We are thrilled to be here in Orlando for the first day of the LIMRA Distribution Conference. Please check back here for real-time updates from the most interesting sessions and conversations.
Distribution Design: an Executive Perspective
Rand Harbert, Chief Agency, Sales & Marketing Officer, State Farm Insurance
Catherine L. Honor, President, RBC Insurance Services, Inc.
Duane M. Morrow, CMO and EVP, Primerica Life Insurance Company
James W. Kerley, LLIF, Moderator, President, LL Global Services, Inc.
The opportunity to insure North Americans remains an enormous opportunity, according to learnings from this panel. Around 70 million North Americans have no life insurance at all.
At the same time, the industry faces a distribution crisis: the American population continues to grow, but the American agent population has declined and is aging. Increasingly, agents are not diverse enough to match population growth in the general population, particularly among women and Hispanics.
Rand Harbert, EVP and Chief Agency & Marketing Officer at State Farm, specifically spoke to the “rise of the consumer.” In the mobile and social era, consumers want to be served how and when they want, meaning the industry must adapt to serve. Specifically, insurance organizations should focus on strengthening their multichannel efforts to reach and connect with this new brand of consumers.
Better, Faster, Stronger – New World of Predictive Analytics for Insurance
Richard Berry, Deloitte Insurance Practice
Marketing, technology, and service in the insurance and financial services industries are changing in substantial ways thanks to a new world of predictive analytics, according to Richard Berry, Deloitte.
Underwriting is the first major area to be affected by predictive analytics. Traditionally, data sets used to predict insurance risk include demographics (age, gender), face value and duration of policy, alcohol/tobacco use, adverse medical history/family health, annual income, and MIB. Today, traditional data can be combined with “new” data sets such as household data and consumer purchase and financial investment behavior. The most innovative data sets today can also tie in social media behavior data and friend network behavior.
Predictive analytics can be used not only for calculating risk in pricing but can also be used upfront to save time, money, and client disappointment. For example, some data sets such as personal medical history are costly to obtain; upfront analysis identifies factors that may have a bigger impact than medical history for a particular client, giving the insurer the option to skip medical history altogether. This saves the insurer and producer both time and money. Coincidentally, it’s also better for the client: if the client qualifies, they still appreciate a shorter, less onerous application process. In the case of non-qualification, we can reduce client disappointment since advisors won’t then sell clients on policies for which they are likely to be declined.
Second, predictive analytics is also immensely valuable in marketing because it helps with client segmentation. Data helps predict which insurance policies a prospective customer is likely to be interested in, enabling you to focus on marketing those policies alone. Conversely, insurers can avoid marketing to anyone who is not likely to qualify for a policy, saving time and effort on all sides.
Third, predictive analytics can be used to identify which customers are most likely to lapse as well as whether the insurer needs to focus retention resources on keeping the customer. On the other hand, if a customer is at low risk of attriting then fewer resources need to be used for retention.
In the IA market, predictive analytics can be used to identify which independent agents are most likely to sell the most. You have the best data on your longest-standing, top-producing agents, allowing you to identify unique attributes that might indicate which newer agents have the same potential.
Thanks for reading! If you’re attending the LIMRA Distribution Conference, please take a moment to stop by the Hearsay Social booth and say hello.