Financial Services - Property & Casualty Insurance
Insurance companies employ a variety of AI/ML solutions, including RPA, chatbots, Intelligent Document Processing, ML and AI models, to optimize their existing underwriting, policy servicing, claims management and processing, damage assessment and Fraud detection. AI technology in insurance has the potential to significantly improve operational efficiency, provide total risk visibility. It enables insurance firms to pivot towards a more digital customer experience and technology-enhanced product lines. Catastrophic modeling based on ML models, enabled to improve prediction of future catastrophe risks in areas like risk due to natural calamity.
RPA along with smart data extraction tools can handle a high volume of repetitive human tasks which helps large insurers to streamline critical operations and free employee capacity. NLP, chatbots and voice assistants can be used for automated responding to queries about policy, the status of claims. While detecting and analyzing damage claims, Computer vision matches the claimant's accident/vehicle damage photographs to the image database to assess damage severity and estimate repair costs. It minimizes claim handling time and reduces claim processing expenses. Drones integrated with computer vision technology can be used to assess property damage more efficiently and offer an estimate of repair costs in the event of property insurance claims.
AI powered Claims management systems to interprete data from multiple sources including photos captured by drone, GIS coordinates for faster and accurate claim processing.
Intelligent chatbots to offer pre-sales and post-sales support, AI-driven digital marketing, positioning of best-fit solutions based on customer interactions.
NLP-powered tools to recognize critical data from emails, scanned documents, and PDFs, automatic classification and indexing for deeper insights.
AI-assisted application processing, 360° evaluation of risk factors, quicker approvals, optimization of underwriting resources.
ML-powered analysis of customer needs and expectations, life-stage evaluation, user behavioral studies, profile-based marketing of pertinent products.
Big Data algorithms for accurate assessment of risk profiles, coverage and premium calculations based on AI-enabled telematics .