Numerous Internet-of-things (IoT) solutions for the mobility domain are on the market to assess driver and vehicle risk and to maintain a regular engagement with the driver. Some motivate drivers to adopt safer and more ecological driving styles. Others help insurers, fleet operators, and their customers steer motor claims easily and efficiently. Still, others evaluate the effectiveness of Advanced Driver Assistance Systems (ADAS).

But companies often use these solutions in isolated ways and miss opportunities to exploit the generated data across the entire (insurance) value chain; e.g., for modelling purposes to gain competitive advantage from real insights into risk and claims. Furthermore, the intelligent combination of different data sources can enable use cases in new and yet unexplored fields.

Imagine the following:

• You are able to coach and alert a driver based on real-time contextual risk information like weather, traffic flow, and road-risk to provide mitigating actions in real time. How can this be used to actively reduce accident frequencies, or influence the driver’s actions in a desirable manner yielding lower risk?
• You can quantify and benchmark the emissions for a specific vehicle, based on where and how it is driven. How can this be used to report sustainability metrics and to motivate people to adopt more ecological and economical driving styles?
• You know about collisions in real time — not just that it happened but also the vehicle damages and expected loss costs, as well as potential bodily injuries of the passengers and the likelihood of an economic total loss. How can that change the assistance services provided to the driver and the way the damage is assessed and a claim settled?
• You have - at your fingertips - reliable digital traces of incidents to assess claims, besides the feedback from drivers. How can that reduce the time to assess a damage; e.g., from reducing the need to inspect a vehicle on site?
• You can rely on robust (not tamperable) “digital witness” data recorded on board to identify and track stolen vehicles or assess and defend indemnity. How can that help in recovering more stolen vehicles, digitally reconstructing accidents, and objectively quantifying impact severities and indemnity; e.g., when the opponent vehicle was operated in automated mode without a human driver in control?
• You can exploit sensor data beyond mobility use cases using the same scalable base platform and best-in-class tools. How can that future-proof investments in mobility and enable expanded or entirely new value propositions; e.g., for gaining efficiencies and preventing losses on properties or in sustainable farming by adopting advanced AI & Machine Learning methods?

There need no longer be separation between driver risk, vehicle risk, and associated services. Companies such as insurers and fleet operators can now look at data points from different sources to get comprehensive pictures that reveal more and more data insights over time. That’s why we developed our msg.IoTA sensor fusion platform, to enable superior capabilities from the intelligent use of data for deep insights – on driving, drivers, vehicle-risks, collisions and claims, emission tracking, and benchmarking and on driver preferences and service needs.

Here’s Why

msg.IoTA is hardware agnostic, cloud-native, and quickly scalable globally. It taps into a growing list of pre-integrated vehicle sensors to focus on vehicle usage, driving behavior, collisions, thefts, and motor claims. It is the analytic playground and workshop for continuous innovation, as well as the operational engine room for analytics on risks, claims, accident reconstruction, emissions, vehicle usage, driver profiles, benchmarking, and service preferences.

Our clients are materially benefitting from adopting msg.IoTA in multiple ways:

• Low entry hurdle to implement and start: Fast and modular adoption with a proven, robust and secure cloud platform. A large German insurer deployed a new motor insurance usage-behavior based insurance product to the market from scratch in six months.
• Raw and enriched data points transparently provided “out-of-the-box” for analytical exploitation; e.g., for differentiating analytical model trainings, simulations, and operational executions.
• Independence - continuous inflow of new capabilities, sensor sources, and integrations within mobility the domain and beyond. This is achieved by our own product innovations as well as from an ecosystem of global leaders such as SAP, insurtech, and academia, curated and orchestrated by msg global. Our clients can benefit from our expertise in ESG & Profitability/Performance analytics and reporting, and a pre-integration with industry standard tools in this field such as SAP Sustainability Control Tower.

The msg.IoTA platform is an effective starting point to enable relevant and long lasting capabilities in a fast changing world of mobility, thereby ensuring the value of telematics data does not decay or, in other words, has no half-life. We’ll share how the platform works as a digital ecosystem in the next post. So, stay tuned.