M2M technologies are devices capable of connecting to one another through a communications channel; this mainly includes machines with online connectivity such as smart devices or black boxes. Utilizing these technologies can enable your organisation to track the locations of your customers via black box or mobile technology.
This technology will be used for insurance purposes on a widespread scale, with many insurers tracking their customer diaspora globally in order to more accurately gage levels of underwritten risk. Our range of datasets can allow your company to gain an accurate insight into customers’ locations, creating meaningful insights into a range of risk-related factors.
Road Route Risk Analysis
Road Route Risk Analysis involves analysing the conditions encountered by one or more mobile assets including the routes taken and the condition and types of vehicles involved, calculating an insurance cost based on the assessed safety of the journeys. Use our data to calculate the risk associated with each route, accounting for accident blackspots, road types and traffic volumes. Taking this data-driven approach creates fairer rates, saving money for the best prepared and more accurately reflecting the journeys with the most associated risk.
By combining this tracked data with our geospatial datasets, we can accurately map out your customers’ daily routines to indicate their day-to-day practices. DriverHalo™ brings geospatial data to your tracking data to transform your consumer profiling, minimising risk, reducing pay outs and ensuring that your premiums align more effectively with your customers’ lifestyle than ever.
At Mapmechanics, we can augment your tracked customer data with geospatial information to provide an unparalleled insight into customers’ routines and interests. Beyond this, we can also track significant changes in customers’ behaviours to ensure that your customer profiling is always up-to-date, allowing you to reduce risk and keep pay outs down.
Monetizing Your Data
If you have a big dataset of locational or road-related information, we can take steps to organise and it in order to inject new value. In many cases, one seemingly unusable set of data can be analysed, augmented and sold in unexpected and niche ways for use in markets you may have never thought of before.