Insurance Edge met up with two members of the team from Quantee at BIBA last month, for a quick brew and a chat. Always good to learn more about the latest developments in insurance pricing. Quoting the right price isn’t easy in today’s market and much depends on your particular niche, the data you have in your policy book already, or the sources of new data that you are working with. You can find out more about Quantee here by the way.
IE: To what extent can MGAs or brokers match rising claims costs to pricing risk, in specific areas, like say Motor, home, gadget, bicycle etc?
Q: The only answer to mitigating effects of inflation is to invest in the process – improve the precision of risk models to enhance CoR/LR, automate modelling and expose pricing changes to sales channels to reduce expense ratio, etc.
– Can multiple data sources help price risk better, or do they sometimes add a bit of uncertainty re overall trends?
The ultimate goal is to have more quality data to enhance precision of user’s pricing models. Multiple sources may help, however one needs to remember that we need to integrate with these data sources, process them and answer to the question whether the new data statistically enhance our KPIs. In order to do that we need proper tools to perform such integration and analysis quickly without additional costs – and this what Quantee is doing.
– Can software track true demand for insurance products vs sentiment?
Software is a huge help in terms of collecting data from A/B tests for demand and sentiment analysis and then using this data in the process – integrating, processing modelling and using in price optimisation and impact analysis. So with modern technology like this, you can get a real sense of the demand in real time.
– Once an insurance brand is using dynamic pricing can it help them spot trends within their policy book, if so, how?
Absolutely. Dynamic pricing is done through utilisation of data and in particular data that helps understand the current environment. With these data points, and having technology to effectively analyse them, you can spot trends within the book very clearly. These can help to see how accurate the price model is, how it is effecting the profit margins as well as what demographics the insurance product is successful/unsuccessful against, as a few examples. This is something Quantee makes very easy for our users to be able to do and maximise their insights into competitiveness.
– Can software help insurance brands develop and price new products, using a competitive price point, or rival company benchmark?
There are several techniques to include competition in pricing – for example using the best price model inside a demand model. In order to execute such techniques, particularly in online pricing (pricing engine) we need a sophisticated technology, such as Quanteee.
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