+91 96558 14047 (India)
+65 8237 9397 (Singapore)
+27 11 886 1707 (South Africa)
+61 8 4634 1736 (Australia)
+44 (0) 208 123 3459 (UK)
+1 315 532 7622 (USA)
Email: [email protected]
Artificial Intelligence is one of the emerging technologies that is expected to disrupt the entire insurance industry in a very big way. Because the insurance industry is one that is dominated by a few major players with products that have not changed substantially over the years, most venture capitalists consider it as an industry that is perfect for disruption. A 2015 KPMG report predicts that the arrival of driverless technology will bring in much safer and will shrink the auto insurance industry by a massive 60% over the next 25 years.
There are three key trends that insurers should know about Artificial Intelligence (AI). In the first of three blogs on this topic, we will look at: Behavioural Policy Pricing – where the use of IoT sensors provide personalised data to insurers allowing for a more accurate and personalised risk assessment.
Current AI application trends in insurance:
Behavioural premium pricing: IoT sensors shift from an alternate source of data to the primary source of data
Data generated through IoT sensors provides rich opportunity for insurers to personalise insurance covers. Here are three ways by which they do so:
The disruption that IoT causes in the insurance sector is similar to the disruption being caused in the finance domain by data science. It moves data in operations from an alternate source to the prime source of data for processing and decision making.
In the past, financial models were primarily based on carrying out statistical sampling of previous outcomes in order to forecast future outcomes. Insurance carriers depended on the risk pools that were constructed using processes of statistical sampling. But in today’s age, data science has brought in sweeping changes and advantages to these processes. Data science provides projections based on actual events in real time by utilising large datasets rather than samples. The use of IoT sensors in insurance also allows the pricing of insurance covers more accurately by basing them on the risk data of the individual concerned rather than samples of data from large groups.
An example to demonstrate this, is available in the domain of Usage Based Insurance (UBI) or pay-per-mile insurance. Here, telematics sensors that are fitted to the asset (an automobile) monitor the usage of the vehicle in real time and provide the data to the insurer. This means that safe drivers – identified by an analysis of the data provided by the connected telematics device, will need to pay less for their policy covers. These policy holders no longer pay for the risk profile of an entire pool but only for the risk based on their own driving habits. The only change that this insurance entails for customers are the installation of a telematics sensor in the automobile and also, being conscious of the way the vehicle is being driven and used.
Ringing in the changes
Along with any new technologies comes the possibility of new risks. While sensor data decreases many risks and are beneficial for insurers in many ways, they can also be vulnerable to hacking. And, as sensor based data is vulnerable to hacking, they can face penalties under data breach laws. Considering these emerging risks, insurers may be able to develop and underwrite new insurance covers – as is already being seen in the bull market for cyber insurance.
With specialised solutions for the insurance industry, Neutrinos is helping leading insurers take impactful digital transformation decisions. We would love to set up a discussion with you to hear your specific requirements. Talk to our experts today!