Agent Allocation and Branch Optimization
Opening new locations is always fraught with risk and potential to go wrong. The insurance company has an aggressive plan to open in multiple locations, and therefore required a robust data layer that enabled better decision making.
Utilizing our extensive data universe, we built a data science model that looked at the relative prosperity of various location across the country in multiple categories (metropolitan, urban and rural). We combined this model with the insurance company’s internal data to arrive at ‘target’ locations that would have high potential and low risk for market entry.
Once our recommendations were submitted to the insurance company, they were validated by the sales team and then used to open multiple new offices. To date, over 50 offices have been opened on the basis of our recommendation. A few non-performing offices have also been closed on our recommendation. Both of these activities have resulted in enormous growth and also improvement in loss ratios.
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