In some parts of North America and Europe, sometimes there’s more snow than expected. A lot more. And then the roads aren’t plowed right away.
By the time people wake up and start digging themselves out, they’re already running late for work, which only adds to the kind of driving conditions that you’ll face.
It may not take artificial intelligence to recognize that the risk of accidents (and subsequent insurance claims) is high on certain days in winter.
Over time, however, A.I. will help insurance companies provide a better experience to their customers — not just in situations involving cars, but across all lines and throughout the year.
Through it may not be recognized as a “digital-first” industry today, insurance has always been entirely driven by its use of data.
Assessing risks, collecting customer information, pricing, and investigating claims are core to the business. It’s just that until recently, much of that data management was handled in manual or even paper-based ways.
Over the last several years, of course, a growing number of carriers have worked hard to digitize many processes, from creating customer portals to rolling out broker management systems.
While all those things can offer great value, A.I. promises to dramatically accelerate insurance firms’ ability to deliver better outcomes because it can analyze massive amounts of data beyond the capabilities of a human, and then make it easier for them to make the best possible decisions.
Even if you’re not an expert in things like machine learning, natural language processing or other elements of A.I., you can start to identify the biggest opportunities to take advantage of the technology today. Consider some of the following potential benefits:
Carriers have typically looked at things like age and previous driving record to determine premiums for car insurance policies, health history and lifestyle factors for life insurance, and environmental conditions for property insurance. All of these remain relevant data points, but other technology advancements provide much more for A.I. to work with.
Think of how sensors could gather information about weather, for instance, or the age of building materials or machinery. Wearable technologies can provide a deeper level of insight into risk of disease or potential disabilities. Drones and GPS can determine the potential impact of severe weather or other elements that could trigger a disaster.
While some of these scenarios may force deeper discussions among carriers, brokers, and customers about the acceptability of usage-based insurance models, there’s no question AI can help in two ways.
First, A.I. can synthesize the data from all these touch points in such a way that pricing on premiums will better inform than at any time in human history.
On the back end, meanwhile, insurance companies will use the deeper understanding of various risk factors to save untold amounts in underwriting fees, which can, in turn, allow them to allocate more resources to improving customer experiences.
Insurance companies will also be leverage A.I. to do predictive underwriting. Using companies such as Daisy, insurance companies can analyze 100% of their data to determine what potential customers have more risk than others.
This will allow insurance companies to identify the optimal risk curve to govern premiums and better manage their loss ratios, allowing them to drive higher revenue and profits.
When problems arise, customers want their insurance companies to stand behind them. Insurance companies want to do the same thing, but they typically need to confront a series of difficult questions: Is the information offered in the claim true? Are the details accurate? Does the policy cover it?
If some of the answers are “No”, carriers need to determine if it’s an error or fraud. While human judgment will remain part of claims investigations, this is an area where A.I.’s ability to analyze data and detect anomalies will make it easier and faster for insurance companies to detect and investigate fraudulent claims.
In the process, insurance companies will save millions of dollars in fraudulent claims payments, driving their profitability and embrace of A.I.
Consumers are becoming accustomed to fast, personalized service that takes their preferences into account when they conduct activities like online shopping.
Algorithms based on A.I. will allow insurance companies and brokers the act in much the same way, positioning them as helpful assistants rather than organizations associated with complexity and long waiting times.
Think about how A.I. could help pair consumers with the right kind of carrier, or the ideal coverage based on their particular needs and risk profile.
Other firms will use A.I. strategically to allow greater self-service capabilities in direct-to-consumer scenarios. A.I.-driven features like sentiment analysis, meanwhile, will raise the alarm before customers become impatient, frustrated or downright enraged over the quality of their service.
Though they address different pain points, all three of the areas described here are based on a similar premise, and it’s one that is also common across A.I. When properly applied, A.I. provides companies with data-driven recommendations so they can make the best and most profitable decisions.
In insurance, where firms have largely been forced to deal with issues after the fact, A.I. promises the kind of early-warning system that will define a strong customer experience.
Getting started now may be the smartest thing you do in 2019.