5 minute read 2 Oct 2018
Man and woman looking at a laptop screen

How IoT data can impact insurance and the wider financial sector

By

Michal Krzysztof Rutkowski

EY EMEIA Advisory IoT Strategy Senior

Internet of things systems thinker. Economics adorer. Music lover. Tech geek. TV art admirer. Engineer and strategist.

5 minute read 2 Oct 2018

The near-instant availability of IoT data could overturn traditional forecasting and decision-making processes.

F or years, in order to manage uncertainty and risk, insurance companies have made decisions based on historical data, inferring the likelihood of risk based on previous policyholders, their behavior and claims.

But the massive increase of Internet of Things (IoT) data, available in near real-time, could radically change this model. IoT sensors can provide insurers with up-to-the-minute data about almost anything: individual driving styles, the condition of buildings and our lifestyle habits. This will have a far-reaching impact.

IoT could become a destabilizing factor for the more traditional elements of insurance and the wider financial sector: undermining the current risk management models and the balance between information sharing and information asymmetry, which will have a major impact on operating models and decision-making mechanisms. And companies that do not embrace this new paradigm will struggle and ultimately fail.

Here are some examples.

Usage-based insurance

The popularization of IoT devices has enabled the introduction of a new type of car insurance known as usage-based insurance (UBI), pay as you drive (PAYD) or pay how you drive (PHYD). The condition for obtaining such insurance is the installation of a device capable of monitoring the geographical location of a vehicle, both on the move and when at a standstill.

In UBI, the final cost depends upon the type of vehicle used, measured against time, distance, behavior and place. This differs from traditional insurance, which attempts to identify and reward safe drivers, giving them lower premiums and a no-claims bonus. The statistics about past events act as a signpost for what insurers believe will happen in the future – most traditional institutions from the financial sector, in particular insurance providers, build their decision models on this basis. If all entities have similar historical data about past claims, they can set a safe risk margin and, on this basis, determine the insurance rate that gives them profit on their operations.

The UBI insurer will be able to offer more and more favorable insurance rates, which will further accelerate the flow of customers between organizations.

However, if drivers with UBI insurance generate statistically less damage, the expected value of damage through UBI will decrease, whereas with traditional insurance it will increase (assuming that the safest drivers, those not involved in accidents, will move to UBI). The UBI insurer will be able to offer more and more favorable insurance rates, which will further accelerate the flow of customers between organizations. The result will be an effect on the statistical distribution of losses throughout the market, i.e., a tendency to further increase the deepening market segmentation.

Buildings insurance and mortgages

The calculation of both mortgages and buildings insurance includes factors such as local transport, crime rates and the quality of neighbourhood schools – but the quality of the building itself is more difficult to assess. This is intensified in cities such as Tokyo, where the frequency of earthquakes means the construction of tall buildings cannot even get funding. The result is that the city grows in area rather than height which impacts its overall architectural landscape.

Both financing and insurance companies that have access to this will be able to look at more than just historical data, and focus their investments and policies on more resilient buildings.

But IoT sensors can now constantly monitor key parameters such as vibration and changing humidity in buildings to determine how they behave during minor earthquakes. This provides near-real-time data about the fabric of the building itself. Both financing and insurance companies that have access to this will be able to look at more than just historical data, and focus their investments and policies on more resilient buildings.

Health insurance

Health insurance plans are usually based on lifestyle factors and life expectancy calculations based on medical history. But IoT data can make health assessments much more detailed at the individual level. Data could come from wearable and mobile devices that track physical activity and heart rate, apps that help with taking routine medication and ECG monitors, for example. This data could be further segmented by an individual’s life stage, for example whether they are working or retired. This can give health care companies a much better perspective on real health risks and lead to more dynamic changes in individual policies.

Conclusion

Two factors are undeniable here:

  • The insurance market will be disrupted by a massive deployment of IoT, changing the quantity and quality of available data, which will destabilize the balance between information sharing and information asymmetry.
  • There will be a significant delay between the adaptation of risk management models to the changes in the market. IoT enables insurers to gather data about behavior in almost real time.

The combination of IoT data sources, plus Blockchain to authenticate and validate data, fast connectivity and artificial intelligence will enable innovative companies to collect verified data, transmit it into their systems and then automatically insert it into their risk calculation models.

In comparison, traditional insurers have to wait to gather sufficient and meaningful statistical data to enable them to assess the risk of non-monitored customers or assets. The economic effectiveness of financial institutions will be directly linked to the length of this delay – failing to include real-time data into statistical models may result in losses or even collapse for the laggards.

However, many companies see IoT mostly from the perspective of “toys” – for example implementing smart watches and other mobile devices with capabilities such as near-field communication (NFC) to enable mobile payments.

IoT solutions that do not change information asymmetry can indeed be treated as mere curiosities – but those that do are in fact powerful tools that could have a significant impact on companies’ entire business and operating model.

Summary

IoT sensors can provide insurers with up-to-the-minute data about almost anything: individual driving styles, the condition of buildings and our lifestyle habits. This will have a far-reaching impact.

About this article

By

Michal Krzysztof Rutkowski

EY EMEIA Advisory IoT Strategy Senior

Internet of things systems thinker. Economics adorer. Music lover. Tech geek. TV art admirer. Engineer and strategist.