Mind Foundry built a unique fraud detection and prediction solution based on AND-E’s specific requirements that could not be met by any off-the-shelf solutions. The Mind Foundry Platform empowers claims experts to identify, prioritise, and investigate fraudulent activity.
The solution accelerates the investigator’s ability to generate reports and close cases by integrating with external data sources, like Guidewire and ingesting over 7 years of data, including 20 million unstructured documents underpinning fraud ring detection. It automates the prioritisation of each case, using new and previously learnt features, including hand-written notes, phone numbers, registrations, and more.
The most relevant claims get flagged and prioritised in an investigations dashboard, so AND-E can resolve them in order of the likelihood that they contain actual instances of fraud. Other search features uniquely relevant to the fraud case are available in the handler's view, accelerating the ability to close each investigation quicker, accompanied by reports, supporting evidence, and investigator notes, all of which were previously accessed through a disparate set of tools or not accessible at all.
As new patterns emerge, using a Continuous Metalearning capability, the solution automatically and continuously integrates data back into the model to improve performance over time rather than suffer model drift, misalignment, or other modes of failure associated with model deterioration over time. New risks can be effectively governed while enabling the model to learn new types of fraud in production, meaning no manual retraining is needed to continuously adapt, optimise operations, and learn with AI.
