This article draws on interviews carried out for WealthBriefing”s forthcoming AI in Wealth Management research report, due for publication later this year.
For boutique wealth managers, the immediate opportunity of
artificial intelligence lies in reducing administrative work
and creating more capacity for client service. This article is
part of conversations in a research report this news organisation
is producing in partnership with Arta Finance. Arta
Finance is an AI-driven wealth and fintech firm headquartered in
Silicon Valley and Singapore. Its rapid ascent reflects how
technology is reshaping the wealth management sector
worldwide.
The success of AI in wealth management may depend less on which
tools firms buy than on how well they prepare their businesses to
use them.
That is the view of Kevin Andrews (main picture), chief operating
officer at Bentley
Reid, who has contributed to WealthBriefing’s
forthcoming AI
in Wealth Management research report. His responses
highlight a shift from exploring the technology’s capabilities to
establishing how it can deliver practical value within a
regulated business.
“12 months ago, we were largely exploring what AI could do.
Currently we are focused more on how it can be used safely and
practically within the business,” Andrews said.
Bentley Reid has introduced an AI policy and governance
on its use, with staff using tools such as Copilot for
research, summarization, drafting and everyday productivity
tasks. The firm does not allow AI to make investment decisions or
generate client advice.
For Andrews, the most significant change has been moving the
discussion towards the business processes and data that support
the technology.
Creating capacity for client service
Asked where AI could make the biggest difference to the economics
of wealth management, Andrews points to productivity.
Relationship managers spend considerable time preparing for
meetings, writing reports, documenting conversations and finding
information. Reducing that workload could give them more time for
activities that benefit clients.
“As a boutique wealth manager, we remain a people business. The
real opportunity for us is helping our staff serve clients more
effectively and consistently, while creating additional capacity
as the business grows.”
However, demonstrating a promising use case is only the first
step. Turning it into something reliable, controlled and
supported within daily operations requires a stronger business
case.
“It’s largely about proving that the value is real and
repeatable,” Andrews said.
A useful test is whether staff are still using a tool six months
after its introduction because it continues to make their jobs
easier.
Adoption depends on everyday usefulness
Some of the most effective applications Bentley Reid has found so
far are straightforward: summarizing information, preparing first
drafts, extracting meeting actions and helping structure
documents.
“They aren’t particularly glamorous, but they save time and solve
real problems,” Andrews said.
Training helps staff understand both the capabilities and
limitations of AI. But adoption ultimately depends on a tangible
benefit. A tool that saves time has a clearer route into everyday
use than one that adds another login or process.
Data presents another challenge. Bentley Reid has a mixture of
established and newer systems, with information held across
different platforms. Making that information structured,
accessible and understood is a priority alongside identifying
practical applications.
Human accountability remains central
Bentley Reid’s measured approach also reflects the need to
balance opportunities with appropriate controls.
“Our starting point is that responsibility remains with the
individual, not the AI,” Andrews said.
Generative AI can produce convincing answers that are incorrect.
At Bentley Reid, someone therefore remains accountable for
reviewing and approving the final output, with that principle
reinforced through policy and training.
Looking ahead, Andrews expects the strongest adopters to be firms
that establish the right foundations and integrate AI effectively
into their operating models. Poorly understood data and
inconsistent processes risk being amplified by the technology.
His perspective offers a practical question for the wider
industry: can an AI initiative deliver a lasting improvement in
how people work?
This article draws on an interview conducted for
WealthBriefing’s AI in Wealth
Management research report, due for publication later this
year. Private banking and wealth management professionals are
invited to contribute their views through the accompanying
survey.
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