This is the third in the IoT Digital Transformation posts. In this blog we focus on how IoT is transforming the Insurance industry. Part 1 focused on the impact of IoT DX for the customer experience. Part 2 focused on how IoT DX is transforming field service.
Now, the number of connected assets is exploding. By most estimates there will be tens of billions of connected assets by 2020.
So here is the interesting part.
These connected assets are associated with the properties belonging to the insured: homes, cars, buildings, fields, equipment, and appliances – to name a few. Furthermore, with wearables and other connected health devices, life and health insurance can also leverage connected devices. Connectivity can also address the liability or casualities of the insured. Connected cars, homes, and other insured properties are becoming increasingly proactively autonomous and intelligent and thus can minimize their exposure to loss. Established as well as emerging smaller insurance companies can now provide innovative products and services leveraging this pervasive connectivity.
It is interesting to note that a relatively old and well established industry sector – namely Insurance – is being challenged and disrupted by the emergence of digitization – especially Internet of Things (IoT). Recently I visited an insurance company that had an IoT innovation center! Not bad for an industry that is several hundred years old.
Evolving cyber and physical connectivity digital transformation (aka IoT DX) provides innovation opportunities in all industries – especially Insurance.
In fact other digitization technologies are also impacting the more technologically conservative insurance industry. It started with insurance companies providing competitive insurance products over the internet. Now DX disruption is coming through digital technologies such as social, mobile and applications as well as services on the Cloud. But more importantly two other digitization trends are digitally transforming the insurance industry. One is predictive and machine learning (aka adaptive) analytics - especially with Big Data. The other is the digitization and automation of end-to-end processes orchestrating the interaction of customers, their devices, with the rest of the insurance enterprise: realizing efficiencies in processing claims while optimizing the customer experience.
There are many dimensions to the IoT for Insurance disruption. In this post we focus on three of the most important areas of the impact of IoT for Insurance. These are not orthogonal and there are definitely overlaps.
- IoT for Mitigating Insurance Risk: Insurance is about mitigating risk. With the enormous amount of data being aggregated from a plethora of devices as well as the movement and habit of the customers, insurance companies have now a much better understanding of:
- The asset being insured and its characteristics: for connected cars, this includes the sensors for vehicle status
- The user and usage of the asset: for connected cars, through GPS information, trip reports, and driving data
It is the combined aggregation of the Thing Data and the Consumer Data that will allow the Insurance companies gain insight, especially in mitigating and reducing risk. This is very much the realm of artificial intelligence (AI) as applied to insurance risk assessment. Now the “risk” assessment policy could be captured both through Big Data discovery as well as business rules that come from the expertise of underwriters, or a combination. This data could be real-time or near real-time and the insurance could even be potentially adjusted based on an individual’s or specific asset’s usage or behavior. Connectivity allows insurance companies offer or innovate with new products: such as insurance of assets or people for specific periods of time or dynamic behavior rewarding insurance. Which brings us to the second advantage …
- IoT for New Business Models: Usage-Based Insurance is the best and most known example of this, especially for automobile insurance. For instance through connected vehicles or third party devices that could plug into the vehicle, the insurance company can monitor driving habits to score the driver and accordingly price the insurance policy - for instance providing discounts for good driving behaviors. Also note that usage-based can be applied to any type of device for instance connected appliances or connected tools. Thus the intelligent models can be leveraged to decide and adjust the insurance rates, dynamically.
- Thing Data predictive as well as machine learning analytics is essential in deciding exactly what the rates need to be and why.
- Equally important are the policy and claims processing innovation that could be achieved through automating and streamlining end-to-end dynamic cases involving the device, the customer and the various business units within the Insurance enterprise. For example, with IoT First Notice of Loss (FNOL) could instantiate a dynamic case to orchestrate the claim processing, connecting the device, the customer and the insurer through end-to-end automated processes that optimize the overall customer experience (faster, better for the insured - and of course less error prone and cheaper for the insurance).
Therefore new business models can also impact the price of the policy as well as the processing of the claims especially through prescriptive maintenance, as discuss in the third advantage …
- Reducing Loss - IoT for Preventive and Prescriptive Maintenance: Connectivity for devices or humans also provides opportunities to avoid loss predictively before it happens. This is of course a win both for the insured as well as the Insurance company. If the breakdown of the insured device asset or whatever the asset is monitoring (house, person, appliance, car, etc.) could be avoided that avoids paying the large claims through prevention. This is very much the realm of digital prescriptive maintenance as applied to insurance. Here again the two fundamental technologies come into play.
- One is AI for the next best action, as we discussed in the two previous posts. The enormous amount of data being gathered from devices both on the device as well as the usage of the device is a treasure trough of information that could be mined and acted upon.
- The “acting” is actually in the context of end-to-end dynamic cases: for instance sending a field technician to respond to or fix a connected or sensed water leakage system – hopefully before it happens or at least minimizing the loss. All the intelligent orchestration and automation of tasks from the connected asset to the service to the claims processes by the insurance company is optimized. When it comes to prevention (especially for loss) IoT with AI driving dynamic cases provides the added advantage of protection against theft, damage, faster communication in emergencies, and efficient processing of claims.
In part 4 we will be focusing on another established industry sector being challenged by IoT DX with a digital transformation platform, Pega: namely Financial Services.