The opportunity to improve value in Annuity portfolios
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Sales of annuity products have experienced a significant surge in response to the rising interest rates in recent years. “Market conditions continue to drive investor demand for annuities. Every major fixed annuity product line experienced at least double-digit, year-over-year (YOY) growth,” said Todd Giesing, assistant vice president, LIMRA Annuity Research. “Despite expectations that interest rates will level off, LIMRA is forecasting total annuity sales in 2023 to exceed $300 billion for the second consecutive year.” Insurer’s capacity to fully capitalize on this product growth is contingent on their ability to quickly and effectively model the various scenarios associated with the sale of an Annuity.  

Challenges modeling payout annuity products 

While the rise in interest rates has been a huge positive for the payout annuity market as a whole - it has been challenging for annuity pricing teams. The volatility has created a need for more active resetting of crediting rates across the market, which in turn has created additional jockeying for position in what is generally a competitive, price-sensitive market.  

For annuity pricing teams, this means balancing the appetite for granular pricing levers across crediting rate buckets and other pricing factors to seek competitive advantage, with the complexity of exploring a large potential solution-space within a very short pricing cycle.  

Insurers Montoux work with describe the following key challenges in the modeling of their Annuity portfolios:

• Limitations in Pricing workflows of rigid modeling systems built primarily for the purpose of Valuation and/or the computational and governance limitations of Excel
• Limitations in the number of pricing scenarios that can be run in order to explore complex solution spaces
• Challenges from computational intensity resulting in significant model run times and costs and/or run scheduling bottlenecks when accessing computational grids
• Inability to quickly scan the competitive market and respond nimbly to changes in market conditions
• Manual processes and efficiency of analysis given the need to turn around high-frequency pricing updates quickly

Technology has risen to the occasion

Montoux addresses the challenges listed above in several ways:

1. Inbuilt pricing scenario analysis

The Montoux platform had dedicated pricing scenario analysis features, including the ability to easily define and execute a large number of scenarios to explore different options for pricing levers. When pricing these scenarios, users can incorporate competitive positioning data allowing a range of rank and distance metrics to be included. Similarly, the pricing scenarios can include price-to-sale elasticity effects.  

2. Increased model and workflow flexibility

Montoux’s highly flexible workflow engine can be configured to suit the needs of annuity pricing processes, automating the flow between input data, modeling and output data/analysis. 

Montoux’s model development environment, known as Model Canvas, is transparent, meaning that insurers can edit and modify the model themselves. This functionality is used extensively by Pricing teams who require the flexibility of model updates without going through a queue and the rigorous process of updating a Valuation model. Model Canvas also enables rapid model-conversion/onboarding, as well as trusted calibration to the base Valuation model where required.

Pricing workflows can also incorporate automated pricing algorithms such as solving for rank, distance or percentile positioning under a variety of weighting schemes. 

3. Reduced model runtimes and compute costs

Using its proprietary HyperScale model runtime engine, Montoux leverages the best of modern cloud infrastructure to improve model runtimes by 50-100x and reduce model run costs to an average of ~10% compared to legacy Valuation systems. These massive reductions enable insurers to run the volume of scenarios they need to feel confident that their Annuity portfolios decisions are right. 

Case study: Tier 1 US Annuity Insurer Seeking to Improve Market Position Through Better Pricing Modeling Capability 

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Customer problem

Montoux’s customer faced the following challenge in their Variable Annuity Pricing Process:

• The customer wanted to introduce additional granularity to crediting rates and discount factors used in their pricing analysis. This significantly increased the complexity of the solution space requiring a drastic increase in the number of pricing scenarios considered. However, model & process runtimes severely limited the number of pricing scenarios that could be run during a pricing exercise.
• Manual effort required in producing reporting and analysis for the pricing governance committee tied up actuarial resources that could be deployed to other high value activities.
• Dependence on the insurer’s Valuation model created an external dependency on model development processes and risk to a tight pricing timetable due to being a lower priority on the valuation team’s computing grid.
  

Benefits realized with Montoux

Montoux enabled the customer to achieve the following outcomes:

• Automated integration with Cannex market data for production of real time competitive analysis and report generation
• Efficient frontier construction powered by a ‘bulk scenario analysis’ capability allowing tens of thousands of pricing scenarios to be easily defined and run 
• Rapid processing times - Montoux’s HyperScale engine spins-up massive computational resources allowing the tens of thousands of scenario to be run in minutes, without users having to worry about grid configurations, job queue management, or run costs (a function of the cost efficiency of the Montoux platform plus inbuilt cost management guardrails)
• Automation of manual processes to free up ~50% of actuarial time consumed each pricing exercise

Conclusion

Insurers seeking to improve the performance of their Annuity portfolios no longer need to be constrained by modeling technology designed primarily for the rigid nature of Valuation work. Montoux is working with large, leading Annuity carriers to improve workflow and model flexibility and automation, ultimately resulting in the ability to run more scenarios with less manual work - a win/win for busy Annuity modeling teams. 

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