Our carefully curated team of senior professionals brings real-world experience to solve your business challenges.
A mature UK Motor insurer worked with HAL to rebuild key existing pricing models using Gradient Boosting Machines (GBMs). Insurers increasingly use machine learning models like GBMs to automate and increase the accuracy of their pricing models. However, GBMs are more challenging to interpret and communicate than conventional modeling approaches.
Our experts used our proprietary model to build a custom and interactive GBM visualisation solution to review performance and explain the impact of individual data features on the model output. This made model review and sign-off faster and more insightful as the complexity of the GBM was transformed into an interactive and easy-to-understand output.
New entrants have no pre-existing claims to use as a basis for pricing models. So instead, our experts used our proprietary model and price comparison website quote data to build a rating structure based on market prices.
The team then worked with the client underwriters to apply adjustments tuned to the client’s target market.
Our work also built categorisations for postcode, vehicle, and occupation for deployment in the live rating. This approach transformed the complexity of thousands (vehicle and occupation) and millions (postcodes) into a detailed, communicable, easy-to-deploy risk index.
Our team subsequently worked on similar Home and Van insurance products with the same client.
Our client wanted assistance to fully understand the implications of the General Pricing Practices and Fair Value regulation on their proposed go-to-market proposition.
The firm was keen to get under the skin of fair pricing regulation, given the brand in question is a household name and likely to receive significant scrutiny when entering the market. In addition, they are a customer-centric organisation that recognises some of the commercial challenges this approach could present in the General Insurance market.
As a result, our teams used our proprietary model to work through a series of commercial options and scenarios to support decision-making and strategic design.
A significantly reworked go-to-market proposition was the outcome of our work. Also, the forward-looking strategy was greatly enhanced to support the firm when it enters the market.