I nsurance products come in all shapes and sizes. Although there’s a large variety of insurance companies on the market, they often face common problems including:

    1. A time consuming manual underwriting process
    2. Loss ratio not decreasing
    3. Difficulties identifying low-risk customer prospects 
Risk Assessment

The Situation

Our client in the commercial insurance space needed to make more accurate predictions on how to charge insurers the right premium to ensure the profitability of the business.

The Problem: 

Underwriters manually review and evaluate properties or other insurable assets. This is a time consuming process that reduces efficiency, productivity, and profitability.

The Solution: 

We built an end-to-end insurance platform powered by machine learning that is being utilized by the entire commercial lines division of a mid-sized insurance company. Our machine learning platform automatically provides important external data to underwriters. 

Results: 

The final deliverable was a software platform that streamlines the underwriting process and gives premium recommendations that accurately reflect risk.

The machine learning platform analyzes tens of millions of data points collected from disparate data sources to provide actionable insights to underwriters. We have found strong correlations between externally collected data and risk.

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