
Case Study: Custom Software Development
Learn how a midsize Kansas City insurer/broker created a system that saved them on average, 480 hours of staff time per week while improving claims risk analysis.
Client Snapshot:
Entrepreneurial, midsized company operates as the administrative and service arm for a leading national insurance provider to residential real estate investors.
Challenge:
Due to rapid growth the company realized their core operating system which heavily relied on time consuming, manual entry processes was becoming a choke point.
Under the weight of increased volume, the system was unable to efficiently onboard new clients or update critical aspects of a client’s insurance coverage. Rather than significantly increase headcount to address these issues, leadership decided to upgrade the system.
Solution:
Fluent was selected to build a new system which was architected and built on a .NET platform with numerous integrations to outside information services.
Given the lack of any packages capable of transacting and tracking complex functions, such as proof of coverage, billing statements, escrow applications, payment tracking, etc. it was deemed necessary to build the system from scratch.
Key upgrades to the system include the following:

Improved user experience and collaboration








Automated billing statements, payments, late notices, etc.








Automated client self-service risk profiling and coverage approvals








Property-centric tracking of ownership, upgrades and coverage changes over time








Ability to select future dates for activating coverages








Enhanced data accuracy via geocoding and address standardization








Standardized enterprise, client specific and new ad hoc reporting
Final Outcome:
Now, with over 7000 clients and growing, the new system reduces many thousands of transactions to a mouse click.
It achieves in one stroke what would have taken more than twelve people over a week to accomplish. The system also facilities improved analysis of claims risk relative to numerous key variables.