Discover How AI Uncovers the Hidden Value of Unstructured Data in Underwriting

Accurate and efficient underwriting is the cornerstone of profitable growth for insurers. To drive productivity, AI is key, but unfortunately not all data is structured and ready to use. In fact, 80% of enterprise data is unstructured, in the form of emails, text documents, legal reports, voice recordings, videos, social media. Get to grips with unstructured data and you’ll be able to extract and organise data to evaluate risk and mimic human understanding. Ultimately, you can reduce your costs, increase your win ratio, and boost market penetration. In this 1 hour free webinar you will: - Examine key AI use cases, like image and voice recognition, robotics, predictive analytics and NLU, to extract data, check and modify policies and triage submissions - especially for commercial lines where the risk is higher, and the conditions are unique - Reduce customer friction through technologies, like Natural Language Understanding, chatbots and virtual assistants, that allow you to tap into unstructured data - Enhance renewals and accurately evaluate your exposure by using AI to streamline manual, slow and error-prone processes and analyse non-standard policies - Transform submission triaging and processing through technology, like OCR and NLU, to drive efficiency and free up underwriters’ time for high-value tasks - Use AI to align underwriting with your risk appetite and make better decisions: Classify and code standardised, historical risk data to decide what’s viable Speakers include: Dante Tellez Guevara, Chief Data & Analytics Officer, Chubb Reid Colson, Chief Data & Analytics Officer, Markel Mahfuj Munshi, AVP of Commercial Lines Advance Analytics & AI, Nationwide Hélène Stanway, VP, Global Head of Technology Innovation, AXA XL Moderator: Pamela Negosanti, Head of NA Sales & Sector Strategy - Insurance and Financial Services, expert.ai This webinar is sponsored by expert.ai, by registering you will be sharing your data with this organization.