CORE INSURANCE

Woodruff Sawyer Announces Ryan Meissner to Lead Southern California Employee Benefits Practice

Woodruff Sawyer | January 28, 2022

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Woodruff Sawyer, one of the largest independent insurance brokerages in the US, today announced Ryan Meissner has been promoted to Vice President, SoCal Employee Benefits Practice Leader. Prior to his promotion, Ryan served four years as the Vice President of Data Analytics for Woodruff Sawyer.

Previous to his roles at Woodruff Sawyer, Ryan held underwriting positions at Burnham Benefits and UnitedHealth Group.

As Southern California Employee Benefits Practice Leader, Ryan plans to focus on "making clients' lives easier" through better analytics tools, automation, and continuing the focus on employee needs as well as those of our HR clients.

"Ryan has been a substantial contributor to the Employee Benefits Practice since he joined our firm four years ago. His client focus, financial and business acumen along with his ability to improve outcomes for how we serve clients and address client solutions makes him the right person to lead our SoCal Employee Benefits Practice. We're looking forward to seeing his positive impact on our business."

- Kathy Prosser, Woodruff Sawyer Senior Vice President and National Employee Benefits Practice Leader

About Woodruff Sawyer
As one of the largest insurance brokerage and consulting firms in the US, Woodruff Sawyer protects the people and assets of more than 4,000 companies. We provide expert counsel and fierce advocacy to protect clients against their most critical risks in property & casualty, management liability, cyber liability, employee benefits, and personal wealth management. An active partner of Assurex Global and International Benefits Network, we provide expertise and customized solutions where clients need it, with headquarters in San Francisco, offices throughout the US, and global reach on six continents.

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Spotlight

AI can improve productivity and help in decision making through training datasets. According to the survey of the Dataconomy, nearly 81% of 225 data scientists found the process of AI training more difficult than expected even with the data they had. Around 76% were struggling to label and interpret the training data.

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