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Artificial Intelligence For Competitive Advantage


Insurance is no stranger to AI. It helps carriers and agents reduce the time to deliver quotes, expedites underwriting and claims processing, and detects fraud. And Usage Based Insurance (UBI) products, like Farmers Signal, monitor driving habits and adjust policies and premiums in response.

At the “sharp end”―sales, marketing and customer engagement―AI is also invaluable and can drive competitive advantage by enhancing acquisition and retention. Chatbots are a common example. These address simple questions, giving customer-service specialists more time to handle complex requests. A word of caution, however. Their usefulness depends on how much work goes into setting them up, and the platform’s capabilities. Most chatbots, according to research, disappoint―with  54% of US online consumers believing they will have a negative experience. Here are three other widely used tools that insurance agents may be able to use profitably.   

Customer Relationship Management (CRM)

You are probably familiar with this kind of application, and may already use a CRM system, like Salesforce and Hubspot. At a basic level they make the processes of managing your clients, prospects and marketing/sales efforts more efficient and automated, freeing up staff time for value-added prospecting and relationship building. For example, they can send out reminders when policy renewals are due. But many also contain more sophisticated AI which can be used to “score” prospects based on receptiveness to a sales pitch. The platform automatically lets you know when their score takes them from a “warm” to a “hot” lead and increases the chances of a successful conversion. In addition to the big generalist CRMs, you can check out these insurance-agency focused CRM and related productivity tools. 

Sentiment Analysis

This is widely used in marketing and especially social media to track how people are feeling about issues, companies or brands. It can uncover insights and possible points of competitive advantage by analyzing the breadth of comments across social and other media. The more sophisticated kinds can even do this on an individual basis, tracking, for example, your clients or prospects based on publically available information and personal data you’ve collected on them. If you want to track how people are feeling about Farmers or its competitors, or specific issues and topics relating to insurance, you can track these with simple search queries and get sentiment scores (e.g. degrees of  “positive,” “neutral,” or “negative,”) and other helpful analyses. This kind of awareness can help you position pitches and marketing communications more effectively, uncover pain points and opportunities, and even gauge which kinds of demographic are likely to be more responsive to that big splashy corporate-advertising campaign your insurance provider is running.  For leading sentiment analysis tools, including free options and more insight into their application see this article from Hubspot

Predictive Tools

This is a catch-all for Artificial Intelligence applications that help predict an individual’s behavior and needs based on a variety of data inputs.  

The basic “prediction” concept is age-old, such as buying up mailing lists of people who have recently bought a home or changed postal address ―in order to target associated life-change needs like renter’s or home-owner’s insurance.  Using AI, however, can help you laser-focus on individuals’ unique circumstances and motivations to fine tune product offerings, communication and timing.  

At one end of the spectrum are applications like call-center sentiment analysis. These are typically used by large organizations like Amazon, Netflix, and Apple, and their predictive algorithms can increase customer satisfaction. Their AI “listens” in on the conversation in real time and can pick up nuances in word choice, tone or mood from the caller. It can do this well before the human brain perceives them, and gives instant cues/tips to help call-center staff respond in ways most likely to elicit a positive reaction―especially in potentially confrontational situations. Some systems may also store conversations, which the AI uses to gauge how a customer’s sentiment has changed over time.  

Other kinds of Artificial intelligence review consumer behavior in order to predict preferences. They can recommend products and services that best match the customer’s needs. Some are insurance-industry specific and typically focus on cross selling, up-selling and client retention. Instead of a person looking at notes on file, including customer type, age, premium paid, and then manually cross-matching these with insurance products, the artificial intelligence draws from multiple sources to make recommendations automatically. These can be both internal like CRM and policy information, and external like social media and credit bureaus; and also take account of life-stage and whether there are other family members. Here’s an example.

Moving forward, AI will no doubt be a double-edged sword. It both threatens to squeeze humans out of the equation, but will also reward them by making their efforts more efficient and giving them a competitive edge.   

And speaking of competitive advantage – if you’re looking for better financing, no-strings advice and the best in service – your Credit Union offers hard-to-beat loan and savings products, many designed with Farmers agents in mind. For more information speak to your Credit Union business consultant or visit our website at

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