As the insurance landscape evolves, data fusion becomes the bedrock of adaptive risk assessment and personalized coverage.

Processing and analyzing vast customer information, claims data, and risk profiles can overwhelm traditional systems, hindering efficient decision-making. Integrating data from various touchpoints like IoT devices, wearable tech, and social media requires overcoming interoperability issues and ensuring data accuracy. Managing data privacy concerns while harnessing the potential of personalized insights presents ethical and regulatory hurdles. Solving these big data obstacles is critical for insurers to unlock valuable insights, improve customer experiences, and refine risk assessment strategies.