Mishandling of Client Assets, Adviser Time Could Gouge Profits

Wealth advisory firms may unintentionally undermine their bottom line as they seek to expand client relationships.

As retirement plan advisers look to deepen client relationships and increase profits, three recently published studies suggested advisers may come up short of that goal.

SEI Investments Co.’s survey of 518 financial advisers with an average client net worth of $2.9 million and survey of 302 investors from ages 50 through 70 with at least $1 million in investable assets found a potential gap between advisers’ intentions and actions. Although 95% of advisers said they actively sought to consolidate client assets and 81% said they offered household portfolio management, 71% of high-net-worth investors reported their adviser had never asked to manage a larger share of their assets.

Want the latest retirement plan adviser news and insights? Sign up for PLANADVISER newsletters.

The research suggested clients may be willing to move additional assets when advisers can clearly quantify the benefits. Among investors surveyed, 46% said tax savings would motivate them to consolidate more assets with a primary adviser, followed by increasing retirement income (42%) and lower fees (38%). Yet only 49% of advisers surveyed said they could quantify the value created by household-level planning strategies across all client accounts, compared with 38% who could not quantify the value and 13% who did not offer such services.

Delivering that type of personalized advice for a household remains labor-intensive. Advisers providing services such as tax-smart withdrawal strategies, asset location and household rebalancing reported spending an average of 48 hours each month on those activities—more than the length of an average work week. Asked about the barriers to scaling such services, 37% of responding advisers claimed a lack of client interest, 30% cited a lack of automating technology, and 22% cited insufficient staffing.

SEI conducted its adviser survey in January and its investor survey in April.

Cost-Effective Protocol

Time management was also highlighted in a white paper by consultancy the Oasis Group, “Why Meeting Management Is a Profitability Problem in Wealth Management.” Quoting a 2025 Cerulli Associates report, the paper stated that advisers spent an average of nine hours each week on administrative tasks. Among those tasks, meeting-related activities such as scheduling, preparation, capturing notes, documenting compliance requirements and following up with clients were said to consume substantial time and create operational bottlenecks.

The Oasis Group paper argued that meeting management should be viewed as an end-to-end business process, rather than a series of disconnected tasks. The report described a three-stage approach to client meetings: booking and scheduling; meeting capture and note-taking; and post-meeting follow-up.

According to the paper, firms frequently rely on individual employees’ memory, informal practices and manual handoffs between these stages, creating inefficiencies and increasing the likelihood that tasks will be missed. The report argued that depending on individuals, rather than established processes, can become an expensive liability when firms must replace employees who have been informally holding core processes together.

To address these challenges, the paper recommended that firms take certain steps before investing in technology to streamline things. Oasis recommended advisory firms first measure the time and costs associated with their current meeting-management workflows, then evaluate where process breakdowns occur. Only after a process has been defined and standardized should firms implement automation or artificial intelligence tools.

The report stressed that technology should support a well-designed workflow, rather than compensate for a broken one, and that firms remain responsible for regulatory recordkeeping and supervision, regardless of whether meeting notes are created manually or with assistance from artificial intelligence.

«