Why implementing flat price increases to in-force books is the wrong approach for Australian life insurers

Why implementing flat price increases to in-force books is the wrong approach for Australian life insurers

It’s no secret that the life insurance industry in Australia and New Zealand faces a profitability problem. According to KPMG, Australian life insurers suffered losses of $1.3 billion in the 2020 financial year alone. 

These losses are unsustainable, and threaten the viability of many of the products life insurers and their policyholders depend on. The pricing curves many insurers rely on are out of date, designed to sell rather than maintain value. This goes hand in hand with Australian life insurers historically prioritizing new business growth, an approach that hasn’t succeeded as evidenced by direct premiums declining by 6.1 percent in 2020. Life insurers are now forced to look more closely at their in-force books, and specifically solve the problem of optimizing in-force value.

In order to immediately address the problem of profitability, executives must rethink the way their businesses set prices. Life insurers can significantly move the dial by adjusting their approach to in-force pricing. Because of the potential value this could generate, in-force pricing is becoming a top priority for many. But getting it right isn’t a given. Without optimizing their pricing curves and moving away from flat price increases, life insurers leave significant value on the table.

Montoux’s experience supporting Australian life insurers through major in-force re-prices indicates that an in-force price optimization approach provides the opportunity to improve embedded value by at least 2x what can be achieved through a generic flat increase. Here’s how that works. 

In-force prices need to increase - but not through traditional flat price increases

Life insurers are generally slow to adapt and innovate - and the outdated way insurers in Australia and New Zealand determine prices is a perfect example. Life insurers set and manage prices from a ‘product view’ by effectively balancing the competitiveness of pricing in the market with value at the point of sale. They also rely on pricing curves that were designed specifically to generate new sales. In today’s market, this approach is out of sync with reality. 

Profitability pressures mean insurers need to prioritize maintaining value, especially as they raise prices across their portfolios. Implementing flat price increases across in-force blocks may offer the benefits of simplicity and ease of implementation, but offer little in terms of ability to achieve efficient and optimal value outcomes.

The consequences of this traditional approach are obvious - they’re happening right now. Executives understand that when prices increase, lapses are inevitable. The two are intrinsically linked and can have a detrimental effect on in-force value, but few life insurance executives understand the details of how. Pricing teams don’t properly account for lapse propensity nor can they effectively predict how many policyholders will lapse. This means life insurers might lose more customers than they expect, including their better customers. 

For example, an insurer increases IP pricing for a cohort with a large number of profitable term policies, causing a number of policies to lapse. This decision is costly because, while the IP component might not be profitable, the term policies likely are, and are therefore a higher priority when it comes to retention. Armed with granular customer knowledge, a life insurer might instead further increase prices on a less valuable cohort with fewer profitable products.

In-force price optimization enables life insurers to improve profitability while better serving their most valued customers

Access to cloud computing, AI technologies and advanced analytics, makes flat price increases at best obsolete, and at worst counterproductive. Life insurers could instead be leveraging the ability to set prices from a ‘customer view’, through in-force price optimization. Setting prices at the level of individual customers or cohorts can materially improve profitability and reduce lapzation risk.

By structuring price increases to come through over time across in-force books, life insurers can ensure their most valuable policies are, on average, less impacted than vice versa. In order to do this, insurers require: 

  • A data-driven understanding of how price impacts lapses for different types of customers with different types of product
  • Access to the tools and methodologies that enable re-shaping of the pricing curve - allowing distribution of price increases over the lifetime of the policy and reducing the impact on more profitable policies versus less profitable policies

Montoux’s experience supporting Australian life insurers through major in-force re-prices has demonstrated an ability to improve embedded value by at least 2x through in-force price optimization. For a medium-large in-force book, this is an embedded value difference in the tens of millions of dollars - the exact sort of value improvement executives and boards are seeking in the current environment.

This is an easy win for life insurance executives.  While it’s true varied price increases may be more complicated to communicate than flat increases, the massive potential value upside makes this trade-off an easy one. It’s fair to say that communication about price increases is painful, regardless of complexity, and through high quality communication insurers can ensure that more complex changes are no more challenging to present to customers than more traditional flat increases.

The result of this approach is a less dramatic impact on lapse rates alongside improved value outcomes

In addition to unlocking a significant amount of value, this optimized approach to price changes ensures price increases impact fewer profitable policies and overall lapses drop. It also means, because life insurers retain more customers, they can significantly reduce the number of price increases while achieving the same value across the portfolio. This approach also allows life insurers to approach pricing strategically, leveraging decision science to ensure their approach is aligned with company priorities and long-term objectives.

Montoux has significant experience guiding life insurance executives towards a more intentional, data-based approach to pricing. If you’d like to discuss how Montoux can help increase the value of your in-force books and reduce lapses through this approach, reach out here.

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