Anyone who has ever been involved in an accident or suffered trauma understands the critical nature of insurance. It can act as a safety net for your family or business, assisting you in regaining your footing and shielding you from overwhelming bills.
Yet the same companies we rely on to help us when things go wrong are basing their policies and products on out-of-date, incorrect data, which not only costs them money but may also harm their consumers in the long run.
And, while other businesses make decisions based on thousands of data points, the insurance industry continues to rely on demographic data that is more than 40 years old.
Industry leaders recognize the magnitude of the issue. According to a recent McKinsey report, nine out of ten insurance companies identified legacy software and infrastructure as barriers to digitization.
Respondents to a survey conducted by the Center for the Study of Financial Innovation ranked outdated technology as the insurance industry's biggest threat.
The insurance industry does not have to operate as usual; artificial intelligence can process over 4,000 data points in minutes and analyze 20 years of mortality, demographic, health, and government trends, producing a dynamic algorithm that can be used to make informed decisions.
Data science-as-a-service (DSaaS) and insurance-as-a-platform (IaaP) platforms can assist insurance companies in determining risk more precisely, developing more customized products for their clients, and improving customer experiences.
Additionally, this enhanced data can help insurance companies in pricing products more accurately, understanding the demographics of who is ready to buy, and acquiring the suitable risk — ultimately making them more profitable.
Additionally, these data streams can assist insurance companies in developing more effective policies and products that better meet the needs of their current and prospective clients.
Historically, the industry has developed new products based on existing ones rather than thoroughly examining what works and what adaptations are necessary.
Carriers can use AI and DSaaS platforms to create products based on demographic and risk data. Industry leaders can then incorporate agent feedback to curate and design products tailored to policyholders' needs.
Indeed, while effective and current use of technological advancements can significantly benefit a business's bottom line, agents are still required to establish trust and serve as the link between considerable data intelligence and developing a personal connection.
Agents who interact with consumers are the ones who show relationships with clients and can help curate suggested data-driven products to make insurance offerings more dynamic and desirable.
While many consumers use digital channels to research and compare insurance options and want the ability to file and track claims online, they still want to know that they can contact a knowledgeable, caring person if they require personal assistance. Companies that successfully integrate cloud-based data-driven artificial intelligence technology with traditional engagement methods via their agents will succeed.