Wealth firm retains $40M+ AUM by using Einstein to predict client churn. Here’s how AI changed the game. #RuleSixPack #1

Let’s talk about how to bring this kind of efficiency to your business.

When high-net-worth clients go quiet, it’s often a sign they’re preparing to leave. This firm used Einstein Discovery to identify the early signals — and saved over $40M in assets.

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The Challenge

Small Wealth Management Firm (approx. 20 employees) was facing a critical issue: Missed signs of disengaged clients. This challenge wasn’t just an operational nuisance—it was costing them valuable opportunities, time, and in many cases, client trust.

How We Solved It

Using Salesforce’s Financial Services Cloud, Einstein Discovery, CRM Analytics, we designed a solution where Einstein Discovery in FSC analyzed behavioral churn signals. This was then put into practice by ensuring Advisors were alerted before high-risk client exits, significantly improving the retention rate.

What This Replaced

Previously, this process was entirely human-powered. It relied on Manual churn detection via CRM history, or "gut feel", often leading to delays, errors, or inconsistent results.

By automating and enhancing this workflow, the team unlocked more capacity and accuracy.

The Result

The estimated value created from this change: $40M AUM retained (~$400K+ annual revenue).

• ~2,500 HNW clients

• 1.5% reduction in churn = 37 clients retained

• Avg. AUM/client = $1.2M

≈ $40M AUM retained, ~$400K+ annual revenue protected (1% fee basis)

Could This Be You?

If you're struggling with missed signs of disengaged clients, it's likely that similar tools and design patterns could dramatically simplify your workflows too. Let’s talk about how to bring that efficiency to your business.

Be sure to review the rest of the RuleSixPack of Use Cases!

Contact Rule Six Consulting Services