Wealth managers embrace AI, machine learning faster than other financial services firms

August 6, 2022 6:04 PM

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As advisors continue to show excitement for the potential of artificial intelligence, the financial services industry is focused on how to make the most of the burgeoning technology in the years to come.

"The Future of the Data-Driven Workplace," a new research report from Financial Planning parent company Arizent, provides insight into how business leaders are leveraging AI and machine learning to facilitate growth and efficiency.

The study polled 386 management-level respondents across the wealth management, banking, mortgage and insurance sectors. Survey participants ranged from managers to C-level executives with 61% describing themselves as a department or division head, vice president or higher.

Once viewed as a novel business tool, the study finds that AI's impact on data-driven decision making across every financial services industry is now undeniable. From simple functions like scheduling and planning, to complex tasks like underwriting and fraud detection, AI and machine learning are a part of the equation.

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Nearly 90% of leaders at financial services firms believe their companies are taking the necessary steps in data access, management and integration efforts to stay competitive in their respective industries. But even with that high confidence, just 51% of those surveyed say their companies are actively implementing AI and machine learning tools beyond planning and investigative phases.

"The tools have allowed some firms to jump ahead of their competitors, utilizing hardware and software to improve efficiency, reduce costs, manage risk and in a more stark realization, eliminate the need for once-vital personnel," the report says.

The emergence of AI and analytics in data-driven decision making is not without controversy. The use of AI in lending decisions is in the crosshairs of federal agencies like the Consumer Financial Protection Bureau, which says algorithms cannot always issue fair lending decisions because of their inability to be free of bias.

But the industry-wide AI love fest persists due to its power to tackle risk management and other industry-specific objectives. Wealth management firms were found to be particularly high on artificial intelligence, while insurance companies use the technology at a lesser rate, according to the study.

Companies not yet utilizing the technology cite a lack of talent, unreliable datasets and high costs as roadblocks. Those already on board say AI's power to cut costs and generate new revenue give them a strong foundation to build on.

Scroll down to see more wealth management takeaways from the new research. The entire analysis can be found here.

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Wealth management leads the way

According to the study, 68% of wealth management organizations are using AI tools to support decision-making processes. About 32% of them report AI use for a significant number of cases.

The industry that comes the closest, banking, saw just 10% of respondents say they are using AI for a significant number of cases. The insurance and mortgage industries trail at 7% and 5%, respectively.

"Wealth management's ardent approach to the technology is notable given the wide variety of firms small and large reporting for this survey," the report states. "Participants come from seven types of wealth management firms and hail from companies with assets under management as little as under $100 million to $2 billion or greater."

Among the 47% of firms not actively using AI and machine learning, 29% of all respondents suggest their firms are still building a business case for their use, and 18% say they're still investigating the tools' potential. Only 2% of firms say they have no interest in pursuing the technology at all.

Easy-to-understand AI tools are the most popular

Among the combined 194 respondents currently deploying or piloting AI programs, 50% say they are using data-mining programs. That is followed by robotic process automation functions at 49%; and reasoning and problem solving programs at 47%. Wealth management firms use data mining (61%) and RPA (55%) the most, while half of banks say they use the technologies.

Planning and scheduling are other popular tools and are reported to be used by 39% of all respondents. Wealth management also tops industries using more niche types of AI functions from social intelligence, robotics including motion and manipulation and telematics, or the tracking of personal or commercial fleet vehicles.

To build, or to buy?

All firms in the survey rely on either established software or third-party vendor technology to achieve their AI-powered objectives, but business plans vary. About half of responding firms use enterprise-based software or specific data management tools, paying for outside technologies to achieve their data management goals.

As far as the firms who want to be more hands-on in developing their solutions, 43% of companies opt to co-develop software with vendors. About a third of those surveyed say their organizations remain independent and have built in-house AI solutions with no third-party support.

High tech, low excitement

AI and machine learning tools are not limited to complex problems or special-use cases. A number of financial services firms devote tools to mundane tasks related to operations, marketing, accounting and finance

But wealth managers make use of AI for operations most frequently with 46% of the 112 respondents saying their firms use advanced analytics tools to improve operational decision making.

The technology is used less often for sensitive tasks like compliance and underwriting in other industries, but wealth management bucks the trend. Just 21% of insurance organizations report using AI for compliance compared to 41% in wealth management; and 17% percent of banking organizations use it for underwriting versus 29% in wealth management.

Barriers to entry

Financial leaders say the biggest thing keeping them from implementing AI is a lack of needed skills. Of the 192 respondents representing firms not yet actively utilizing AI, 33% say they lack the talent within their own walls to deploy.

By sector, more than one in four respondents in each industry report a talent shortage. And despite the fact that wealth managers are found to be the biggest fans of the technology in the survey, they also report the highest rate of a lack of talent among industries at 42%.

Non-AI users also cite complexity, with 27% saying implementation is too difficult to achieve,

and another 16% saying they struggle to find the appropriate use case for AI within their business models. Money also ranks high as a prohibitive factor with a quarter of the 192 inactive AI respondents saying the initial cost in implementation is too high, and 21% saying they could not justify the rate of investment to introduce AI solutions. Poor data quality is another key barrier cited by 24% of all non-AI users.