How to score inbound leads at an RIA with AI
An implemented AI lead scorer for an advisory firm looks at every inbound lead and scores it on five dimensions, fit (does this match your ICP), AUM signal (any indication of investable assets), urgency (life event triggers), intent (what they actually asked for), and source quality. The score determines whether the principal is paged immediately or the lead goes into a slow nurture.
The five dimensions
- Fit. Does this person match your ideal client profile (niche, demographic, life stage)?
- AUM signal. Any indication of investable assets in their inquiry, name, or domain?
- Urgency. Life events that trigger immediate need (retirement, inheritance, divorce, sale of business)?
- Intent. Did they ask for a discovery call, or just download a guide?
- Source quality. Did they come from a referral, an ad, an organic search, a podcast?
What the score determines
- High score (8-10): principal is paged immediately, draft reply ready in 15 minutes.
- Medium (5-7): routes to a 24-hour follow-up cadence.
- Low (1-4): goes into a long-term nurture sequence.
- Spam/junk: archived without notification.
What it does NOT do
- Make the actual decision to take or reject a client.
- Discriminate on protected characteristics.
- Replace the principal's judgment in the first call.
The implementation
The lead scorer is one of the AI workflows in a Quiet Machines implementation. It's tuned to your specific ICP during the on-site build, and it learns from your accept/reject decisions over time.
Quiet Machines implements an AI brain inside advisory firms in a 3-day on-site build. AI visibility audit →