How Decision Science optimizes the MedSupp pricing process

How Decision Science optimizes the MedSupp pricing process

The Medical Supplement (MedSupp) market is a complex one for insurers to navigate and win. MedSupp is an entry level, homogeneous product characterized by low margins, intense regulation, and high degrees of price sensitivity. This makes the MedSupp market particularly competitive, especially when accounting for the product’s value in cross sales for short-term care, long-term care, life insurance, and annuity products. 

The product is typically sold through agents and repriced on an annual basis. Recently, insurers are struggling with a decline in MedSupp sales as a result of increased interest in Medicare Advantage. 

When competing in the MedSupp market, the competitive, commoditized nature of the product makes it difficult for insurers to differentiate. It involves having to answer what are sometimes difficult questions:

  • How should we balance profitability and price competitiveness / sales? 
  • What is the impact of price on sales, and what other factors drive sales?
  • What is the impact of price on cross-sales of other products and what are the other drivers of cross-sales?
  • What is the impact of price on persistency and what other factors drive persistency?
  • What is the relationship between price and claims outcomes?

By answering the above questions and incorporating these insights into the pricing process, MedSupp insurers can pull a key lever to increase value for shareholders and policyholders alike. 

Advances in AI, machine learning and advanced analytics enable MedSupp insurers with an opportunity to rethink their approach to pricing. By properly using AI technologies, data science, and market/customer data to inform pricing decisions, insurers can engage pricing as a strategic lever to achieve business objectives, improving sales, cross sales, and value as a result.

This approach is not unique across the broader insurance industry. Integrating AI technologies and advanced analytics into pricing and repricing decisions is common in general insurance and is gaining traction with forward thinking life and health insurers as well. For those moving quickly to adopt a more sophisticated, data-driven approach to pricing, there’s significant opportunity available to gain competitive advantage in the MedSupp market. 

Adopting a Decision Science approach to MedSupp pricing is an effective way to optimize pricing to achieve an insurers’ specific business goals and objectives. It enables insurers to model and explore a wide range of scenarios in order to identify the optimal pricing decision, taking into account the following value drivers;

  • Sales
  • Lapses
  • Premium (determined by price)
  • Claims cost
  • Distribution costs
  • Cross sales of additional products and their associated value

Montoux recently worked with a leading MedSupp provider to integrate a Decision Science approach to their pricing. By looking at the impact pricing has on new business value (VNB), sales, cross sales, morbidity and persistency, the insurer was able to properly understand the impact pricing changes have on customer lifetime value (CLV). 

This further helped the insurer to understand the price sensitivity of their MedSupp product and adjust their approach to pricing to improve value and competitiveness without adversely impacting CLV. 

The following shows how a Decision Science approach can complement the MedSupp pricing process;

Decision Science has powerful implications for MedSupp providers looking to engage pricing as a lever for growth. By grounding pricing decision making in data and exploring a wide range of potential scenarios to find the ideal approach, insurers can remove ‘gut-feel’ guesswork out of the process and can confidently price MedSupp products with the knowledge that they will achieve their business objectives.

Back to blog home