August 16, 2017
As a technology executive familiar with the opportunities new solutions offer, I can confidently say I’m ready for artificial intelligence. However, my enthusiasm for AI outpaces many of my colleagues in the insurance space.
It’s a good question — is the insurance industry ready for AI? The short answer, yes. The long answer… well, read on to hear more about that.
AI is a fairly nebulous topic, partially due to its lack of agreed upon definition. The field of AI has also spawned many cognitive technologies including speech recognition, natural language processing, computer vision and more, but clear applications for insurance did not immediately follow. As AI grows in capabilities and popularity, use cases for insurers are now emerging. However, whether because insurance is a highly personal line of service or because it follows a business model that’s bogged down in tradition, many insurers are hesitant to embrace AI.
Forward-thinking InsurTech companies fare better than most when it comes to driving value from AI, both because of their flexibility and a ‘born in digital’ mindset. But the majority of insurers still struggle to execute digital transformations that incorporate these kinds of technologies.
AI and the Insurance Value Chain
The insurance industry is still far off from a complete AI revolution. However, even integration at an introductory pace will help insurers automate human tasks and learn more about their customers. Although disruption is a word oft associated with AI, insurance organizations can pursue practical and immediate microinnovations that act as stepping stones on the path toward full AI integration.
Take underwriting, a routine and potentially challenging responsibility of the life & annuities insurance industry. Underwriting typically requires humans to make important decision about a customer’s policy based on a wide variety of data sources, or to trust potentially inaccurate data provided by an applicant. Sounds complicated? That’s because it is.
Enter AI machine learning. With machine learning’s ability to sift through aggregated data and find subtle permutations and relationships between data points that human analysis may miss, insurers can automate the underwriting process to save time and create greater uniformity in underwriting decisions.
For example, an insurance company can develop an AI system capable of determining the risk profile of an applicant. To do so, the system would pull information from multiple online sources and make underwriting decisions based on established underwriting rules, all without human intervention. These decisions would also incorporate objective criteria learned from existing policy decisions already in the system. AI software’s cognitive feedback loop allows the technology to learn and make educated decisions even in changing circumstances.
By leveraging previous insights and cognitive machine learning, AI actually removes much of the guesswork and subjective thinking from the underwriting process. Not only does this improve businesses by adding regularity into routine decision-making, but it also removes any bias – presumed or real – that could exist when humans spearhead the underwriting process. For an industry always working against a negative-experience model, perception improvements like this are crucial to boosting the insurer-policyholder relationship.
AI Applications for Insurers, Continued
AI has other exciting applications throughout the insurance value chain, many of which lead to a better end-user experience.
For example, AI can tap into a policyholder’s social activity to predictively uncover opportunities for new policies or existing policy endorsement. Imagine if a customer posts a new baby picture to his profile, updates his status to say he’s recently had a child or makes a series of baby-related posts. When this happens, insures can use image recognition and natural language processing to interpret his social feed and reach out to him to discuss a new life insurance policy or increase his limit. This proactively meets the customer’s need and earns more business. AI can similarly hook into financial planning software to inform sales interactions based on monetary information and key milestones like promotions and retirement.
Looking forward, AI could even offer important clarity for the cyber defense of insurers’ digital environments. With cyber threats on the rise, insurers now struggle to assess the risks of digital organizations. These risks are particularly difficult to evaluate because they change at a rapid pace, and insurers cannot easily quantify this liability. Every channel and device added only complicates the equation.
Fortunately, businesses armed with machine-learning software can outsmart cyber threats over time. First, AI can analyze unstructured data (e.g., white papers and research reports) from previous hacks to better understand digital weaknesses and how to stop hackers from exploiting them again. Second, AI’s ability to aggregate and analyze massive data sets can keep pace with cyber-security changes with an accuracy that humans cannot. This makes it easier to assess the risks of their digital organizations and improve cyber defenses.
Looking Forward: Insurance and AI
The reasons to start leveraging AI are numerous, so why aren’t more insurance companies jumping at the chance? In fact, some are, but we just don’t hear about it. Larger insurance companies are actively integrating AI software and strategies into their business models, but rarely share their progress because the technology is seen as a crucial point of differentiation from competitors.
Despite this, now is the time for all insurance companies to begin considering AI. Issues surrounding data and complex decision making will only get more difficult with time, and insurers must embrace modern systems now to prepare their companies with scalable architectures and flexible technologies.
This is especially true as younger generations of digital natives grow into policyholder ages. While just 44 percent of internet users 55 years or older value AI for recommending products/services, excitement around the technology increases with younger respondents. Over half of internet users ages 35-54 find value in AI, and 62 percent of those ages 18-34 feel the same. While AI integrations are more common in spaces like retail, companies of all kinds will see increased demands for the conveniences AI makes possible— insurance included.
However, insurance doesn’t face just a technological challenge when it comes to AI. The battle is a cultural one as well. Maximizing ROI from AI investments demands a company that is willing to learn alongside its technologies. Organizational stakeholders must be aligned around cultural innovations and promote processes optimized to support such updates. An insurer resistant to the internal changes AI reveals squanders the opportunity to undo the antiquated strategies, mindsets and relationships that consumers will no longer accept.