This article was originally authored by Toby Blyth. For further details or assistance, please reach out to Michael Bracken.
In brief - With the advent of insurance technology, what can insurers, assessors and lawyers expect?
Telematics involves devices or products that combine communication and data to provide a service. When applied to cars, telematics allows real-time monitoring of data such as location, speed and use, which is communicated to third-parties such as manufacturers or insurers.
Those third-parties can then more accurately price risk, by rewarding drivers with lower premiums where their data indicates safe driving practices, or by offering a policy that charges premiums on a per kilometre basis.
Increasing data integration brings efficiencies to car insurance industry
Shoshana Zuboff notes in The Age of Surveillance Capitalism that the process of integrating game mechanism (gamification) into geolocation apps is much more than a game. They are precursors to a world where hard geographic reality is overlain with a soft thick virtual embedded information layer that integrates the real environment with the digital environment. Telematics highlight the emergence of a world where data is automatically captured and communicated to insurers with real effect.
App and internet based maps and traffic systems have already integrated a thin virtual layer of data through marking static physical features, static road traffic or architecture (eg, speed limits and rights of way) with a relatively thick data layer relating to traffic flows based on a variety of networked data points.
Parallel with this is a state-owned public layer of data, comprising technologies such as traffic monitoring and electromagnetic switching traffic control architecture.
Newer cars can add to this data layer by integrating via base stations and the mobile communications network into the system.
As cars become more and more part of the Internet of Things, and the systems are married together, it will be possible to determine:
- the exact location of a car accident leading to property damage (via geo-positioning, signals in the embedded architecture, and signals built into the car indicating the location of damage)
- the speed and direction with which the cars were travelling
- the position of each car in relation to the existing rules network
- how many people were in the car, and
- if a driver was intoxicated (via breathalyser enabled disable switches)
How might telematics affect third party property policies and knock-for-knock agreements between insurers?
Motor vehicle third party property policies indemnify drivers for the damage caused to other cars as a result of the insured's negligence.
Where an insurer has issued a first party property damage policy, that insurer will first pay out the damage to the insured's vehicle, and then locate any other insured driver whose fault led to the collision.
Traditionally, the insurer would then sue the at fault driver in the insured's driver's name via subrogation to recover the payment the insurer had made to its insured. That obviously only worked financially where the at fault driver has third party property damage insurance.
Given the costly and friction heavy processes involved in litigating, insurers developed knock-for-knock agreements, which essentially allowed each insurer to predetermine how liabilities that its insured drivers incurred to third party property holders were settled, and then netted off pursuant to a clearing arrangement.
The developing network architecture will very soon allow an insurer to dispense with much of the expensive parts of the knock-for-knock agreements (ie, claims officers and lawyers) by developing relatively simple algorithms that will operate via private block-chain or similar, that embeds certain prearranged rules to decide who pays whom, for example:
- if insured driver A is driving more than 10 kilometres over the speed limit and insured driver B is driving at or below the speed limit, then insurer A pays insurer B for the damage to B's vehicle
- if both cars are travelling over the speed limit, then the faster vehicle's insurer pays the other vehicle's insurer
- if insured vehicle A breached a relevant road rule and insured vehicle B did not, then insurer A pays insurer B and vice versa
The fact that these algorithms can be set out here in short order shows that it will not be difficult to develop such a system.
How will telematics affect insurers, assessors and lawyers?
As the insurers are merely agreeing as to how their subrogation rights will be exercised, competition issues do not arise. However, the networked algorithm based architecture dispenses with the human-controlled algorithm (embedded in a set of written rules) that knock-for-knock agreements currently utilise. Of further interest will be whether Australia introduces a prohibition on automated decision making without human recourse (see Article 21 of the GDPR already has).
Of course, another casualty of this process will be assessors, because vehicles' inbuilt damage monitoring will report to the insurer which parts of the vehicle need repair, and those repairs can be carried out by a mechanic in a similarly networked and paid for system.
The final loser in this scenario will be the lawyers who act for the insurers in litigating responsibility for motor vehicle accidents.
We recently presented on the topic of artificial intelligence and its impact on broking, underwriting, compliance and claims at our inaugural Insurance ThinkTank held in Sydney on Thursday 17 October. For more information, please contact Toby Blyth.
This is commentary published by Colin Biggers & Paisley for general information purposes only. This should not be relied on as specific advice. You should seek your own legal and other advice for any question, or for any specific situation or proposal, before making any final decision. The content also is subject to change. A person listed may not be admitted as a lawyer in all States and Territories. © Colin Biggers & Paisley, Australia 2023.