Leverage Automation in Underwriting to Reduce Costs & Speed-Up Response Times

Delivering quick response times is now vital for any high-growth business. But most underwriters don’t have the infrastructure to automate unstructured communications at scale—especially when it comes to the broker relationship. In fact, according to a recent case study by Hiscox, 97% of broker requests are incorrectly routed. Leverage automation in underwriting and you’ll maximize the likelihood of a timely response, saving both time and money. In this webinar, you'll find out how automation is reducing manual workload for underwriters, streamlining operations, and elevating the broker experience. You’ll find out how to: - Avoid intellectual waste: Exploit automation to reduce the time skilled underwriters spend on repetitive tasks and redirect labour to adding real value—developing the client relationship - Streamline communications: Integrate robotic process automation, machine learning, language processing, optical character recognition and analytics to triage submissions from multiple sources, detect and remove duplications, reduce human error and ultimately reduce processing time - It’s not just about being faster…use automation and analytics to make better quality underwriting decisions and select the right risk - Pinpoint the opportunity automation creates to reduce costs in terms of new hires and efficiency savings - Explore how automation can be used to elevate the broker experience, drive efficient operations, and dramatically speed up response times And hear from these automation experts: - Tim Yorke, Chief Operating Officer, AXA Commercial, AXA - Bradley O’Connor, Head of Operations Technology Platforms, Beazley - Dr. Michael Zimmer, Head of Artificial Intelligence and Machine Learning, Zurich Group Germany - Claudio Morando, Head Portfolio Analytics & Strategy EMEA, Swiss Re - Moderator: Ed Challis, CEO, Re:infer This webinar is sponsored by Re:infer. By signing up you agree to share your information with this organisation.