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Insurance

Process underwriting submissions

How AI/ML Improves its Underwriting & Supports for Commercial Insurers with Their Agents

How AI/ML Improves its Underwriting & Supports for Commercial Insurers with Their Agents

For:
- Insurer agents & brokers - Carrier agents
Goal:
Improved Employee Efficiency
Problem addressed
A commercial insurer found that its submission process was often too complicated and time-consuming due to issues experienced by the agents during the data validation process. The agents were spending hours or days manually collecting information from the web and validating them in what was over 250 submissions a month. Even so, the overall quoting conversion rate was at a low of 14%.
Description
Planck created accurate underwriting insights based on all data available online and offline through AI and integrating third-party data. They automated the eligibility process by automatically declining ineligible businesses and approving submissions, reducing turnabout time and the time spent by agents in this process.
Outcome
Thanks to this solution, agent collaboration was improved and intake data became more complete and accurate. It also managed to improve the Underwriting Operating Model already in place.
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Raw Data
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Machine Learning
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Automate Process
Conversational agents
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