Artificial Intelligence (AI): Technology that enables machines to simulate human intelligence, including learning, reasoning and decision-making.
Machine Learning (ML): A subset of AI where systems learn from data patterns to make predictions or decisions without being explicitly programmed.
Generative AI: AI models that generate new content such as summaries, text or insights based on large datasets.
Natural Language Processing (NLP): AI technology that enables computers to understand, interpret and analyse human language, including medical reports and claims descriptions.
Insurtech: Technology-driven innovation designed specifically for the insurance industry to improve efficiency, pricing and customer experience.
Telematics: Technology that collects real-time driving data such as speed, braking and cornering behaviour to assess risk and determine insurance premiums.
Cloud-Native Infrastructure: Insurance systems built directly in cloud environments, allowing scalability, flexibility and faster deployment of digital services.
Predictive Analytics: Advanced data analysis that uses historical and real-time data to forecast future outcomes, such as claim likelihood or fraud risk.
Intelligent Document Processing (IDP): AI-powered technology that extracts, classifies and validates data from structured and unstructured insurance documents.
Usage-Based Insurance (UBI): A pricing model where premiums are calculated based on real-world usage data, such as actual driving behaviour.
Fraud Detection Algorithms: Machine learning models designed to identify suspicious patterns or anomalies in insurance claims.
Explainable AI (XAI): AI systems that provide transparent reasoning behind decisions to ensure regulatory compliance and trust.