Role of AI in Detecting Personal Injury Fraud in Rotterdam

AI is transforming fraud prevention in personal injury cases in Rotterdam by analysing big data for patterns typical of the region. Tools scan claims for anomalies such as unusual injury patterns around the Maas or claim clusters in Rotterdam neighbourhoods like Charlois and Feijenoord. CIEL integrates machine learning with local registers such as the Rotterdam injury archive, achieving 92% accuracy in risk scores for port-related accidents. However, the GDPR requires transparency in algorithms to avoid bias against port workers or migrants. Case study: AI unravelled a network of 60 false back injury claims linked to IP addresses from Rotterdam-South. Benefits: lightning-fast screening of claims from busy logistics hubs, with 25% cost savings for Rotterdam insurers. Drawbacks: the black box effect can unfairly exclude innocent victims of tram accidents, resulting in lawsuits at the Rotterdam district court for discrimination. Future: explainable AI (XAI) with audit trails, mandatory under the EU AI Act which classifies these systems as high-risk with human override. Insurers train on diverse datasets including Rotterdam demographics. The NVVK is testing pilots in Rotterdam with a promise of 35% fraud reduction in the region. For claimants: request the AI score and lodge an objection via Rotterdam legal aid. Combine AI with specialised legal assistance for optimal handling in this port metropolis. (212 words)