Lead Scoring in Private Lending: Definition, Process, and AI Enhancements
What is lead scoring in private lending?
Lead scoring ranks potential borrowers (or broker‑submitted deals) against a set of criteria to decide which are worth prioritizing. In private lending, this blends borrower fit and deal viability so your team focuses on opportunities most likely to close.
Why does lead scoring matter for private lenders?
- Many incoming leads are noise—wrong loan type, unrealistic expectations, poor borrower fit.
- Without scoring, teams spend equal time on bad‑fit and high‑potential leads.
- Well‑scored leads shorten cycles and improve closing rates.
How does lead scoring work in private lending?
1) How do you define your criteria?
- Loan type and amount
- Property type and location
- Borrower track record
- Exit strategy clarity
- Credit profile (if relevant)
2) How do you assign weights?
Not all criteria are equal—e.g., property type might matter more than credit for certain programs.
3) How do you score and rank?
Each lead gets a numerical score based on the weighted criteria. Higher scores rise to the top of the queue.
How does AI improve lead scoring?
- Instant Scoring at Intake: immediate priority list for the team.
- Pattern Recognition: learns from historical funded deals to find true predictors.
- Adaptive Criteria: adjusts weightings as market conditions change.
- Real‑Time Alerts: flags aging high‑potential leads.