Natural language processing (NLP) technology, which enables computers to understand and process human languages, goes a long way to improving the lives of users around the globe. It also has massive revenue implications.
It is estimated that the total NLP software, hardware and services market will reach around $22.3 billion (U.S. dollars) by 2025, from $7.63 billion in 2016. NLP software solutions leveraging AI are predicted to grow from a value of $136 million in 2016, to $5.4 billion by 2025.
The speech and voice recognition market was valued at $5.15 billion in 2016 and is expected to reach $18 billion by 2023. With voice-based search identified by Gartner as the fastest growing mobile search, Comscore estimates that by 2020, half of all searches will be performed via voice. A Gartner report predicts that by 2020, 85 percent of customer interactions will be managed without human involvement.
By 2021, more than 50% of enterprises will be spending more per year on bots and chatbot creations than traditional mobile app developments. Gartner also believes that by 2020, 55 percent of all large enterprises will be using at least one bot or chatbot.
The image recognition market is expected to grow from $15.95 billion in 2016, to $38.92 billion by 2021.
As noted in my last blog post, an NLP/AI revolution is underway in the insurance world. The time, effort and cost-savings that can be achieved by freeing up agents to deal with higher value calls and complex issues can translate into significant savings and new revenue opportunities. How is this playing out today?
Chatbots and virtual agents are the perfect vehicles for reaping NLP’s benefits, as they’ll enable insurers to focus on constantly improving service, broadening engagement and ensuring retention, while fulfilling the demands of a new generation of customers that has grown up in the digital age.
A mere website, where a handful of insurance sales functions can be performed, isn’t enough for consumers today. And they don’t want to be left hanging when an online service gets confusing or questions can’t be answered. Even worse is being forced to speak with a human agent, or go to the office for a dreaded face-to-face meeting.
As digital transformation become more ubiquitous, insurers are integrating chatbots and virtual agents into their overall ecosystems, leveraging their wealth of big data and finding innovative and engaging ways to efficiently handle customer queries, connect the customer with the right people in the organization and even resolve claims, while significantly increasing efficiency.
IPsoft’s Amelia, a blonde avatar dressed in a stark black business suite and modeled on a human named Lauren Hayes, is perhaps the perfect example of how NLP can be used to create an advanced virtual agent that offers organizations a cost-effective, engaging alterative to repetitive tasks. Amelia can be used in the insurance underwriting process. Customers can converse with Amelia via her conversational interface on any device, and she can connect to the carrier’s systems and data sources to gather the customer information she needs, or the customer can upload information, such as medical and physical records, directly to Amelia.
In May, U.S.-based insurance carrier Allstate launched its chatbot, called Allstate Business Insurance Expert (ABIE), to provide real-time answers to questions about small business needs and insurance solutions. And Singapore-based insurer Singapore Life launched its first self-learning chatbot, SingLife, in June. Operating via Facebook Messenger, or the company’s website, SingLife uses predictive modelling and helps provide life insurance coverage in simplified steps.
The peer-to-peer insurer Lemonade’s claim-bot, A.I. Jim, rose to chatbot fame early last year when it reportedly broke a world record by handling and paying out a straightforward claim within three seconds, with no paperwork required. According to Lemonade, one of their policyholders submitted a theft claim for a $979 lost coat in December 2016. Within seconds, A.I. Jim reviewed the claim, cross-referenced it with the policy, ran 18 anti-fraud algorithms, approved the claim, sent wiring instructions to the bank, updated the policyholder and closed the claim.
Once a chatbot such as A.I. Jim obtains the details of a claim, it calls a set of insurance system application program interfaces (APIs) and other supporting systems to log the claim, run anti-fraud algorithms, make the decision to accept and pay, and then execute the payment.
The ability to shift simple claims to a bot that can understand the language of the claim and then automate and shorten the process from months or weeks, to minutes or even seconds, opens the door for massive effort- and cost-savings, plus a significant upgrade in customer satisfaction.
We don’t want to over-simplify the issue. Chatbots obviously can’t exist on their own. To reap the benefits, insurers require a solid policy administration core that can supply the bot with the required information, interface with it in real-time and then run the required processes. The right digital suite will also help insurers ensure that the chatbot is part of the overall effort to achieve peak digital engagement.
For more information, please check out our white paper, Insurers Can Benefit from Natural Language Processing (NLP), which outlines the advantages of NLP for insurers and explains what is needed to maximize NLP.