Raymond James Affiliate · Financial Services · Dallas, TX · 18 weeks
AI-powered client risk profiling deployed to 42 advisors
A wealth management firm managing $2.1B in assets was spending three hours manually reviewing each client portfolio. We developed an AI-driven risk profiling tool that cut review time to 22 minutes per client and uncovered $14.2M in rebalancing opportunities that manual reviews had overlooked.
Challenge
The firm’s 42 advisors spent about 3 hours per client on quarterly portfolio reviews, capping their capacity at 12 to 15 reviews weekly. Their manual, spreadsheet-based risk scoring hadn’t been updated in four years. This outdated process caused them to miss 18 to 24 rebalancing opportunities every week.
Approach
We developed a risk profiling tool that pulled portfolio, market, and client data directly from the custodian and CRM. It calculated a risk score and suggested portfolio adjustments for each client in under two minutes. The tool also provided a clear explanation of the top three risk drivers and recommended next steps.
Outcome
We cut portfolio review time from 3 hours to 22 minutes per client by automating data analysis. This allowed advisors to handle 40 reviews weekly, up from 12-15. In three months, the AI flagged $14.2M in rebalancing opportunities that manual checks missed. More frequent, detailed reviews lifted client satisfaction scores from 7.2 to 8.9 out of 10.
We kept things simple, and more than 9 in 10 advisors adopted it
The original risk score? Advisors found it confusing and didn’t use it. So, we stripped it down. We created a simple system that highlights the top three risk factors for each client, in plain English. The payoff? In just six weeks, 94 of every 100 advisors were actually using it regularly.
We dug into the data and uncovered $14.2M in missed revenue. Then, we closed those gaps, quickly.
Okay, here’s the deal. The old quarterly review was just too slow, it missed a ton of opportunities to rebalance more often. So, we built an AI tool that checks portfolios daily and calls out when allocations go off track. In just three months, it caught $14.2 million worth of adjustments that the old system completely missed.
How We Jumped on the Data to Ramp Up Customer Reviews, Quick and Clear
We slashed the review time from 3 hours to just 22 minutes. That freed up our advisors to check in with high-value clients every month instead of every quarter. And guess what? Client satisfaction shot up from 7.2 to 8.9 out of 10. Not too shabby, right?
Results
- $14.2M Rebalancing opportunities identified
- 3 hrs to 22 min Portfolio review time
- 42 Advisors using AI profiling
- 7.2 to 8.9 Client satisfaction score
Our advisors used to spend about three hours on each portfolio review and still missed some opportunities. Now, the AI system does the analysis in 22 minutes and spots things we didn’t catch. In just the first quarter, we identified $14.2 million in rebalancing opportunities.