Solution
Mind Foundry has built a unique solution to predict and prevent large losses (of over £50,000) based on Aioi Nissay Dowa Europe's (AND-E) specific requirements that could not be met by any off-the-shelf solutions.
We combined a number of different data sources, including driving behaviour data, geospatial data, and environmental data, into a single machine learning solution. The solution looks at the likelihood of an accident occurring on specific routes taken.
Machine learning models are used to analyse continuous behavioural and historical driving data, looking specifically at customers driving patterns, like speeding and braking, as well as road familiarity, because the data shows that drivers are more likely in certain circumstances to have an accident on roads they are more familiar with. This is then paired with road risk data, such as how many accidents there are on the M4 each year. The models are then aggregated to provide an all-inclusive risk score.
As new patterns emerge, using a Continuous Metalearning capability, the solution automatically and continuously integrates new data back into the model to improve performance. New risks can be effectively governed and analysed by human operators, while enabling the model to learn new types of large loss, meaning no manual retraining is needed to continuously adapt, optimise operations, and learn with AI.
