Articles - Transform commercial property underwriting with AI and NLU

The insurance landscape is becoming increasingly complex and demanding, against a backdrop of digitisation, globalisation, cyber threats, climate change, and increased workloads. The pandemic has shown how vitally important robust policy wording and underwriting procedures are, and that ambiguous wording can lead to unintended exposure, litigation, and errors. The demands and complexities are daunting, compounded by the need for ever-faster response times from clients.

 Leverage AI and NLU to tackle ambiguity in policy wordings, manage unstructured information and automate workflows
 Transform Commercial Property Underwriting with AI and NLU: New Report with Markel, Generali, Munich Re and Everest
 But with the adoption of sophisticated tools and technologies, carriers can create leaner, more efficient operations and meet these challenges.
 Find out how the industry is leveraging artificial intelligence (AI) and natural language understanding (NLU) to tackle ambiguity in policy wordings, manage unstructured information and automate workflows, in this new report by Intelligent Insurer “Transform Commercial Property Underwriting with AI and NLU” (sponsored by expert ai).
 Gain exclusive insights from:
 • Maria Grace, Chief Underwriting Officer, Property & Inland Marine, Everest Insurance
 • Guenter Kryszon, Executive Underwriting Officer, Global Property, Markel
 • Edward Leibrock, Senior Vice President, Head of US Corporate Property, Munich Re America
 • Sander van Voorden, Global Head of Property and Engineering, Generali
 • Moderator: Pamela Negosanti, Head of Sales and Sector Strategy, FSI, Expert ai

 By reading this report you will:
 • Modernise policy wording: Read key lessons taken during the pandemic from industry underwriters to future-proof your business, remove ambiguity in your policy language, tackle silent cyber and cyber risk to avoid unintended exposure and potential losses
 • Quantify your exposure: Incorporate technology to analyse first- and third-party exposure in your portfolio and learn how to get on top of your overall exposure using optical character recognition to determine what to disclose and the risks
 • Win more business: Understand how technology can drive operational efficiency and objectivity in the process to gain greater market penetration
 • Avoid leakages from policy wording: overlay technology to capture and track unstructured data to avoid inaccurate policy reviews and human error
 • Learn how to build a single system that delivers improvements in speed, efficiency, and accuracy, combining technology, human and automated components
 • Leverage machine learning, AI and NLU to better analyse policy language and improve underwriting. Hear how underwriters can utilise it to triage incoming submissions, automatically filtering out risks to bubble up the best opportunities and meet profitability targets

 Be better equipped to tackle new exposures such as cyber risk, assess risk more accurately and explore new avenues of business within commercial property by reading this new report.
 Helen Raff
 Head of Research
 Intelligent Insurer
 Direct line: +44 (0)203 301 8244


Back to Index

Similar News to this Story

Harnessing AI and Data in Insurance
Since the launch of ChatGPT at the end of 2022, artificial intelligence has captured the public’s imagination as well as investors’ attention. Over th
Global insurance market outlook 2024
Still strong labour markets and improving real wages are set to boost insurance demand. Higher interest rates will fuel strong sales in fixed-rate lif
Your Dreams are China in your hand
One of the more polarising questions in investment right now relates to China. Some suggest investors should avoid it, and some suggest investors can’

Site Search

Exact   Any  

Latest Actuarial Jobs

Actuarial Login

 Jobseeker    Client
Reminder Logon

APA Sponsors

Actuarial Jobs & News Feeds

Jobs RSS News RSS


Be the first to contribute to our definitive actuarial reference forum. Built by actuaries for actuaries.