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How Nuon AI works…

Reacting to Competitor Price Changes – Welcome to the first in a series of blogs focusing on how Nuon’s AI actually works.

By Mathew Donfrancesco Founding Partner, Nuon AI

We are kicking off with how we help an insurer respond in real-time, to pricing changes in the market.

This real-world simulation shows how the Nuon algorithm identifies and responds to a competitor who makes a factor change.  This particular scenario sees a price reduction on a motor product for legal cover.

Within two hours, the insurer using Nuon has learned, adapted and recovered its conversion rate.

The Nuon AI Pricing Service allows an insurance company to spot and adapt to changes in the marketplace. An example of a change could be a competitor lowering prices, requiring aspects of an insurer’s product to lower in price to keep the business or say a successful marketing campaign that strengthens an insurer’s product standing that allows for a price increase.

The Nuon AI Pricing Service responds to these changes by constantly experimenting with pricing, and reacting to the findings by applying small price adjustments to all subsequent quotes associated with the learnings.

To demonstrate how this works, we run a simulation against the Nuon AI Pricing Service that illustrates changes in the AI effects, via the Nuon Management Dashboard.

Simulation Example: reacting to competitor price or factor change

In the following simulation example, we pit an insurance company using the Nuon AI Pricing Service against a single competitor.

  • Initially, the competitor is set to have a lower base rate price, but with a higher price on a single rating factor.
  • During the simulation run, this is changed so that the competitor then matches on base rate, but drops the price on the single rating factor to below that of the insurance company using Nuon’s AI.

In the first management information [MI] dashboard chart (fig. 1), we can see the effect the competitor’s price change has on a rating profile, as adjusted by the Nuon AI Pricing Service. Initially, the AI raises the price to exploit the rating factor that is priced higher by the competitor. An example of this could be an insurer who changes from bundling or charging for legal cover or any other extra service.

When the competitor lowers the price, the Nuon AI responds by lowering the price of the profile to regain the business.

fig. 1

The next management dashboard chart (fig. 2) represents the take up rate (quotes purchased) of the simulation run. The initial part of the chart shows Nuon AI adjusting pricing to increase take-up from 70% to 80%. When the competitor price changes, the take-up rate drops to around 50% until Nuon AI readjusts to push it back up to around 85%.

Fig. 2
fig. 2

The next management dashboard chart (fig. 3) shows the average price change that the Nuon AI Pricing Service has affected to achieve the increase in take-up rate. Initially, it lowers pricing by around £8 per policy.

With the average price for this simulation set at around £800, this represents around a 1% drop to increase take-up by 10%. After the competitor price change, it readjusts the pricing further to regain business.

Fig. 3
fig. 3

CLOSING NOTES

The Nuon AI simulator is open to insurers, brokers or MGA operating on the UK aggregator sites. Every quarter we run a data simulation for three insurers, if you would like to be included, contact: pauld@nuon.ai

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