Tech Talk: Speed-to-Value and the AI Revolution

By | September 18, 2017
Insurance Journal's Tech Talk column is made possible in part by the generous support of ITC

The term “speed-to-value” has been around as a management maxim for decades but is being reborn in the digital age — and its application for agents today is perfectly timed. Here’s why.

Speed-to-value refers to the need to continually develop innovative products and get them to market quickly. In our industry, much of this responsibility falls to insurance carriers. For agents, speed itself is a value — being as responsive as possible to the customer, responding in real time to questions and requests, and delivering quotes and forms in hours instead of days.

An agency’s digital tools are critical in the speed-to-value equation, including an up-to-date website that offers multiple contact options and easy-to-use features such as chat, a client portal and/or an agency-branded mobile app.

The artificial intelligence (AI) revolution is also linked to speed-to-value. Most of America is already using AI in some form, e.g., Watson, Siri, Cortana, web page rankings, and recommendation systems such as Amazon. Rather than dismissing the prospect of the virtual agent, agents need to find ways to adapt and respond to it.

“There are many steps agents can take today to improve delivery time of services,” said Steve Anderson, a technology authority for agents. “Agents say they provide good service, but are only open 9-to-5. People expect to be able to access information using a variety of communication platforms, including text messaging, online client portals with access to client real-time information, as well as extended office hours.”

Ron Berg, executive director of the Agent’s Council for Technology (ACT) said AI can help agents in the form of machine learning, otherwise known as chatbots or robo-advisors.

“Agents will be able to use these tools to supplement their existing staff and provide agency website-based guidance for consumers and customers,” Berg said. “This can help agency staff by taking time off their plates to have the chatbots answer basic and specific questions on coverages, options, and many other related issues.

Agents should think of chatbots as “guided conversations,” according to Anderson.

“Chatbots combine machine learning and conversational computing to provide the ability to answer common questions using multiple types of devices,” he said. “I see two potential iterations of these conversations: internal and external. I suspect for insurance agencies, the use of internal guided conversations could come more quickly. I call it employee augmentation because it uses a knowledge base that can be accessed by any employee to answer common (and maybe not-so-common) questions from clients.”

This allows everyone in the organization to answer these questions accurately and quickly the first time, without having to look up information. As new employees are brought into the organization, this also becomes a great training tool and allows that new employee to get “up-to-speed” faster.

According to Anderson, one agency that is testing a guided conversation for an automated annual homeowners renewal process has had success.

“An email is sent with a link to the conversation which the homeowner can complete in less than five minutes on any device, mobile or desktop,” he said.

So far, the agency reports a 16 percent completion rate of these renewal reviews and approximately 35 percent of the completions go through a mobile device, he said.

As important as speed is, Bill Wilson of Insurance Commentary offers a caveat.

“Consumers need to understand that, from a service standpoint, their insurance programs are not like buying consumer goods on Amazon. They are creating and modifying complex legal contracts,” he said. “It’s important to be responsive, but when most of your assets and potentially a big chunk of your income are on the line, some steps in the process must be deliberate and thorough no matter how long they take.”

Topics Agencies InsurTech Tech Data Driven Artificial Intelligence

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