About
In an ever-shifting world, finding the right price between risk & profitability accurately is key. Using extensive databases & the latest technology, PriMA evaluates each Home warranty’s accident-rate, severity & frequency on a granular local level.
Innovation presentation
Instead of using the traditional GLM model, that assumes linear data behavior and produces a single media price for an estimated risk, PriMA uses predictive models and machine learning to classify data by relevance in clusters using the Bayes model, generating a probability curve that measures the risk vs profitability ratio, showcasing the best price range. PriMA provides feedback to its databases, so it is constantly evolving and adapting to new market trends and variations.
Uniqueness of the project
PriMA shines on using great capillarity data, making a smart use of said data, and staying ahead of risk spikes.
Combining our unique Home Assistance extensive database, with over 40 years of compiled experience and granular data, with census local data (1.000 – 2.500 people) on building, environment & socio-economic variables, PriMA can be further enriched with B-Partner databases and custom ad hoc variables.
Instead of systematically crossing all variables, PriMA prioritizes the most relevant data to generate useful & meaningful clusters, that provide a deeper understanding of the whole situation and its risks assessment.
With its continuous data feedback and machine learning, PriMA is constantly evolving, updating the ratios, predicting risk spikes related to seasonality, extreme climate events & fraud claims, enabling prevention measures.
