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Top 5 Best Telematics Device Options and Solutions | Reviews

 

Telematics-Based Insurance Device Reviews: The right telematics data collection technology can make or break your telematics insurance and usage-based insurance program strategy at a time when consumer behavior is changing rapidly. 

As insurance telematics and the global usage-based insurance (UBI) market have grown substantially over the last few years, the technology choices for implementing insurance telematics programs which reward safe drivers based on their driving patterns have now become even more diverse, staying on top of technological advancement and telematics trends is important for insurers to stand out and be successful.

Techniques for collecting, consolidating, and analyzing the data to assess driver behavior continue to be refined as the technologies for accomplishing this evolve and improve. With so many available technology choices, one question is frequently asked by insurers: What data collection option best suits the programs we want to offer drivers?

The insurance industry has always been data-centric in-order to align insurance premiums with actual need via usage-based insurance (UBI), but telematics adds extra dimensions of volume, timing, and large-scale processing to the equation. A substantial challenge exists: the workload involved in capturing, processing, and analyzing information from telematics devices on millions of vehicles. Telematics devices typically produce data records which can include G-force values, date, time, speed, location, cumulative trip mileage, fuel consumption, and more. The quality, scope, and precision of the data depend on the type of telematics device that is capturing and transmitting it. The ultimate goal is to use the driver and vehicle data collected, combined with insurance claims data and other information to perform analyses to accurately identify, predict, and influence driver risk and claims losses.

How to Choose the Right Telematics Device? From the perspective of the insurer, particular kinds of information are vital to assessing and grading driver behavior—regardless of the equipment that collects that data. Each of the data collection solutions discussed in this article—smartphone, self-powered, OBD, black box, and OEM embedded devices—have varying pros and cons. Rather than favoring any one approach over another, we discuss how each solution has certain strengths and weakness that may make it effective for one type of insurance program, but perhaps not another. Check out these five in-depth professional unbiased telematics device reviews and transformative data collection technology solutions that matter most to leading insurers to stay relevant and meet the challenges of tomorrow.

 

Let's get started:

  1. Smartphone Data Collection
  2. Self-Powered Data Collection
  3. OBD Data Collection
  4. Black Box Data Collection
  5. OEM Embedded Data Collection
  6. Factors to Consider When Comparing Data Collection Solutions
  7. Conclusion

 

1. Smartphone Data Collection

Telematics solutions based on smartphones avoid installation costs while providing reasonable data accuracy and they can also provide a variety of custom features through apps. These solutions offer a straightforward path to telematics data collection through the smartphone’s data transmission capabilities, including cellular data and WiFi.

With the diversity of smartphone makes and models, as well as different sensors, algorithms must be applied to normalize the data that is collected, stored, and analyzed. Once the data is normalized and the other considerations addressed, smartphone telematics solutions can be successfully incorporated into a variety of telematics insurance programs.


Harnessing the power of telematics through smartphone sensors

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2. Self-Powered Data Collection

Devices in this category include the battery-powered Bluetooth®-enabled beacon, which is often mounted on the dashboard or windshield. Deployment costs are minimal, making this a cost-efficient choice for mid-range to mainstream insurance telematics programs. Bluetooth connectivity with devices, however, can be a challenge for some users.

Flexible self-powered options include both devices that communicate directly with servers using their own cellular modules, in addition to devices that tether with the smartphone and use the smartphone’s cellular capabilities to get data to the server.

Tethered smartphone connections can increase customer engagement and flexibility. Vehicle identification data is captured and can be harvested later, even when a smartphone is not present in the vehicle. Data transmission can also be performed using the smartphone communication and data plan capabilities, which eliminates the need to set up separate communications through the Bluetooth hardware.

Self-powered devices that communicate directly with servers minimize customer interaction, however, there is a tradeoff with a smaller density and duration of data that can be captured and transferred with this option.


Mobile and wireless IoT devices empowered by telematics

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3. OBD Data Collection

The OBD-II interface, which has been a federally mandated feature on all US vehicles since model year 1996, is one of the earliest technologies for vehicle telematics data collection. The equivalent standard in Europe is called EOBD (European On-Board Diagnostics).

As a long-running, well established solution in the marketplace, permanently plugged-in OBD devices have a proven track record and high level of acceptance. Driving data is typically transmitted directly over cellular networks for processing. This moderately priced option can be combined with smartphone connectivity to enhance driver engagement.

 

Robust next generation OBD-II telematics with OBD-II, GPS and MEMS sensors

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4. Black Box Data Collection

As the de facto standard for UBI programs in the UK, black box technology captures and delivers a stream of data from active vehicles using a cellular service for communication. A fixed electronic device—the black box—securely mounted inside the vehicle ensures that accurate trip and collision data is obtained and transmitted to a data center.

Popularity of this approach is especially high in regions where vehicle theft is rampant, offering a proven, tamper-resistant method for prompt recovery of stolen vehicles. However, these aftermarket devices must be professionally installed in vehicles, leading to higher installation costs.

 

Black Box is a telematics box fitted to a vehicle to record and monitor the driver's behaviour performance

Learn more about Black Box data collection

 

5. OEM Embedded Data Collection

Data extracted directly from built-in vehicle sensors eliminates aftermarket installation costs, but a lack of standardization among OEMs has impeded market acceptance. Expect to see innovative programs developed over time to take advantage of these built-in capabilities, which could lead to highly accurate data capture, new ways to monitor driving, and integration with driver-assistance features that could improve safety and reduce crash frequency and severity.

Although this form of data collection for insurance telematics is relatively uncommon today, a TSP equipped to integrate with embedded car systems and make sense of the disparate data will be able to tap into the benefits for both insurers and their customers as the technology matures.

 

Original Equipment Manufacturer (OEM) telematics solutions

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Factors to Consider When Comparing Data Collection Solutions

When weighing the merits of data collection solutions, consider these factors:

  • Data requirements
  • Continuity of the data record
  • User experience

These factors are discussed in the following sections.


> Data Requirements

To meet the data requirement standards for a given program—whether a smartphone, self- powered, OBD, black box, or OEM embedded solution—continuous, calibrated measurements must be captured from the smartphone or vehicle sensors. For in-vehicle, cellular-based OBD solutions and Bluetooth-based OBD this is achieved by the direct connection to the vehicle’s engine control module. In mobile applications, the use of data fusion techniques can enhance the quality of collected sensor data, as well as exclude poor quality data that cannot be verified or validated. In some instances, data fusion techniques have also been applied to OBD solutions to enhance data results.

Vehicle speed can be determined precisely with solutions consisting of an OBD device, based on data from the Vehicle Speed Sensor (VSS) in the automobile and GPS-based speed. In smartphone solutions, vehicle speed is calculated based on the GPS signal, which requires that a strong
GPS signal is being received. The VSS data values can also provide insights into certain types of driving behavior by detecting indications of wheel spin and loss of vehicle traction.

Positional and speed data collected from smartphone-only solutions can come quite close to the quality of positional and speed data from OBD-equipped options (including Bluetooth), for capturing data relevant to crashes. Because the smartphone is typically not physically secured, the data collected can be affected by movement within the vehicle, such as the phone sliding off a seat into the footwell during hard braking, which creates potentially confusing data.

As shown in Figure 1 below, in dense urban areas with strong GPS signals, positional data accuracy is very good. In marginal areas with lower signal strength, positional accuracy is less precise. The degree of accuracy also depends on the quality of the GPS receiver, which can vary from device to device.

User based insurance and telematics remotely‎ vehicle tracking

Figure 1. Degree of GPS Accuracy Can Vary


Under optimal conditions, data collected from GPS speed calculations compares favorably to captured data from OBD vehicle speed sensors, as shown in Figure 2.

usage-based-insurance-GPS-Positional-Data-Accuracy-in-Urban-Settings

Figure 2. GPS Positional Data Accuracy in Urban Settings


By nature, a smartphone-only solution—in most instances—cannot deliver the same degree of precision when providing crash data as a permanently mounted black box or other device firmly attached to the vehicle. Depending on the insurer’s needs, however, smartphones return a level of data accuracy that is well suited to a wide variety of program requirements.

For example, the smartphone may be lying on the seat beside the driver or loosely resting in a cup holder so that during a collision, the accelerometers may not provide precise data. Secure mounting enables better calibration of the positioning of the unit and better data results.

In comparison, OBD-based solutions (including those with Bluetooth connectivity), OEM embedded solutions, and black box solutions capture data from a telematics device mounted in a permanent position within in the vehicle. This provides a high degree of data fidelity from the accelerometers. Overall precision and sensitivity to low-energy impacts offer a level of data useful in assessing crash scenarios. As shown in Figure 3, the data fidelity provides a deeper view into the nature of the crash and generates a much better picture of the incident.

UBI-Insurance-Data-Values-Support-Construction-of-Vehicle-Incidents

Figure 3. Data Values Support Construction of Vehicle Incidents

 

> Continuity of the Data Record

Data that is captured continuously and is accessible as needed improves the value and utility of the driver evaluation. An OBD or black box-equipped solution, as well as OEM solutions, essentially connect a vehicle to the data collection mechanism (rather than the actual driver of that vehicle). In comparison, mobile device solutions rely on the owner of a smartphone bringing that phone along in whatever vehicle is being driven.

There are pros and cons to each approach. For younger drivers without their own vehicle, the use of a smartphone can track that driver’s performance regardless of whose car is being driven, letting them establish a driving record that can help keep premiums low. Success of this approach depends on whether the mobile application being used can automatically activate in driving situations and minimize ways that the driver might circumvent the monitoring process. The more contiguous the data record tracked for the driver, the more precise the ratings based on driver performance. If the solution depends on the driver selectively turning the app on or off during trips or travel, the potential for fraud is much greater. Authentication models for smartphones can be used to keep track of when the ignition is turned on or off, so insurers have a reliable means to determine how frequently drivers are using the software.

OBD solutions and self-powered device solutions can provide a more consistent, stable solution that cannot be turned off without detection. These solutions are mounted in place and ready to detect trips and validate vehicle identification from the moment the car moves. However, they typically lack any mechanism for identifying individual drivers in situations where more than one person often drives the vehicle. If, for example, a father lets his son drive the family car on a daily commute, the data collected during the trip cannot determine whether the father or son is driving unless there is additional input to identify who is the passenger and who is the driver.

 

> User Experience

Solutions that are simple to install and use on a daily basis provide the best experience for drivers and have the greatest chance for adoption and long-term use. Positive engagement with the users, making it easy to understand current status of the policy and receive relevant communications from the insurer, is an essential part of most telematics insurance programs today. Engagement that helps a user become a better driver and offers incentives for safe driving practices are an important aspect of the overall user experience.

Different user demographics have different expectations of an insurance telematics solution, and insurers should be aware of these differences when crafting solutions. Younger drivers, particularly those in the millennial generation (born between 1982 and 2004) are highly adapted to smartphone use. They are digital natives and use social networking heavily. They are open to new technologies and would be likely to respond positively to a smartphone app that highlights metrics that determine the driver’s premium while offering tips on how to improve one’s behavior.

The social aspects of smartphones could also be used by the insurer in innovative ways to create a dialog with the drivers. Incentivized programs or gamification could be used to influence driving behavior, encouraging safer practices and generally creating greater engagement from the drivers. Active use of smartphones to make calls while driving, for example, could be discouraged, depending on the insurer’s policies. Using transparent algorithms to assess driving behavior and encourage better driving practices would likely be positively received by this generation. Other age groups could be responsive to these incentives as well.

Older drivers may not own smartphones or may prefer OEM solutions that are built into the vehicle and require no interaction from them. Older drivers may also be less inclined to engage in incentive programs that offer only slight improvements in their rates and prefer solutions that operate completely in the background, not requiring their engagement or interaction in any way.

For mobile applications, power management is another critical aspect of the overall user experience. If the sensors are active continuously and drain the smartphone’s battery so that it is not available for use when needed, most users won’t be inclined to use this solution over the long term. Developing algorithms to selectively engage sensors and manage power use proactively can extend the smartphone battery life and improve the user experience.

Self-powered device solutions offer a more flexible approach to the user experience by developing the program features to enhance a smartphone-based telematics program, but they also place greater demands on the user, who must successfully complete the Bluetooth association with the accompanying hardware, install the required application, and ensure that cellular communication is available on a regular basis to complete the data collection cycle.

Conclusion

Telematics programs differ widely. Selecting a data collection solution should be based primarily on client needs and program objectives, as well as the options that best support the solution. For example, commercial programs present very different needs and requirements than a personal lines program. A telematics solution focused on lead generation and customer acquisition will, by nature, differ from a more comprehensive implementation (and might initially use a smartphone for collection and then later replace it with an OBD device or a self-powered device using Bluetooth).

As these technologies continue to evolve, other factors—such as differences in the characteristics of certain consumer segments—can weigh into the evaluation and influence the selection of the most appropriate telematics data collection approach to meet the challenges. We recommend that you consult an experienced telematics service provider (TSP) with a platform and strategy that is fully data agnostic to investigate and evaluate the trade-offs and capabilities of all technology solutions – and never assuming you are forced to one or a limited number of data collection options.

 

Download White Paper: Comparing Smartphone, Self-Powered, OBD, Black Box, and OEM Embedded Devices

 

 

 


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