Traditional insurance companies are at a critical crossroads. Changing customer expectations, increasing regulatory complexity, and pressure to streamline operations are driving the push for reinvention and innovation.
Two of the biggest game changers in the industry have been the introduction of artificial intelligence (AI) and machine learning (ML). When applied to a unified first-party data set in a customer data platform (CDP) like BlueConic, AI and ML can transform the way marketing, customer experience, analytics, and other growth-focused teams at insurance companies operate and use data to understand and interact with consumers.
BlueConic principal customer success manager, Nicky Peterse, has years of experience helping financial services and insurance companies across geographies implement and use our CDP to improve how they engage with customers and drive business growth. We sat down with Nicky to find out how AI/ML is being used in the insurance industry to make the previously impossible, possible.
Q: How is AI and ML being used in insurtech today?
A: While the possibilities are endless, it really depends on the first-party data insurance companies have available to run the models and the objectives they are trying to accomplish. Some popular use cases today include customer lifetime value (CLV) modeling, recency, frequency, monetary value (RFM) modeling, and smarter personalization.
By calculating CLV, companies can identify who their high-value customers are and use that insight to segment customers by the expected number of future purchases (i.e., signed policies), overall lifetime value, and more. When companies have data on when policy contracts start and end, they can use RFM modelling to analyze and predict propensity to churn and focus their marketing efforts accordingly. Finally, insurance companies are leveraging AI and ML to understand what stage a consumer is in their journey and deliver (or suppress) the right message at the right place and time.
In addition to these more typical examples, some additional use cases are starting to emerge, such as next best action/next best offer and lookalike models. Next best action/offer models can help companies make smarter decisions, such as when to ask for an email or promote a particular product. Traditionally performed on platforms like Facebook, lookalike models enable insurance companies to be much more precise in their targeting based on who is most likely to purchase a particular product.
Q: What are some of the innovative technologies being implemented in insurtech currently?
A: More and more financial and insurance companies are embracing pure-play customer data platforms (CDP) like BlueConic to make the most of their privacy compliant first-party data. These platforms include build-in machine learning modules that enable business users and data scientists alike to run models directly on top of their first-party data. Business users without technical skills or SQL knowledge can run CLV and propensity models right out of the box and immediately act on those insights. Perhaps more importantly, the models aren’t black-boxed, enabling data scientists to change any of the out-of-the box models, or bring in their own.
Q: What does the future hold for insurance technology?
A: I expect use cases built on top of first-party data will drive most of the innovation. When marketing, customer experience, and other growth-focused teams have access to unified, consented first-party data, along with AI/ML capabilities all in one system, they can a much deeper understanding of consumers and ensure they’re delivering individualized experiences across all channels. It’s this type of customer-centricity mindset that will enable insurance companies to unleash growth going forward.
To find out how BlueConic can help you transform your relationships with consumers and unleash business growth in the privacy-first era, request your demo today.
