Nuon Experimenter

Validate underwriting, test pricing strategy, run lean experiments, learn faster and find new profit.

HOW IT WORKS: 

Nuon’s Factor Experimenter provides an underwriter with tools to try out price/factor adjustments on insurance products, giving them insights into the impact the changes would have if implemented fully in the product’s rating engine.

As well as being simple to set up, underwriters can run simultaneous experiments on live data against an array of possible scenarios.

An underwriter can specify which rating factor or factors they wish the AI to run experiments on using a subset of live quotes coming through the system.

The underwriter can specify the bounds of the experiment in terms of how much the factor price can be adjusted, how many quotes can be experimented on and how long the experiment should last. It is also possible to try out an array of price changes within one experiment.

Once the experiment run is complete, Nuon delivers the underwriter with a summary of the effect the price change would have if fully implemented in the form of a breakdown of how many policies are likely to sell in relation to each adjustment, and how much the overall premium is affected.

Pricing

  • Tiered monthly license fee
  • No setup fees, rolling monthly contract, first two months free

Setup timeline

  • 3-5 weeks, subject to product complexity

Entry requirements

  • Ability to make adjustments to pricing
  • Ability to pass real-time quote data via API
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Case study

An underwriter has been given an indication by an actuary that the loading on one of a product’s rating factors needs to rise by at least 3% to remain profitable.

The underwriter dials in the rating factor into Nuon and sets an array of experimental loading price adjustments ranging from 3% to 6%, with a 1% increment.

Nuon’s Factor Experimentor runs experiments with live quotes for a period of a week to gain insights as to what effects the price changes will have.

In this case, the service reports that raising the loading on the rating factor reduces the take-up rate by 2%, but that raising it by a full 6% has almost no additional impact on the take-up rate over the required 3% rise, making it the most profitable option.

The underwriter goes ahead and asks IT to increase the rating factor loading by 6% in the insurance products in-house rating engine.

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