Price Optimization Case Study
How can we address income protection portfolio profitability challenges and maximize customer retention?
Our customer faced profitability challenges in a certain portion of their in-force portfolio.They needed to improve portfolio profitability without adversely affecting lapse rates.
Montoux’s Decision Science Platform delivered the following outcomes:
• Built price-to-lapse elasticity models across product bundles
• Deployed a flexible pricing model to enable faster, more responsive pricing capability
• Integrated price elasticities and competitor prices in the pricing process
• Optimized in-force prices across product bundles to achieve profitability objectives
$25m (12%) uplift in portfolio embedded value
Minimized customer lapses while addressing profitability issues
Addressed portfolio cross subsidization challenges
Ensured claims ratios remain within target levels
Improve customer lifetime value by $6m per annum.
Reduce LTC claims costs and reserves by 5 percent, improve customer wellness outcomes.
Automating the experience study workflow; completed in near-real-time based on monthly data feeds.
Identified a pathway to increase sales by over 30 percent.
Increase in-force protection product Embedded Value by 12 percent.