A Python scoring engine for secondary market transactions — multi-factor buyer-fund compatibility analysis with ranked recommendations.
In ProductionIn the LP secondaries market, matching the right buyer to the right fund interest is part art, part science. The Buyer List Engine automates the science part: it ingests fund characteristics and buyer preferences, scores compatibility across multiple dimensions, and produces ranked buyer lists for each transaction.
The engine replaces hours of manual spreadsheet work with a systematic, repeatable process that ensures no strong buyer-fund match gets overlooked.
| Factor | Weight | Description |
|---|---|---|
| Strategy Match | High | Buyer's target strategies vs. fund strategy classification |
| Geography Fit | High | Buyer's geographic preferences vs. fund's regional focus |
| Vintage Preference | Medium | Buyer's preferred vintage years vs. fund vintage |
| Size Compatibility | Medium | Buyer's check size range vs. estimated transaction size |
| GP Relationship | Medium | Buyer's existing relationships with the fund's GP |
| Historical Activity | Low | Buyer's past transaction volume and close rate |
Ingests buyer preference data and fund details from Excel workbooks. Outputs formatted, presentation-ready ranked buyer lists.
Scoring weights are adjustable per transaction. Override defaults when you know a specific factor matters more for a particular deal.
Companion tool to expand the buyer universe by identifying new potential buyers based on strategy overlap and market activity.
Source code available on request. This tool processes proprietary market data and is used in production workflows.