How to Optimize Product Enhancements

with Predictive Analytics 

 

Client’s Situation

With advances in technology and modeling techniques, many carriers are looking to integrate predictive analytics to advance product sophistication for profitable growth. Our client has been working with a leading predictive modeling firm for their expertise in machine learning and actuarial consulting to help improve their Personal Lines Auto pricing.

The early results from their initial predictive model showed improvements across the board—improved new business conversion, improved retention, and decreased loss ratio—a win-win scenario. After a few years, our client wanted to refresh the predictive model and test whether more recent modeling efforts could identify additional pricing segmentation. As expected, the latest model highlighted additional lift in pricing segmentation—great! However, the increase in pricing segmentation would result in more than expected premium disruption for current members. 

 

Traditional Approach

Over time, predictive models are refreshed and improved due to new techniques and approaches.  These advances in pricing and sophistication are traditionally favorable and can lead to profitable growth.  However, there may be tradeoffs that carriers need to consider when implementing new or updated predictive models. Given the common challenges from agents and members from high amounts of premium disruption, carriers may decide more traditional pricing and underwriting actions are preferable. Opting for less disruption may be beneficial in the short term but may limit the long-term growth potential that more advanced pricing and segmentation can offer.

 

MCA Approach — Finding the Right Balance

We believe prioritizing predictive models and advancing class plan segmentation will drive improved pricing accuracy for long-term growth and profitability for our clients. However, we also know the value mutual companies place on product and that underwriting “explainability” and “manageability” are key guiding principles that shape the evolution and innovation in product strategy.

We believe the right solution for our clients balances product innovation with both “explainable” and “manageable” in a way that strengthens their mission and purpose to their agents and members.  

 

Results

Our analysis revealed opportunities in our client’s class plan to create a more stable renewal experience, whereby, our client could integrate the latest predictive model recommendations while also minimizing agent and member disruption—all within the regulatory requirements for each market.

Key Highlights:

  • Manageable: The majority of members’ (over 50%) renewal premium change will be within 5% of their current premium; a significant increase from the new model recommendations.
  • Explainable: Less than 15% of members will experience more than 10% premium change at renewal; the more favorable result is from the new model recommendations.

In addition to creating a more manageable and explainable renewal experience for our client’s members, our solution will allow our client to take advantage of the full modeling solution to improve new business pricing. We think this is now a win-win-win!

 

Solutions for a Changing Landscape

The industry is changing, and traditional solutions may leave you falling behind. MCA can assist your mutual company to find hidden opportunities in your data so you perform steadily for the long term. Contact us at mutualcapitalanalytics.com so we can enable you to serve your customers and communities better and improve your business performance.