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The explosion of Big Data from various sources and the affordability of processing power are making it easier for insurers than ever before for companies to get “smart” about their customers. From more personalized customer service, HR recruiting without bias, speedy, low-cost invoice payment clearing, businesses are wielding data to innovate their business models. In order to stay competitive, insurers need to investigate the benefits and embrace the change.
First insurers need to embrace data; it is an asset. It is critical insurance providers recognize the value of data analytics and harness its insights into their internal practices and customer-facing policies. It is not just about analyzing data rather it is about deriving decision support within a contextual situation. For example, when a claims adjuster is in the middle of a transaction, the system may guide her to what the average of the last thousand decisions in this case were and predict what the next steps in that situation may be based on automatic inference—all in real time.
Emerging models in automotive, the public sector, service providers, and healthcare insurance are the first to effectively leverage connected sensors and data analytics to more accurately assess current and future risk and to provide protection services. Data-driven insurers are learning more about their customers and providing them with customized next-generation experiences.
IoT-based feedback can also modify user behavior. Car insurance companies for example can now analyze the driving habits of their individual policyholders, and make changes in real time such as alerting them to adjust certain behavior, such as aggressive acceleration. Insurers can even reward their sensible drivers with a better premium. In fact, some insurers provide other immediate rewards such as a free theater tickets or coffee or discounts on certain products. They have found the motivational effect is even higher than with a premium discount.
Get Smart with Automation
Artificial intelligence and Machine Learning are fast becoming the new normal, allowing insurers to monitor autonomous equipment, such as vehicles and homes, and make databased decisions in real time. This technology has huge potential to help insurers transition from financial loss compensators to risk prevention specialists through analyzing and applying uncovered customer behaviors into insurance offerings. The business advantages are both on the risk reduction as well as the fact that customers tend to pay more for these kinds of offerings.
Machine Learning allows insurers to reduce costs, improve efficiency, increase customer satisfaction, and gain competitive advantage. This opens the opportunity to simplify insurer employees’ everyday lives and to grow their business. Rather than programming software to accomplish a specific task, the machine uses Big Data and sophisticated algorithms to learn how to perform the task itself. For example, by reviewing and assessing large quantities of information in pictures, videos and voice conversations, insurers can better monitor and understand interactions between customers and sales agents. Additionally, the predictive analytics based on a customer-to-customer basis can optimize pricing on a case-by-case basis.
It’s a win-win, insurers are more informed about their customers and the reduced pricing greatly improves the overall customer experience. Finally, Machine Learning also gives insurers the competitive edge they need with product, service and process innovation.
Getting Ahead with Data
Instead of using approximate values such as postal codes, driving history or creditworthiness, predictive and preventative technologies allow the insurer to monitor the risk situation of individual customers and their insured possessions in real time. Increasingly insurers are becoming able to prevent house fires, flooding and provide greater security against criminal activity and other losses.