Drive smarter pricing models and customer experience touchpoints, with our proprietary scores for insurance risk and insurance premium.
Our data is sourced from reliable sources and meticulously curated to ensure 99.9% accuracy, and completeness. Designed to work with predictive models out-of-the-box.
• NSPL & ONS for base postcode data.
• UK Government region and zoning data.
• UK 2021 Census data.
• Gov.uk road accidents & safety (2019-2022).
• Gov.uk & ONS crime statistics.
• Mixture of car, motorcycle, and van data.
• Full manual review of all 1.8m postcodes.
• Manual review of many postcodes.
• No ethnicity, disability, gender, religious, or sexual orientation data used in this file.
Missing values filled using alternate data sources where possible. Where not possible then filled using a nearest neighbour algorithm weighted by distance and spatial homogeneity. Automatic outlier detection with manual review.
Label descriptions for dwelling type, land use, and industry types using hierarchical cluster analysis. Urbanicity scores derived from population density, accident, theft, building type, and other factors. Gov / ONS / census categorisations.
3 risk factors (accident, injury, theft). 2 market factors (complete, residual). Geospatial categorisations. Sociodemographic categorisations.
Risk factors use accident / theft statistics smoothed and classified by road use and postcode descriptive SHAP values. Market factors use genetic modelling to reverse engineer market data & smooth results. Categorisations use a combination of clustering and classifier techniques.
Better pricing models: Our data can help you to identify areas with higher accident, theft, or injury risk. Our scores will help you to calculate premiums more accurately and reduce losses.
Identify new markets: We have created a market-first score to understanding the market price for each Postcode. Invaluable to identify new markets for growth, or where your pricing is misaligned against the market.
Customer experience: Our data can be used to segment your customers based on their risk profile and other factors. It can be used to aid operations with customer retention conversations.
We publish quarterly updates that match Royal Mail's data.
We regularly update our proprietary scores, at least once a quarter.
Tested and trusted by our clients.
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