Telematics | Big Data | Usage based Insurance
During 2013, general-purpose insurance companies faced a crunch in business growth as the automobile-insurance market underwent a gradual decline. Specialty insurers were gaining traction from niche customer groups. The client needed to come up with a differentiated product/service to fuel the company’s growth. The client’s gross profit margin in automobile and trailer insurance during Q1 & Q2 of 2014 had decreased by 7% and 9% respectively. An obvious business solution was to offer differentiated insurance premiums to different customer groups to help tailor the client’s offerings according to more profitable customer groups.
Acquiring this capability depended on tracking driver behavior in each of the vehicle insured by the company. Another challenge that the client faced was filing multiple claims by customers who reported recurring accidents. This increased the service cost structure that the client had to bear. The company also wanted to promote safe driving by giving incentives to drivers for adopting a safer road behavior. Drivers would get bonus points for driving company insured vehicles safely. However, offering new services required the client to acquire real-time behavior observation technology to monitor each driver’s vehicle driving behavior. The client had a rough idea of what their company needed but was unsure of the technology solution that could deliver the business results.
After careful evaluation, the client chose Allied Consultants as their technology partner.
Data from the OBD II port, extracted through a data logger device is relayed to the cloud using Smartphone Bluetooth over the GSM network. The data residing in AWS S3 is sent to the dumper using Windows Services. Modeled data was pulled from SQLdb that resulted in data representation on the UI. The data flow from the user’s vehicle is represented below.
Design/architecture of the solution
The primary challenge that Allied Consultant’s developers had to overcome was the parsing of data from the AWS database and conversion of this data into the modeled form. The challenge was overcome by developing code using the Microsoft .net framework.
Results and Benefits
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