To say that a one-size-fits-all approach doesn’t work in financial planning is taken as axiomatic among advisors. But if clients deserve nothing less than a well-tailored financial plan, why not also a personalized web portal where they can go to manage their portfolios?
Predictive analytics solutions that enable such customization have been in the marketplace for years, yet few advisors or insurance manufacturers use them, according to a January 2006 report from The Tower Group, Needham, Mass. As more boomers enter retirement, the need for such technology is becoming greater than ever–and not just for online self-service applications. The software’s powerful data mining capabilities can help advisors better target clients for up-selling and cross-selling opportunities.
“Predictive analytics allow advisors to more efficiently service and communicate with clients,” says Cynthia Saccocia, the report’s author and a research area director with The Tower Group. “Those [advisors] who don’t leverage these tools will find their practices more expensive to run, as they won’t be able to service a greater volume of clients as effectively.”
The report, titled “Courting the Retired: Predictive Analytics to Define Preferences in Products, Services and Delivery,” concludes that the ability to segment clients so as to learn individual preferences increasingly will be key to courting the retired and the soon-to-be retired. Financial institutions that make products and services available to their entire customer base and segment the base to target individuals based on their life stages, events and needs will offer the most successful programs.
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To attract and retain retirees and pre-retirees, the report adds, financial institutions–not least life insurers and affiliated producers–will have to use predictive analytics tools to identify behavioral trends, segment the base and use the knowledge gained to better service clients.
Predictive analytics solutions are software applications that can anticipate outcomes or suggest actions based on historical data about clients. The software aggregates client profiles, then segments clients according to common attributes, such as previous products purchased, income level, age, ethnicity, etc.
The products typically are sold as modules to customer relationships management solutions. CRM vendors–PeopleSoft, Siebel, Microsoft, among others–generally also market the products as enterprise solutions to be installed on desktop PCs, or as hosted software that may be leased through an application service provider or ASP.
The technology might, for example, determine that particular owners of term life insurance would be ready to purchase a permanent life insurance product based on a triggering event, such as the birth of a child or increase in the client’s income. Similarly, the software might suggest shifting client assets from high-risk equities and mutual funds to lower risk bonds or fixed annuities when the client attains a certain age.