Internet of Things is coming to an Insurance business near you
IoT is fastly emerging in the Insurance Industry as a technology that will change the way we generate, assess, and deliver insurance products and services.
We all know insurance companies make money by charging customers for insurance coverage. But how is the price of the insurance premium actually calculated? Traditionally, domain experts (the Underwriters) would use historical data of similar customers and their policies to define a price for the potential risks. With the rise of Data Science, the insurance risk is now calculated using Machine Learning Pricing models that support Underwriters’ decisions by detecting complex patterns in historical customer data.
The underwriter’s contribution is still crucial. They bring domain knowledge and understanding of the customer, but things are starting to change; Insurers are rethinking how to improve the customer relationship and the risk assessment of each customer.
Typically there are only two points of contact between the insurer and the customer; first when the terms are agreed and the customer buys the product, and second during either the renewal or cancellation process — unless there is a claim during the policy time. Insurers have little contact with the people they serve. Limited exposure to the customer over time makes it difficult for insurance companies to build positive customer relationships.
Risk assessment is another area for improvement. An insurance policy is priced based on the level of risk the policyholder represents. However, the data available to evaluate this risk is often limited and it doesn’t always measure the risk of an individual based on his or her own behaviours. Instead, the risk is calculated based on biographical information like age, education, address and form of employment. These data points are able to support good risk evaluation to an extent, but they might promote bias in decision making since they evaluate the risk of an individual based on ‘similar customers’.
A new technology on the horizon could help. This new tech is making its way into our lives in small but meaningful ways with good results for businesses which could help address the customer relationship and risk assessment issues for the insurance industry. That technology is called the Internet of Things (IoT).
The Internet of Things (IoT)
IoT has been adopted in many industries and markets. According to ZDNet “The Internet of Things, or IoT, refers to the billions of physical devices around the world that are now connected to the internet, all collecting and sharing data.” These devices are used in our homes and in our cars to collect personal details and information about what we do and where we go.
Some insurance companies have spotted IoT’s potential. According to a survey, while 70% of the insurers think IoT data could be very important to the organisation’s strategy, only 5% said they were actually using it in their analytics.
The data collated can teach businesses valuable details about their customers by studying patterns in real personal data. The data can provide insurance businesses, with the right models and right capabilities, actual insights into what new products and services their customer base really need.
As an example, the below sketch maps the types of data that could be collected from an IoT insured car. The data can be grouped and cleaned in real-time to provide clear indications and warnings a customer might need for car-related support services.
The introduction of such data brings a new level of customer interaction and experience with the potential to reduce churn and provide more competitive insurance premiums. So why is this revolution happening now?
Some recent technological developments have meant that IoT is now a real consideration and within reach for most insurance companies keen to use a more extensive dataset in which to ascertain the risk calculation of potential customers.
One such development is the growth of big data tools, cloud providers, and edge computing. These tools allow businesses to process huge amounts of data collected from IoT sensors in real-time. Also, because of the high demand for sensors and microcontrollers, as we can observe in the below graph, the cost of IoT ownership has decreased and the processing power has increased and so it is no longer the bottleneck of IoT solutions.
According to Forbes, there has been a 27% increase in IoT startups that develop smart devices. So how can insurance companies benefit from adopting IoT solutions more widely?
With IoT, new insurance services and products could be developed. For example, in auto insurance, a new service might be able to predict when a car needs maintenance and be able to recommend specific types of car services near to the customer’s location.
IoT could also help insurance companies cross-sell to customers. With more data about customers and their behaviours, there may be scope to suggest new customised products, make recommendations for each customer and create a network of partners such as car repair centres or MoT specialists, where a commission-based business model may well be explored.
According to the FBI, US Insurance Companies generate $1 trillion in revenue and almost $80 billion is spent by insurers on fraudulent claims, which in turn increases the price of premiums. One way to tackle this is to use better fraud detection models. Insurers could fit cars with devices that could capture ‘on the go’ driver behaviour. This will not only protect the Insurance companies by penalising customer’s driving choices that might be risky but also reward good ‘on the road’ behaviour.
Other types of Insurance products could also be improved by detecting a potential cause of a future claim early and proceed with predictive maintenance, for instance, detecting a leaking pipe and immediately notify the customer and send a technician to fix it. It’s much cheaper to repair smaller issues as they occur than all the damage caused by the late problem detection.
Challenges
IoT devices represent opportunity but also challenges. One challenge is to convince customers to give away their personal data. According to a survey by Deloitte, a price discount on the policy is not enough to tempt 75% of the customers. A bigger effort may need to convince customers to ‘opt in’ to their personal data being used in this way.
Legacy IT systems may also present a problem; data management and warehouse platforms may need to be redesigned to harness the full potential of the IoT real-time data. Many insurance companies may be apprehensive about introducing new technologies which are to some degree untested as of yet and require a significant investment.
People in the industry may also present a challenge. There has also been some industry debate as to whether the use of IoT may reduce the need for the specialist skills of some staff in the insurance sector. As such, some teams may seek to challenge and question the benefits and the introduction of the technology.
Privacy and security issues are also major concerns. IoT technology deals with highly sensitive and very personal information about customers; where they go, when and how. This type of detail about an individual comes with an unrivalled level of personal sensitivity about what a business could do with it and shows no signs of abating.
Final Notes
Overall, more specialist customer data, such as sensory data from IoT devices, can help businesses and in particular, insurance companies build better insights about their customers to potentially create better services. But it takes time and effort to weigh up all the factors and get started.
For insurers, there are some very real opportunities to rethink and reshape their customer relationships and to redefine how they evaluate risk and price their premiums. IoT is likely to bring about some big changes to the industry, the big question is when.
