Goal of the analysis:
To assess the rate at which policyholders renew their policies and maintain their premiums over time. This analysis identifies factors influencing persistency rates, evaluates their impact on the company’s profitability, and helps develop strategies to improve policyholder retention.
Data required:
- Policyholder data, including demographics, policy type, premium amount, and payment frequency.
- Policy renewal data, including renewal dates and rates across policy types and segments.
- Historical persistency data segmented by time periods (e.g., 13-month, 25-month, 37-month persistency rates).
- Distribution channel data to link persistency with sales methods or intermediaries.
- Industry benchmark persistency rates for comparison.
Detailed step-by-step instruction on how to conduct the analysis:
- Define Key Metrics
- Persistency Rate = (Number of Policies In Force After a Defined Period / Number of Policies In Force at the Start of the Period) x 100.
- Renewal Rate = (Number of Policies Renewed During the Period / Total Policies Due for Renewal During the Period) x 100.
- Segment the Data
- Categorize policies based on type (e.g., term, whole life, universal life).
- Group data by demographics (e.g., age, income, geography) and payment frequency (monthly, quarterly, annual).
- Calculate Persistency and Renewal Rates
- Use the above formulas to calculate persistency and renewal rates for each segment.
- Track persistency at multiple intervals (e.g., 13-month, 25-month, and 37-month periods).
- Analyze Trends and Correlations
- Compare persistency and renewal rates across segments.
- Identify correlations between policy type, distribution channels, and demographics with persistency rates.
- Identify Drop-Off Points
- Examine persistency rates over time to detect periods with significant drop-offs (e.g., after the first year).
- Benchmark Against Industry Standards
- Compare your company’s persistency and renewal rates to industry averages to identify gaps.
- Visualize the Data
- Create time-series charts to show persistency rates over defined periods.
- Use bar charts or heatmaps to compare performance across segments and distribution channels.
Format of the output of analysis:
- Tables summarizing persistency and renewal rates by segment (e.g., policy type, demographics, payment frequency).
- Charts showing trends in persistency rates over 13, 25, and 37 months.
- Benchmarking report comparing company rates to industry averages.
- Identification of top 3-5 factors impacting persistency rates.
How to interpret results:
- High persistency rates indicate strong customer satisfaction and product alignment with policyholder needs.
- Low renewal rates or persistency drop-offs suggest issues with affordability, product fit, or customer engagement.
- Persistency rates below industry benchmarks highlight areas requiring immediate intervention.
- Correlation insights, such as persistency linked to specific demographics or channels, can guide targeted retention efforts.
Steps a company can take to improve on this measure:
- Simplify the renewal process through automation and reminders for policyholders.
- Offer incentives, such as loyalty discounts, for long-term renewals.
- Analyze customer feedback to identify barriers to renewals and address these concerns.
- Enhance training for agents to improve communication and ensure policyholders understand product benefits.
- Develop targeted retention campaigns focused on high-risk segments identified in the analysis.
- Use predictive modeling to proactively identify customers at risk of non-renewal and offer tailored retention solutions.
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