strategic weapon and the firms that treat it that way will define the next decade of wealth management.”
As noted, firms are not unable to collect customer data, their legacy infrastructure just limits their ability to access it. This is a ticking time bomb for firms, according to Menon. Initially, poor data quality impacts operations and risk management, creating more controls, manual reviews and buffers. This impedes client experiences and hinders the effectiveness of investment decisions.
Menon said, “Supervisory findings underscore this problem. For instance, a recent FCA review on prudential regulatory reporting data quality found that approximately 40% of firms failed to pass all data quality tests, indicating a significant ongoing issue, as only around 60% of firms passed all tests.
“When data lacks trustworthiness, decision-making slows, and accountability diminishes. The difficulty lies in the fact that these data issues rarely cause a sudden, catastrophic failure; instead, they fail slowly, accumulating across various decisions.” While gradual, it eventually grows and reaches the client as “pervasive inconsistency.” The most damaging consequence would be done to the reputation of the firm, whether it is with investments, risk management, or compliance, leading to client retention challenges.
Schmitt also pointed to the client trust being the biggest casualty of poor data quality. “Clients can live with outdated data for a moment; what they cannot tolerate are duplicates with different values, inconsistent performance figures, missing information, or errors that cannot be corrected despite repeated requests. These moments erode confidence faster than any market event. Once a client doubts the integrity of their data, they begin to doubt the advice, the process and ultimately the institution.
“That’s why firms must treat data quality as a front-office topic, not a back-office chore. Managing duplicates, updates, corrections and lineage is not operational housekeeping, it is a core trust function. In wealth management, data quality is client loyalty.”
Vandenbroucke highlighted four areas where poor data has the most vulnerabilities. The first is client retention, where a lack of preference and framing can lead to the right product being delivered the wrong way and causing customer churn. Second is operational efficiency, such as collecting data by re-asking questions asked previously and causing increased handle time and abandonment.
The third vulnerability is risk management and suitability, where missing behavioural inputs undermine the quality of compliance with investor protection regulation or product-fit assessments and risk losing customer trust. Finally, investment strategy personalisation is a potential casualty, with a lack of portfolio glidepaths and nudges can result in client’s underperforming.
On a concluding note, Vandenbroucke said, “Wealth firms already own the most differentiating data: live, consented behavioral intelligence about how each client weighs risk, loss, and context. When captured through engaging micro‑journeys, persisted into the customer profile, and operationalised via personas and framing‑aware design, these signals translate directly into higher conversion, faster onboarding, better suitability and ultimately superior retention and revenue.”
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