What is Propensity Scoring?
Propensity scoring is a data-driven approach that helps identify which pension schemes are most likely to be receptive to our services. By analysing multiple factors, we can prioritize our outreach efforts and focus on the opportunities with the highest potential for success.
Our Approach
We use a weighted scoring system that combines five key factors, each scaled to 100 points, to calculate a comprehensive propensity score for each scheme. The final propensity score is the sum of weighted contributions from all five factors, normalized to a 0-100 scale for easy comparison.
The Five Weighted Factors
| Factor |
Weight |
Scaling (0-100) |
Calculation Method |
| 1. Size |
20% |
100 points |
Asset-based tiers:
• <£100m = 0% of scaling
• £100m-£500m = 25% of scaling
• £500m-£1bn = 50% of scaling
• £1bn-£2bn = 75% of scaling
• >£2bn = 100% of scaling
|
| 2. Funding Level |
25% |
100 points |
Funding ratio bands:
• <60% = 0% of scaling - big exposure to failing scheme and PPF assessment
• 60%-80% = 50% of scaling - some insolvency risk but possibly 10 years+ from buyout funding
• 80%-90% = 100% of scaling - sweet spot as circa 10 years from buyout
• 90%-100% = 75% of scaling - still probably 5-10 years away from buyout
• 100%-110% = 50% of scaling - probably within 5 years of buyout
• >110% = 0% of scaling - above settlement point with superfund and possibly buyout, risk of short term appointment unless stated run-off LTO
Note on Buyout Funding: The propensity scoring adjusts for the fact that publicly available funding levels (from accounting basis or Technical Provisions on the scheme funding basis) are typically 10%-25% more generous than actual buyout funding levels. Our scoring methodology extrapolates approximate buyout positions from the figures reported in scheme accounts, with schemes at extreme funding levels (very high or very low) receiving lower propensity scores as they are less likely to be immediate opportunities.
|
| 3. In-house Administration |
20% |
100 points |
Binary classification:
• Yes = 100% of scaling
• Outsourced or No or Not Known = 50% of scaling
|
| 4. Actionable Intelligence |
25% |
100 points |
Consulting Budget-based scoring:
• Under £500K = 0% of scaling
• £500K+ = 25% of scaling
• £1M+ = 50% of scaling
• £1.5M+ = 75% of scaling
• £2.5M+ = 100% of scaling
Based on total consulting budget for diagnostic modules relevant to Aptia
|
| 5. Weak Competitor |
10% |
100 points |
Competitive analysis:
• Capita, Equiniti (aka EQ), or LCP = 100% of scaling
• Other competitors = lower scaling
|
Calculation Formula
Propensity = Sum of (Weighted Scaling × Calculated % of Scaling) across all five factors
Example: (20% × Size Score) + (25% × Funding Score) + (20% × In-house Score) + (25% × Budget Score) + (10% × Competitor Score)
Data Source: Consulting Budget Intelligence
The Actionable Intelligence factor is based on total consulting budget data for diagnostic modules relevant to Aptia's services. This data is derived from diagnostic reports and financial analysis, providing insight into the scheme's capacity and willingness to invest in professional consulting services. More opportunities identified where the value created for the scheme far outweighs the associated consulting or admin budget indicate greater potential for engagement and conversion.
Key Insights from Our Analysis
- Schemes analysed across the UK pension landscape
- A-List schemes (propensity score ≥ 50) represent the highest propensity opportunities
- B-List schemes (propensity score < 50) are monitored for hooks but are currently lower priority
- Pipeline schemes are actively being pursued with high engagement potential
- Normalized scoring ensures fair comparison across all scheme sizes and types
How to Use This Information
Use the Focus filter to view A-List, B-List, or Pipeline schemes. The color coding and visual indicators on the map help you quickly identify and prioritize your outreach efforts. Pipeline schemes are marked with a distinctive green border and pulsing effect to highlight their active status.
Continuous Improvement
Our propensity model is continuously refined as we gather more data and insights. We regularly update the scoring factors and weights based on actual engagement outcomes, ensuring that our targeting remains accurate and effective. Feedback from the sales team is incorporated to improve the model's predictive power.