Using Machine Learning to Identify High Potential Client Prospects in Wealth Management Posted on : Feb 23 - 2019

In business you often want to accurately predict a relevant product need for a given client.  Much research has been done on “recommender” systems using, for example, collaborative filtering to suggest a product based on either the purchases of similar clients or on the past purchases of that client.

Then, there are the cases where you have a product or service and want to find the ideal client. This becomes more difficult if the ideal client population is a small subset of the general population.

This scenario is particularly tricky in the Wealth Management business. Many of the desirable clients who have accumulated enough wealth to require sophisticated advisory needs – investments, tax, estate planning, trust – already have long established relationships with a trusted advisor.  In some cases, these relationships span multiple generations. These clients are notoriously sticky, and tend not to move their business unless they are dissatisfied or the advisor moves to another institution.

A better strategy might be to go after the “emerging affluent” who are accumulating wealth and beginning to appreciate that managing it themselves is not the best use of their time and does not guarantee the best outcome. These clients, however, will not all become profitable. And, the ones who do may take quite some time to get there.

So, client prospecting in the wealth management business is difficult – the already profitable can be impossible to land, and the not yet profitable may take years to fully develop.  So what can be done?

In these situations, the solution is to leverage your own data to learn how to identify and differentiate the best prospects.

Most wealth management leaders use their knowledge and experience, and anecdotal evidence, for prospecting. They will usually have a few great sources for referrals, or a favorite industry or region where they have had success, or they know that prospects from certain channels are better than others. View More