Real-World Applications of Predictive AI: How Propensity to Buy Improves Close Rates

In today’s competitive insurance landscape, companies must innovate not only to stand out but to make meaningful connections with customers. Predictive AI models that target key behaviors, like “propensity to buy,” are helping insurers gauge a customer’s likelihood to convert from a quote to a purchase-especially crucial in saturated markets where high inquiry volumes make it challenging to differentiate high-intent customers.

Recently, an insurance technology leader for alternative distribution tackled this challenge using Fenris Digital’s predictive AI models to achieve real-world, measurable results in prioritizing leads and streamlining processes based on each customer’s unique risk profile.

By integrating Fenris’s predictive models, the insurtech was able to segment and prioritize calls based on a prospect’s likelihood to move through the quote and binding process, thereby achieving: 

• 27% increase in quote completions using the Quotability Model.
• 2x higher bind rates by eliminating low-probability prospects with the Bindability Model.

This targeted approach not only reduced time spent on lower-probability leads but allowed their teams to dedicate more resources to high-conversion opportunities. 

The practical results speak volumes about the power of predictive AI in transforming the customer journey. With these models, the insurtech provider was able to significantly reduce unnecessary touchpoints, leading to faster response times and enhanced service quality for prospects. Moreover, the insights gleaned from these predictive models allowed them to continually refine their strategy, ensuring they remain adaptable and responsive to shifting customer needs-a crucial advantage in today’s fast-paced insurance market.

For insurers looking to enhance customer experience and improve operational efficiency, adopting a predictive approach can make all the difference. By focusing on propensity-to-buy models, insurers can drive not only better customer outcomes but also achieve a more strategic allocation of resources. As this case shows, when AI-driven insights are applied thoughtfully, companies can achieve significant competitive advantages while delivering the tailored, frictionless experiences that modern consumers expect.

Download Use Case