We worked alongside a mass-market retail travel insurance provider with over 2.6 million policies. The client has two main brands, each with its own travel insurance niche: one for those with significant medical histories, and another for backpackers and digital nomads.
The client was using an internal underwriting analysis tool to aggregate their data and give them a basic report writing capability, but wanted to delve deeper into the data and needed granularity when it came to finding causes and correlations.
The client wanted to build up their loyalty programme to migrate travel insurance policyholders away from the traditional aggregation platform by analysing how best to manage the relationship and improve retention, whilst seamlessly adjusting around 6 million price points directly fed into the aggregation platform or hopper.
As a result, the company decided to look for an insurance data analytics platform that would suit their unique needs.
As mentioned above, the client was using an internal underwriting analysis tool to aggregate their data and give them a basic report writing capability.
This internal self-coded system, however, was lacking in its flexibility and required specialist training and expertise to operate. Whilst the system was able to process a lot of data, it was very rigid in its design and was only able to provide data analysis in a limited, structured format.
The GIROUX.ai platform offered the client a number of benefits, including the following:
Triangulation analyses by cover types and traveller type
Our client has been able to benefit from the following results:
In terms of trend analysis, the team’s underwriters have found a huge benefit in being able to filter on any metric to delve deeper into the performance.
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