AI at Planners' Side... Transforming the Insurance Sales Field
The Age of AI in Insurance Sales: Productivity Competition Among Planners
AI Utilized in Tasks from Consultation to Policy Planning
"Caution Needed Against Excessive Dependence and Bias"
Generative artificial intelligence (AI) is rapidly permeating the insurance sales field. With AI being introduced for product recommendations, policy planning, and consultation training, AI-based sales support systems have emerged as a new source of competitiveness for insurance companies. However, concerns are also being raised that as planners increasingly rely on AI—such as accepting AI analysis results without sufficient verification—there may be a rise in judgment errors or cases of incomplete sales.
Generative AI is being utilized to enhance the productivity and consultation quality of designers. ChatGPT generated image
View original imageAccording to the insurance industry on June 11, competition among insurance companies in the field of AI is expanding into the area of supporting planners. There is a growing trend of integrating AI throughout the entire sales process, from personalized product recommendations and the generation of consultation scripts to policy planning and underwriting. This is driving improvements in both the productivity of planners and the quality of consultations.
Mirae Asset Life Insurance recently became the first in the industry to introduce a generative AI underwriting system based on a large language model (LLM). This system analyzes customers' health information and insurance claim histories to produce real-time underwriting results. Planners can simply enter a customer's medical treatment history or attach a diagnosis report to pre-check eligibility and conduct an underwriting simulation during the policy planning stage.
NH NongHyup Life Insurance has also developed an AI-based policy planning system, advancing digital transformation in the sales field. This system optimizes insurance design by comprehensively analyzing customers' existing coverage and available premium amounts. It automatically incorporates complex product structures and rider rules, reducing both planning time and application errors. In particular, it is considered highly useful in the field, especially at agricultural cooperatives where both banking and insurance work are performed.
Hanwha Life is utilizing generative AI to enhance planner training and consultation capabilities. The 'AI STS' system developed by Hanwha Life generates consultation scripts based on customer information and provides repeated training and feedback. In fact, planners using this system have shown health insurance sales performance more than 40% higher than non-users. This improvement is attributed to the system's ability to present anticipated questions and answers tailored to the customer's age, occupation, and medical history, thereby enhancing consultation quality.
Industry experts analyze that the adoption of AI is becoming a core tool that determines the competitiveness of insurance companies, going beyond simple work automation. By identifying coverage gaps and predicting eligibility based on customer data, as well as standardizing consultation quality, companies can simultaneously improve productivity and efficiency.
However, concerns about the side effects of expanding AI use are also emerging. In particular, "automation bias," where humans place excessive trust in AI judgments, is cited as a major risk. If planners use AI-generated product recommendations or consultation scripts without sufficient verification, this could lead to judgment errors or incomplete sales. There are also concerns that if less experienced, new planners become overly dependent on AI, their understanding of products and consultation capabilities may weaken.
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An industry official stated, "AI is more of an auxiliary tool to enhance work efficiency rather than a means to replace planners," adding, "Since building trust with customers and providing personalized consultations are at the core of insurance sales, it will be important to strengthen expertise alongside AI utilization."
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