Introduction
As we live in an ever-evolving world, different solutions that we offer our clients,and our customers also evolve with time. Today no part of a human life is untouched by technology.Not only have, AI&IoT, brought about a paradigm change in the way we analyze data&do predictions based on past data, they have also been redefining the way how we price our offerings and solutions to customers who too are becoming more& moreamenable to cost effective digital offerings. Across various sectors, these digital offerings have also been gathering rapid pace. Asfor instance, in June 2022, Samsung announced its 3-nanometer semi-conductor technology compared to the conventional 5-nanometer. If the then reports are to be believed,Samsung had claimed that this new 3-nanometer semi-conductor technology can reduce the power consumption by almost 45%, improve performance by 23% and reduce area by 16%.
Insurance sector has usually been traditional in its approach towards underwriting of various offerings. While some of this may still be required for Commercial Property and Casualty Insuranceproduct offerings, many retail Insurance product offerings like Auto-Insurance have caught the attention of many Insurance players and almost every player has been trying to make the experience better for customers leveraging technology to better its offerings to customers. As per a June 2022 report of the Boston Consulting Group, post covid saw accelerated technology adoption in Insurance sector with Insurtechs having raised $14.4 billion across 644 deals in 2021, surpassing the total raised in 2020 by about 87% and reaching a cumulative ten-year total of $43.8 billion from 2012 to 2021.
Auto Insurance underwriting has, for many decades, been using risk factors that range from a customer’s demographics to his/her driving record, age, credit history, type of vehicle, engine capacity, claims history etc. to cost and price the risk. While these risk factors have etched their importance in pricing various offerings, these traditional underwriting approaches do not consider driving behavior of the driver, action or inaction of the driver given the driving context or the other environmental factors during driving to better price the risk. Though one could arguethat information like accident history or no claim discounts are good proxies of the driving behavior,a real time monitoring of the individual driving behavior through Telematicsnot only adds valuable insights ofadverse driving eventslike over speeding etc. but also other driving co-relationswith road network characteristicslike junction, crossing, intersection, flyover etc.
To address some such challenges, Insurance playershave been trying to make gradual, yet important, strides in vehicle telematics technologies.
Telematics Technology
Merriam-websters defines Telematics technology as“the combination of information technology with telecommunications especially the integration of telecommunications networks in vehicles (as for collecting data on performance)”.
Telematics data refers to a variety of information that are collected in real time from drivers using various sensors that are either retrofitted in the vehicles (like On Board Diagnostic kits or OBDs) using OBD ports or using mobile applications. OBDs, due to them being hardware devices, are expensive and cannot be expected to be fitted in every vehicle. This is apart from other associated costs that come along with registering the devices and maintainingthem, besides such devices becoming outdated in no time. Mobile based telematics app solutions are, hence, becoming more popular.
Factors driving Telematics Technology adoption
Current lingering inflation,due to geo-political conflict hasbeen driving customers to scout for more cost-effective digital offerings with better coverages and experience. A survey conducted by Nationwide in Dec 2020, found that around two-thirds of consumers were open to allowing telematics to capture driving behavior if it resulted in premium discounts. Mobile App basedTelematicscomes as a usage-based offering that makes the underwriting risk factors more deterministic and helps safe driving Insureds to save premium costs besidesoffering them various engagement programs that enhance customer experience like reward points, discount vouchers on shopping etc.
What data Telematics solution collects?
To scratch beneath the surface, a mobile based Telematics app not only tracks information like geo-spatial data that provides information on vehicle movement,but it also uses various sensors installed in smartphones such as accelerometerto track acceleration, gyroscopeto trackthe rate of rotation across the three sensor axes, magnetometer to track the ambient magnetic fields across three axes and host of other sensorsto tracka variety of useful information that help to study the behavior of a driver.Behavior based assessmentthrows up finer nuances of a driver’s driving characteristics or his or her driving style which determine how safe or risky a driver is on the road.Knowledge of these nuances act as a win-win for both the Auto Insurers and the Insureds. While for Auto Insurers, it could lead to bettering the loss ratios with reduction in occurrence and severity of the accident or crash events, with real accurate timelytelematics data, this also ensures improvement in a driver’s behavior leading to safe driving besides saving on premium costs.
When a vehicle is on the road, there are a variety of risks,gleaning the data of whichthrows many interesting insights which can be used not only for rewarding safe drivers but also driver coaching
- Speeding –As perNHTSA (National Highway Traffic Safety Administration), for more than two decades, speeding has been the cause of approximately one-third of all motor vehicle fatalities and in 2020, it was a contributing factor in 29% of all traffic fatalities. While such aggressive speeding may be characterized by say traffic congestion if one wants to avoid running late, contextualizing speeding may throw reasonable predictions on what led to it. Data from telematics may throw useful information like if speed was within the posted speed limit given other ambient conditions being normal like fewer vehicles on the road, good roadconditions, normal weather etc.
- Cornering– Cornering,also referred as lateral acceleration, is a measure of centripetal force applied when a vehicle is moving on a curved road or is taking a right or a left turn.A sharp curvature needs slowing of the speed so that a limited friction provides appropriate acceleration to take a smooth turn.Too sharp a turn may lead, in extreme instances, to overturning of the vehicle. Apart from additional wear and tear that the vehicle may undergo, telematics data related to cornering provides useful information of a driver’s behavior on the road.
- Braking – Telematics data may give rich insights on harsh Braking where and when it took place.A hard brake puts brake pads & other brake components into great stress and results in early wear and tear of these components.A hard braking behavior also indicates high risk of a driver losing control of the vehicle that may lead to an unfortunate outcome.
- Acceleration– A hard acceleration apart from being a fuel guzzler, also leads to wearing off of the engine and transmission systems including being riskier to the passengers leading to crash events.The telematics data may not only offer vehicle’s acceleration at say one to two second intervals,but contextualization built into the application, may also give useful insights such as the probable reasons that may have led to hard acceleration.It is possible that a driver might have been trying to avoid hitting an object or from being hit by an object.
- Idle time – Idle time refers to the time-period when a vehicle’s engine is running but vehicle is stationary without moving. Whilst certain occasions may warrant idling a vehicle like stop signs, traffic, any incident enroute or when a driver is on a long haul on a highway, idling the vehicle too often leads to rapid fuel burn as well as increase in maintenance and running costs over short to long term. A Telematics application may not only send alerts to user driver to stop the engine, with intelligent contextualization built into it,but data from telematics can also offer rich insights on the idling time over the total trip duration which can help in driver coaching.
A typical Telematics application may use hard metrics like the ones above andmay also overlay them with contextual information like weather pattern, traffic / traffic congestion, road characteristics, accident hotspots etc. to determine the driving pattern of a driver and ultimatelyquantifying the pattern in the form of a score.The score also acts a guardrail for driver coaching to better driving skills.
One of the challenges that confront Insurers, is the ability to make reasonable predictions of a risk materializing. By gaining a better visibilityof a fine-grained view of driving behavior of the driver along with contextual data, underwriters& risk professionalscan better price their customers. With data on several factors determining driving behavior, they can get rich insights on what to consider and what not to, to arrive at a suitable price which is more personalized per customer along with added benefits of reduced frequency and severity of claims.Many such applications also come with plug and play interface enabling integration with Auto Insurers’ IT systems.
Conclusion
Telematics as a data driven digital offering helps in informed decision making, improves pricing accuracy, enhances driver safety and reduces claim costs. As traffic resumes to pre-pandemic levels coupled with renewal rates set to rise to 8.4% across US in 2023 according to a recent report from Value Penguin, a usage-based Insurance product like Telematics offers a great value proposition to Auto-Insurers and customers alike.
