Internet of Things (IoT) is a network of connected physical objects embedded with sensors. IoT allows these devices to communicate, analyze and share data about the physical world around us via networks and cloud-based software platforms.
In the current scenario, IoT is one of the most important phenomena revolutionizing the technological and business spheres. Several industries such as Agriculture, Healthcare, Retail, Transportation, Energy, and manufacturing are leveraging IoT to solve long-standing industry-wide challenges and thus transforming the way they function. For example, in Manufacturing, sensors placed in the various equipment collecting data about their performance are enabling pre-emptive maintenance and providing insights to improve overall efficiency. In Retail, “things” such as RFID inventory tracking chips, in-store infrared foot-traffic counters, digital signage, a kiosk, or even a customer’s mobile device is enabling retailers to provide location-specific customer engagement, in-store energy optimization, real-time inventory replenishment, etc.
The Insurance industry, on the other hand, has been rather sluggish by virtue of its size and inherent traditional nature. They cannot, however, afford to continue a wait-and-watch attitude towards IoT. Insurance is, interestingly, one of the industries that are bound to be most impacted by various technological leaps that are being made. IoT, blockchain, Big Data are all expected to push Insurance to evolve into a different beast altogether, including a shift from restitution to prevention.
Primary IoT Use-cases That Insurers Have Adopted
Connected cars: Many auto insurers have been collecting and analyzing data from sensors in cars to track drivers’ behaviors real-time and thus providing usage-based insurance (UBI).
Connected homes: Sensors in homes that can detect smoke and water levels can lower frequency and severity of damages by automatically sending out messages to the homeowners, fire department or other maintenance service providers, in any event, requiring attention. Certain connected doorbells are capable of preventing burglaries, while other devices provide remote home surveillance.
Connected people: Wearable fitness trackers provide data to insurers that help them underwrite their health insurances better and advice preventive care. These trackers also enable the wearers to lead a healthier lifestyle, thus reducing their premiums and frequency and severity for the insurers.
Though some of the content can be applicable to other Lines of Business, in this article, I shall focus on leveraging IoT in Auto Insurance. Please note that the steps and assumptions of actions taken are based on a specific case study. The specificities may vary for other Insurance providers based on existing policies, location, technological and data maturity, etc. The intention is to provide a detailed example. This study can be replicated for other providers and recommendations can be made accordingly.
IoT has the potential to impact almost every facet of Auto Insurance. The preventive and underwriting areas have already received sufficient focus. Data from sensors in the cars can help understand and analyze driver behavior and thus profile risky driving behavior. This has enabled a much-appreciated shift from usage-based underwriting from the traditional demographic-based underwriting. Here, it is important to point out that just driving behavior metrics such as speed and number of sudden breaks is not sufficient to assign a risk profile to the driver. These metrics should be analyzed in the context of the location, usual routes were taken, average driving behavior in the area, etc. to truly judge one’s driving behavior. This requires assimilation of multiple data sources.
Claims Management
The insurance buyer demographic has shifted to one that prefers everything here and now. They prefer dealing with things remotely from the comfort of their offices and consider the need of heavy paperwork and human presence primitive. Application of IoT in the improvement of Claims management is at a very nascent stage but could have a tremendous impact on the claim handling turn-around time, accuracy of investigation and customer satisfaction.
1.Accident/Event and FNOL
2.Workshop Assignment
3.Investigation and Fraud detection
4.Miscellaneous
Document maintenance: Since a lot of hard-copy of documents are still used in Insurance, RFID can be used for document tagging and maintenance.
Once the repair has been completed, the various sensors of the car can do a self-check to ensure the parts they are connected are in good working condition.
Feedback: The mobile app will be a much more effective method of collecting feedback from the customers than paper forms and telephone calls.
The Wealth of Data Generated
As discussed above, underwriting of policies will improve drastically even for 1st-time buyers.
Efficient visualization and automated insight generation to provide reliable and concise.information about their driving behavior to the drivers themselves will help them become safer drivers.
IoT-based analytics can be used to predict future events such as:
Major weather patterns – Based on this Insurance companies can prepare for various catastrophes and improve locality-based underwriting.
The data will enable Insurance companies to identify accident-prone weather, roads, driving behavior and combinations thereof. The Insurer can then advise the driver accordingly. For example, the insurer may inform the driver that he ought to avoid a particular route in a particular kind of weather since accident probability of that combination would be 30%.
With all the additional data, various important profiles and segments may emerge that will form the foundation for propensity estimation and developing effective targeting strategies.
Criticality Of Analytics In Utilizing IoT Data
Analytics is a critical component of using IoT data to ensure maximum benefi
Policy buyer level information can be used to evaluate the risk associated with the buyer and legitimacy of claims
Analyzing the population as such can identify customer segments and determine their needs. Coupled with efficient visualization and automated insight generation, insurers will be able to promptly determine any concern and the cause for the same
The data will enable Insurance companies to identify accident-prone weather, roads, driving behavior and combinations thereof. The Insurer can then advise the driver accordingly. For example, the insurer may inform the driver that he ought to avoid a specific route in a particular kind of weather since accident probability of that combination would be 30%.
Analysts can identify significant trends and patterns from data accumulated over a period. This can be incorporated into statistical models that can predict the future for insurers
Based on expected weather patterns and catastrophes, insurance companies can prepare accordingly and improve locality-based underwriting.
The various policy changes and tests by the insurance companies to deal with changes in the market will also be reflected in the IoT data. This information can be used to determine the optimal action to be taken when an immediate or expected issue needs to be mitigated
IoT Implementation For Insurance Companies
In an ideal world, any kind of transformation would be a series of steps with minimal overlap between each other. This is, however, not reality. Insurance companies have assumed that they cannot move on to integrating IoT in claims management until the current data and processes have all been completely digitized. One would like to imagine that given the amount of time and money that has gone into digitization, all organizations above at least mid-size would have all their data digitized and well-synchronized. The reality is, however, a combination of traditional and digitized systems. While a complete online data mart would have been the ideal scenario for IoT integration and to derive the best from it, IoT can also be integrated into such combination systems and still add substantial value by syncing with whatever data is online and clean.
Analytically sound database structure and ease of analysis are critical while setting up IoT system. The database design should be in such a way that all the required information should be stored without error and all current and future analysis can be carried out with relative ease. This can be done only under the supervision of able and experienced analytics practitioners.
IoT for usage-based insurance is no longer a choice for providers. If they do not implement it right away, they will be left with a policy portfolio of higher risk drivers.
Managing voluminous multisource data and organizing the technological resources.
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