The Next Best Action: Using Machine Learning to Anticipate Client needs

Create a vendor selection project & run comparison reports
Click to express your interest in this report
Indication of coverage against your requirements
A subscription is required to activate this feature. Contact us for more info.
Celent have reviewed this profile and believe it to be accurate.
12 December 2019
Awaad Aamir


Wealth management firms have historically lacked the ability to tap into the reserves of client data they’ve collected to unlock its commercial value. With advances in predictive analytics and Machine Learning (ML), wealth managers are starting to meet client needs with higher percicion and greater cost efficiency.

Next Best Action (NBA), an application of ML, delivers prompts that let advisors act on time-critical client needs with highly personalized recommendations. This report looks at the applications of NBA tools in the Wealth management space, its ecosystem of vendors, the technical components that enable its functionality, as well as the dangers of integrating a sophisticated AI tool into core components of an advisor’s workflow.

Subscription required

Access to this content requires a Celent research subscription.

Subscribers should sign in to access this research.

If you are not a subscriber, register now or contact us to find out more about our subscription options.

Insight details

Insight Format
Geographic Focus
Asia-Pacific, EMEA, LATAM, North America