Insurance: iLAB Understands Adoption and Innovation in the Insurance Industry
iLAB Understands Insurance
Over the past decade, technology has drastically impacted the insurance industry. For example, big data enables the use of telematics, providing insurers with actionable data about the habits of each individual customer, their susceptibility to risk, and trends in the areas they live and work. While these changes have reduced a company’s exposure to risk from a traditional actuarial perspective, the pressure to adapt and innovate new technologies has heightened the risk elsewhere.
By harnessing the power of big data, insurers can amplify the actuarial calculations that determine premiums. Premiums can be accurate to the specific customer, and high-risk candidates are avoided altogether.
The improper calculation of premiums or an inability to meet customer demands can have a devastating impact on a company’s revenue.
The Risk
Our client offered their products through a vast network of partner companies who must have access to new, constantly updating systems. Failure of these systems in the hands of valuable sales partners could lead to a significant loss of revenue.
Customers also expect these tools on their computers, tablets, and mobile devices so they can complete the application process on their own time. An inability to deliver these solutions or failure to work correctly can lead directly to a loss of sales to a competitor.
The iLAB Solution
The first opportunity for failure is identified in the system’s ability to handle continually changing actuarial information. Could this solution adapt to changes and implement them quickly across an entire sales network?
Through manual and automated testing, our team could run through combinations of sample customer inputs to ensure calculations were accurate every time.
Regression testing allowed our team to identify if new changes in actuarial calculations would impact the current systems, leaving the opportunity to use new data in calculation models. Using stress and load testing, we identified and addressed capacity issues with the system that would limit the number of users able to use the system before a failure occurred.
As a result, our client implemented an effective and efficient system that revolutionized their pricing model and streamlined sales efforts while avoiding the catastrophic risks of potential system failures.