One day in 2030, Scott drove to his destination in a car with automatic driving function. He switched the driving mode to “manual” on a whim. At the same time, the digital assistant in the car planned a recommended route for him and synchronized the information to the insurance company. Through big data, artificial intelligence and other technologies, the latter analyzed and optimized the route, and fed back another route with low accident rate and the corresponding premium price to Scott.
Finally, Scott chose this route with low accident rate and low premium. But when he reached his destination and drove into the parking lot, he accidentally hit the sign railing. At this time, the built-in digital assistant of the car starts to automatically diagnose the damage degree of the car and prompt Scott to shoot and upload the damaged part. After the photo is sent back, the digital assistant prompts that the claim has been approved, and a UAV is on the way to the scene for investigation in the future. If the car is still driveable, Scott will be guided to a nearby repair shop for repair.
This brain hole is the story described by McKinsey in insurance 2030: how artificial intelligence will rewrite the insurance industry. Although you think the above plot will only appear in science fiction movies, in fact, these technologies already exist and have been successfully applied on a small scale. At this stage, emerging technologies such as big data, artificial intelligence, blockchain and Internet of things have been widely used in product innovation and service innovation, providing the possibility of disruptive change for the traditional insurance industry.
Based on AI, big data and other technologies, it can launch dynamic behavior pricing for insurers, that is, adjust the premium in real time based on the driver’s behavior habits. Through vehicle sensor and AI technology, real-time record the vehicle driving status, vehicle frequency, mileage, driver’s driving habits, route selection, etc., combined with the insurer’s basic personal information (age, gender, occupation, residence, physical condition, etc.), accident records, violation records and other multidimensional data, build a customer portrait through machine learning, and formulate personalized Differentiated dynamic pricing. For example, insurers with safe driving habits and compliance with traffic regulations can get lower premiums; Insurers of dangerous driving can also reduce the premium by improving driving habits.
In addition, the choice of premium products is also more diversified. Insurers can make personalized choices according to their own needs and customize insurance products that match their own living habits and travel modes. Micro payment will also become a trend under the empowerment of technology. For example, shared cars are charged according to kilometers or times, and automobile insurance can also be priced and charged according to the road conditions, mileage, driver’s personal information and other data of a single trip.
Digital assistants are already common in daily life, such as Apple’s Siri and Microsoft’s Cortana. The built-in digital assistant in the car will also become a development trend. The digital assistant based on artificial intelligence will gradually replace manual in insurance agency, and provide more personalized customized services for drivers through the combined application of efficient information and Internet of things, including recommending insurance products, optimizing driving routes, providing automatic claim settlement, accident after-sales and other services.
In addition, through the continuous development of in-depth learning technology, digital assistants are expected to have the role attributes of intelligent customer service and Intelligent Consultant. Based on natural language processing, speech recognition and other technologies, realize effective interaction with drivers, quickly answer questions and improve customer experience.
Based on AI technology, it can realize the on-the-spot investigation of vehicle damage and casualties caused by vehicle accidents, and provide rescue information for medical teams. This is to analyze the collision pulses recorded by vehicle telematics equipment and virtual sensors through machine learning algorithm and ADR (accident detection and response) technology, timely send fine real-time personal injury reports to first responders, and provide key details required for rescue.
In addition, the digital assistant configured in the vehicle can monitor the driving status and vehicle running status (tires, fuel consumption, temperature, engine, etc.) in real time. Combined with external factors such as weather and road conditions, the AI risk control system can troubleshoot abnormal situations and realize timely early warning to drivers. In addition, the development and optimization of fatigue driving early warning system can comprehensively reduce the probability of accidents from the source, protect the interests of insurers and insurance companies and effectively prevent risks.
With the application of artificial intelligence, big data, Internet of things and other technologies in the insurance industry, insurance has changed from the previous “detection and maintenance” mode to the “prediction and prevention” mode. Digital solutions provide great opportunities for auto insurance companies to reduce claim payment and meet emerging needs. Grasping the technology and trend of artificial intelligence, constantly launching new products and services, improving customer experience and meeting personalized customer needs are the foothold for the innovation and development of the insurance industry in the future.