It's been more than a year since ChatGPT was launched, and looking back on 2023, the AI industry has caused a huge shock around the world, with all walks of life trying to introduce AI into business practices, including the insurance industry at home and abroad. For example, Simplifai, an automation solution provider, has launched lnsuranceGPT, and many domestic insurance companies such as Ping An Insurance of China, Sunshine Insurance, and Pacific Insurance have also continuously developed big data models for automated insurance sales, underwriting, and claims, with the intention of achieving round-the-clock customer service in the insurance industry and improving the efficiency and accuracy of insurance application and payment.
The introduction of artificial intelligence in the insurance industry is by no means to catch up with the trend, insurance is very similar to the underlying logic of artificial intelligence models, insurance follows the law of large numbers and is priced based on insurance actuarial models, and artificial intelligence also requires big data and models to be continuously iteratively upgraded. The similarity between the two makes insurance a natural fit to introduce AI-enabled business processes. In addition, the digital transformation of the insurance industry in mainland China has been developing for many years, and 2023 will only accelerate the commercialization of AI large models based on the explosion of ChatGPT. For example, this year, CPIC released three innovative scientific and technological achievements, namely digital employees, black light factories, and decision-making centers, that is, robots imitate human work behaviors and work 24 hours a day, and can currently operate more than 440 RPA products at the same time, covering almost all business lines of property insurance, and launched products such as "pre-entry of auto insurance loss estimates", "no image quality inspection of personal injuries", and "automatic entry of insurance policies by robots".
It can be seen that the digital transformation of insurance has become the trend of the times, and more and more positions will be completed by digital employees. However, we still need to pay attention to the resulting balance between efficiency, quality and cost. The introduction of AI in insurance will undoubtedly improve service response times, efficiently handle high volumes of customer interactions, and increase productivity. In addition, the customer portrait generated by big data analysis can gain insight into customer behavior preferences to a certain extent and meet the personalized needs of customers. In addition, for positions with low technical difficulty and high repetition such as customer service, the near-zero replication cost of digital employees can create large-scale labor in batches, and the cost advantage is significant.
However, the excessive pursuit of efficiency will make the problem of insurance service quality more and more obvious, insurance claims are highly professional and complex work, if the AI model has serious defects, it will greatly affect the results of insurance claims, making the fundamental logic of "insurance surname Bao" inverted. For example, UnitedHealthcare, a U.S. health insurance company, has repeatedly incorrectly overturned doctors' diagnoses based on AI algorithms and refused to pay medical benefits to the insured, resulting in additional consumption of the insured's living savings. The introduction of AI will cause insurance to lose its protection function and deviate from the essence of insurance, which will seriously lead to a crisis of trust in insurance and hinder the development of the industry. This is also where the future digital development of insurance needs to be vigilant, strengthen the training of models, retain manual intervention for highly professional positions, and achieve insurance business innovation and high-quality development.