Double submission throughput and reduce the cost to acquire new business by automating data prep for exposure models and risk rating

The best commercial property underwriters aim to rapidly screen and prioritize submissions in order to be the first to market, increase volumes without scaling headcount and maximize their quote-to-bind rate. However the complexities of the submission data, combined with repetitive manual processes makes it challenging for carriers to achieve these objectives.

Reduce the cost of acquiring new commercial property business
Screen & prioritize submissions algorithmically
Automate geocoding via the Google Maps integration
Increase speed-to-quote with RMS and AIR output


  • Manual processes cause delayed responses to brokers and distribution partners
  • High operational costs, slow turnaround times and lack of audit trail
  • Difficult to screen, score and prioritize submissions due to data inconsistencies
  • Critical data to drive insights locked in spreadsheets and files

How Quantemplate helps

Quantemplate enables commercial property insurers to quickly screen and prioritize submissions by automating the data preparation process, utilising machine learning and applying validations.

Diagram of Exposure Management data flow showing broker submissions across different sectors (retail, industrial, condo). Schedules of Values are mapped to a common format, geocoded via the Google Maps API, construction and occupancy codes are applied and year-built is cleansed. The data is validated then feeds Verisk Air and RMS risk models, Analytics via Quantemplate, and rating and exposure management systems. Rapid data throughput allows carriers to be first to market, and to rapidly screen and prioritise. 

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