Swiss Re has highlighted the increasing importance of advanced analytics and artificial intelligence (AI) in enhancing customer engagement and boosting sales within the insurance industry.
Recent research from the company has shown that “customers identify artificial intelligence as a key driver of better experience,” signifying the pivotal role of AI in not only boosting sales but also in shaping consumer expectations.
Daniel Levy, principal risk consultant at Swiss Re, pointed to AI’s potential in personalizing customer interactions in his latest discussion. This approach not only retains customers but also enhances the quality of interactions. Traditional propensity models are now seen as insufficient when not paired with other strategies. According to Levy, “Propensity is not perfect,” and a more diversified approach is necessary to realize greater returns on investment, particularly when customer interactions are low-cost and involve a large segment of the customer base.
He advocates for the use of multiple AI tools to achieve better returns on investment, particularly in scenarios involving inbound inquiries or broad customer bases. The company underscores the limitations of single-solution reliance and promotes diversified AI application.
In addition, Levy pointed out the effectiveness of behavioral segmentation models, which categorize customers based on behavioral patterns rather than demographic data. Such models have proven superior in engaging customers, as they provide insights into customer motivations and enable tailored communications. For instance, one client saw a 33-fold increase in customer action from those identified as highly active compared to those with lower activity levels.
Behavioral insights also help in understanding nuanced customer motivations, which can differ significantly even within similar demographic groups. Recognizing these differences allows for more effective and personalized customer outreach.
Levy also touched on the ethical considerations of AI usage, emphasizing the importance of transparency and responsible application. The company suggested that without proper oversight, the use of AI in crafting personalized messages could lead to ethical concerns, especially if the rationale behind certain communications is not clear.
“That said, these models raise possible ethical issues which need to be factored into any responsible company’s strategy. Unlike with behavioural segmentation, it is not always clear why a propensity model chooses a particular message, and the difficulty of explaining results can raise questions. For this reason their usage needs to be monitored carefully,” Levy said.
