Data up front: Asset management’s underutilized growth engine

Executive summary

While most wealth and asset managers have mastered using data for compliance and operations, they’re missing a massive revenue opportunity: using that same data to deepen investor relationships and accelerate growth. The firms winning new mandates and retaining assets aren’t just collecting better data — they’re putting real-time, actionable insights directly into the hands of their distribution and investor relations (IR) teams at every client touchpoint.

Data’s next stop: The front office

Asset and wealth managers aren’t short on quality data. Where nearly one-third of Grant Thornton’s 2025 Digital Transformation Survey respondents said their organization’s data quality needs work, less than 20% of respondents in the asset management industry agreed.

Today, most of that rich information powers compliance workflows and operational dashboards. Essential, yes — but it’s leaving money on the table.

“Data as a growth asset is table stakes in today’s market. It’s simply a necessity for sustained competitive advantage,” said Karan Gulati, Grant Thornton Business Consulting Principal. The firms gaining an edge are moving from isolated data that remains largely siloed in back-office processes to a model that delivers one trusted view of investors, products and performance.

Confronting evolving investor demands

Millennials and Gen Z are on track to inherit upwards of $100 trillion in the next 10 years. But that wealth transfer isn’t automatic for incumbent managers, said Mark Owens, Grant Thornton Business Consulting Managing Director.

“Young inheritors expect transparency, strategy customization and digital control over their investments,” Owens said. Quarterly PDFs and passive-only portfolios won’t cut it — and these investors won't hesitate to move their assets.

Institutional allocators face similar pressure. Many have their own analytics desks and demand the same digital transparency from external managers.

Meeting these expectations requires distribution and IR teams to have the right information instantly available. But most firms deal with data scattered across departments, making it nearly impossible to get a unified view for client conversations or strategic decisions. “The costs of building integrated data systems can be significant, but doing nothing is riskier,” Owens said. “When you model out declining revenue streams and shrinking investor retention, you realize scattered data could cost you catastrophic AUM losses. Suddenly, the investment math looks very different.”

So how do firms bridge this gap without the massive IT budgets and in-house expertise of larger managers? Three strategic moves can turn your existing data into a competitive advantage.

Three ways to turn data into a growth engine

1. Build a single, trusted environment — then actually use it

Forming mixed teams — IT, data science, sales, marketing, compliance — for data initiatives can help signal to teams that data strategy is a companywide priority. The firms that are succeeding are those that place revenue growth at the center of their strategy, then build their data needs and operational workflows around that goal.

2. Apply AI where it drives revenue

Many asset managers approach AI as an operational efficiency play — automating compliance, streamlining reporting and reducing manual processes. While these applications deliver value, they miss the larger revenue opportunity: deploying AI to make distribution and investor relations teams fundamentally more effective.

The strategic shift involves using predictive capabilities to identify prospects showing behavioral signals of readiness to allocate, detecting early client retention risks and optimizing engagement timing based on data patterns rather than sales cycles.

“When identifying the right AI tools, it’s best to choose those that you can layer on top of your existing data to give you capabilities that you didn’t have before,” Whatton said.

Asset management-specific solutions such as Chronograph, iLevel and Cobalt for portfolio analytics can layer onto existing tech stacks. But when selecting a tool, Whatton emphasized, “Tools should always drive back toward strategic objectives — being able to measure results and how you’re meaningfully changing outcomes with these tools versus just throwing money at things that you think might help.”

The evaluation should focus on specific business questions: Can the AI capability identify prospects earlier in their decision process? Does it reduce time-to-close on new mandates? Are retention conversations happening proactively rather than reactively?

“The real value of AI lies in delivering measurable business outcomes — not just new features,” O’Hea said. “The right solutions should accelerate prospect identification, shorten sales cycles and enable proactive client retention.”

3. Personalize the investor experience at scale

Distribution teams that leverage behavioral data and portfolio intelligence can deliver the level of personalization today’s investors demand. This means moving beyond regular reporting to what Gulati calls “relentless digital engagement” — text-based alerts on portfolio performance, mobile search features for investment recommendations without requiring portal logins and real-time access to alternative investment opportunities based on individual risk profiles.

“Investors want to be involved more because there are so many tools for them to use independently in the market,” Whatton said. “You’ve got to have a differentiator — your technology platform has to provide something truly different.”

CRM data and portfolio intelligence enable asset managers to deliver those differentiated experiences and strategic, one-to-one conversations, which fuel opportunities with younger investors. “It’s about being more thoughtful and proactive in addressing second- and third-generation family members,” Owens said. “Help younger investors understand traditional and alternative investments. Plan and manage liquidity for life events like college debt and first home purchases. It can include financial wellness education and training delivered through digital channels on demand,” Owens said. “When you build depth in the relationship, you have a much greater likelihood of retaining those assets.”

Measuring these experiences focuses on revenue uplift against the fixed costs required to enable personalization capabilities, tracked through metrics such as net promoter scores by client segment, cross-sell volume and message engagement rates.

Where to focus now

Start with existing infrastructure

Firms don’t need to rip and replace legacy systems to begin using data in ways that give investors the personalization, speed and clarity they expect. This shift is possible even within a firm's existing tech stack.

“Most firms don’t need to overhaul their entire tech stack,” O’Hea said. “The real opportunity lies in optimizing what’s already there — leveraging existing cloud platforms like Azure, AWS or Oracle to unlock advanced analytics AI and scalable data management. This approach keeps costs variable, aligns technology spend with growth and delivers true agility.”

Rather than wholesale system replacement, asset managers can harness their current cloud infrastructure’s full suite of services — from data warehousing and networking to AI-driven analytics. This creates flexible, modular data environments that scale with demand, allowing firms to deploy new analytics, reporting or personalization features as needed while paying only for what they use.

The result is a variable cost model that directly links technology investment to business outcomes and supports mass customization without large upfront capital expenditure. Asset managers who adopt this approach can respond faster to client needs and maintain a lean, future-ready operating model.

Move toward front-line investment

Begin conversations that reallocate resources and attention toward data initiatives in the front and middle office. This requires addressing both workforce and technical challenges.

“Team members often lack the skills to interpret and leverage data analytics effectively, limiting the actionability of available data,” Gulati said. “Investor-facing teams are stretched thin, juggling multiple responsibilities, which limits their ability to focus on data-driven projects.”

Additionally, a lack of coordination between teams — IR, distribution, ESG, compliance — leads to inefficiencies and missed opportunities. A culture of competition, secrecy or reliance on traditional methods can discourage adoption of new data-driven approaches.

For the front office, O’Hea stressed the importance of aligning sales targets with firm-wide objectives: “It’s extremely important that the strategic goals of the company are aligned with the tactical goals of the sales teams, and those metrics can be pulled from finance or CRM. The operating model is the key part — you need to get the plumbing right.”

When goals cascade this way, salespeople aren’t just chasing quotas; they’re contributing to revenue that aligns with the organization’s overall strategy.

“It’s important that strategic goals filter down to individual performance,” O’Hea said. "This cascading of objectives stops salespeople from just delivering numbers and focuses them on meeting strategic goals that deliver long-term organizational objectives.”

Ultimately, meaningful change only happens when business objectives are clear and both firm and technology leaders are jointly accountable for results. Success is defined by shared ownership and a unified vision of what progress looks like.