Artificial intelligence, the internet of things and massive computing power are transforming the insurance industry. Claims procedures are being handled in an entirely new way, impacting everything from data gathering to data analysis. I saw something similar in my previous stop at American Express, where I worked on projects such as using artificial intelligence for data predictions and automating customer service. I'm doing something similar in my current role as well.
For example, the way we process data for quotes is rapidly transforming, thanks to much more efficient algorithms. Traditionally, the distribution chain for commercial insurance has been particularly complex and inefficient. It used to take two to four days to generate a quote, and there were a lot of hands involved in that process. Thanks to advances in data gathering and human process improvements, generating a quote now takes only minutes in some cases. By arming employees with artificial intelligence tools, we’ve made those cycles much faster and more accurate. These enhancements are driven by software packages that deploy pattern matching and natural language understanding (NLU) to find insights and key concepts in huge quantities of data.
Finding a needle in a haystack
NLU is a field of computer science, AI and computational linguistics that focuses on understanding and deriving meaning from human language in a smart and useful way. It lets users search through textual information to automatically find key concepts and phrases, which can then be flagged for an underwriter’s attention. The goal of AI is to enhance and augment human employees’ capabilities so they can do things that are not otherwise possible. Using NLU, you can find the needle in the haystack.
Even on complicated policies and claims, artificial intelligence is making great strides. Standardized actuarial models have always translated well into algorithms, but specialty products, which are more complicated, also benefit from AI at the underwriting level with a little bit of work. If there is a contractor, for instance, AI lends itself very well to looking at factors like how they are classified online and the nature of the work they do.
Our sources of data are changing, too. Although unmanned aerial vehicles, or drones, have become increasingly common as commercial tools and recreational devices, they’re also an extremely useful source for gathering insurance data. With a variety of sensors and the ability to take high-resolution aerial photographs, drones have shown great potential for gathering information that is otherwise difficult or expensive to collect.
For instance, drones can gather data on the condition of a property from hard-to-reach places such as roofs and easily measure information such as water damage or heat exposure. That means not only a faster roof inspection process, but a safer one as well. No need for inspectors to scale the roof on a ladder.
Using technology in stores and restaurants to reduce risks
I've seen digital technologies, such as internet of things, offer new opportunities around accountability in the grocery and restaurant industries, with platforms that help reduce the risk of customer and employee accidents like slips and falls.
Instead of carrying clipboards, employees are using apps, sensors, beacons or QR codes strategically placed throughout a business. The app tracks the employee’s path during a scheduled safety walk, ensuring nothing is skipped. It also ensures quicker reporting and responding to issues in store. Instead of waiting for the employee to complete their rounds and file a report, its now tracked in real-time alerting managers to any issue that needs to be addressed.
Grocery stores and restaurants are also using
That’s all part of efforts to simplify regulatory compliance and reduce risk through platforms that create auto-alerts for temperature conditions in food storage areas and document required inspections to show they’ve been completed. Monitoring employee and third-party practices in real time means restaurants, for example, are less likely to face claims over foodborne illnesses. These types of claims can not only result in costly lawsuits, but they can also significantly damage the corporate brand.
By increasing internal and external compliance rates, lowering risk, and minimizing claims, IoT technologies have the potential to substantially reduce the total cost of risk for companies in the food industry, the retail sector, manufacturing and beyond.
Artificial intelligence makes the jobs of those working in the insurance industry easier. Applying large data sets to the insurance life cycle improves expectations and outcomes all around. There are some complex policies, with hundreds if not thousands of factors involved. AI is evolving and allowing specific pattern matching, which helps determine particular risk exposures. Instead of underwriters looking at every single risk, they can focus on the highly complex or customized cases instead.
From data gathering to data processing, claims procedures are being handled in an entirely new way, transforming the insurance industry in ways big and small.
