How Artificial Intelligence Is Transforming The Insurance Industry

How AI and machine learning are changing the insurance industry

Here’s a look at the areas where AI is transforming the insurance industry.

Risk assessment

Historically, to assess potential customers’ insurance risks, underwriters have relied on information provided by applicants. This method is problematic because applicants may be dishonest or make mistakes, rendering these risk assessments inaccurate. AI can help in the following ways:

It assesses risk more thoroughly.

Machine learning, specifically natural language understanding (NLU), enables insurers to analyze more abstract sources of information — such as Yelp reviews, social media posts and Securities and Exchange Commission filings — to better assess the insurance carrier’s potential risk. 

“Our ability to actually look at these textual data sources and pull out highly relevant information is greatly increased [with NLU],” said Andy Breen, board member and CEO of Prints of Love and former senior vice president of digital at Argo Group. “We’re making use of these information sources that weren’t available or easily disseminated before.”

It assigns appropriate premiums.

More accurate risk assessments mean more appropriate premiums. In an industry where the most significant difference between insurance companies is price, not products, a more individualized exposure model could make a big difference, according to Sofya Pogreb, board member at Next Insurance and chief operating officer of Bill. 

“Traditionally, [the industry has offered] ‘lowest common denominator’ products: a standard liability policy,” Pogreb said. “What you end up with is a very undifferentiated product, where a bakery and a laundromat have the same policy. That’s not the right way to go for the customer. Being able to consume more data automatically, we will see more customization, and customers will benefit by paying for coverage they truly need.”

Fraud detection

Insurance companies are extremely concerned about fraud, and AI is a crucial watchdog in the fight against fraudulent claims.

“The ability of machine learning to assist in spotting suspected fraud is well established, but human-led data science is just as capable so far,” said Areiel Wolanow, managing director at Finserv Experts. “The key difference over time will be one of cost. Professional criminals will keep abreast of industry-leading fraud indicators and adapt their behavior to suit. Human data scientists will need to iterate their analysis over time to keep pace, while machine learning algorithms train themselves over time based on observable changes in the underlying data.”

Error reduction 

The insurance industry’s distribution chain is winding and complex. A series of intermediaries examine information between the insured and the carrier, leading to a lot of human error and manual work that slow the process. However, AI is starting to fix that problem.

Algorithms can improve the speed and accuracy of information as it is passed from one source to the next. Breen explained that by logging in to a portal and uploading a PDF, the insurer reduces the amount of data entry and thus increases the accuracy of that data. “People get tired and bored and make mistakes, but algorithms don’t,” Breen said.

For Pogreb, bridging the gap between the insured and the insurer is as important as reducing errors. More accurate data benefits both customers and insurers because insurers can develop better products based on more precise assessments. As a result, customers pay for exactly what they need. [Read related article: Websites for Comparing Small Business Insurance Quotes]

“With machine learning, I think we’ll be able to do a much better job giving the consumer that advice automatically,” Pogreb said. “Based on what you tell me about your business and what I know about similar ones, [I can say] I believe this is the right combination of coverage for you. So it’s putting the onus neither on the agent nor on the customer — who, frankly, doesn’t have the experience or knowledge — but letting the data provide the advice.”

Customer service

Even in a sector as change-resistant as insurance, good customer service is paramount. After all, people often stop using companies that provide bad customer service. That’s why so many insurance company websites now include chatbots. These AI tools can guide customers through numerous queries without human intervention. They’re also available 24/7, unlike many human teams.

For example, a customer who needs help accessing their account could ping the chatbot for assistance while visiting the insurer’s website. This function could potentially resolve customer concerns quickly. Human customer service agents may still be necessary for more complex issues, but AI chatbots can handle some of the work.

Claims processing

Insurers exist to process claims and help customers cover them, but claims assessment isn’t easy. Agents must review several policies and comb through every detail to determine how much the customer will receive for their claim. That can be a painstaking process, but AI can help.

Machine learning tools can rapidly determine what’s involved in a claim and forecast the potential costs. They may analyze images, sensors and the insurer’s historical data. An insurer can then verify the AI’s results and settle the claim. The result benefits both the insurer and the customer.

How AI in the insurance industry benefits business owners

Widespread industry adoption of a specific technology often reflects the benefits it offers to companies in the sector, sometimes with no apparent effects on the customer. However, this isn’t the case with AI in the insurance industry, which provides clear customer advantages. AI tools can provide the following benefits to small business insurance customers:  

• Customized insurance plans: AI-driven risk assessments help insurers tailor plans to a company’s unique needs so small business owners don’t overpay for unnecessary coverage.
• Efficiency in claims processing: AI can drastically increase efficiency when creating statements. Machine learning algorithms speed up the claims process, thus reducing the time business owners wait for claims to be approved and funds to be disbursed.
• Fraud detection: AI can identify patterns that suggest fraudulent activities to protect businesses from false claims and potential financial losses.
• Predictive analytics: AI can predict potential risks and suggest preventive measures to help business owners mitigate risks before they turn into costly claims.
• Improved customer service: AI-powered chatbots and virtual assistants provide 24/7 customer support by answering queries and assisting with policy management, thereby enhancing the overall customer experience. 

The future of insurance AI

The insurance industry has only begun its foray into AI, and companies are already experimenting with new ways to incorporate it into their day-to-day operations in anticipation of further technological development. 

“It’s the very early days of AI,” Breen said. “For menial, repetitive tasks, we put the computer on it … but we’re a ways away from a computer underwriter. We’re really just augmenting humans at this point.”

Still, AI is making significant industry changes that offer a glimpse into the future of this technology. Here’s what to expect in this industry.

AI in insurance will further streamline the underwriting process.

Pogreb sees even more potential for AI to streamline the underwriting process. She predicts the number of applications a human underwriter is required to handle will plummet as machine learning finds its place in the insurance industry. 

“We believe with technology and machine learning, a lot of [human underwriting] can be done away with,” Pogreb said. “The percentage of insurance applications that require human touch will go down dramatically, maybe 80 percent to 90 percent, and even to low single digits.”

Additionally, Breen noted that underwriters at Argo Group are starting to manage portfolios instead of reviewing every submission. Machine learning algorithms handle standard, predictable claims, while human underwriters essentially fine-tune the process and intervene in cases that need higher-order decision-making.

More insurance firms will adopt AI tools to stay competitive.

While AI adoption is in its early stages in the insurance industry, it’s already transforming the landscape. According to Wolanow, insurance companies that want to stay competitive should test the waters of AI.

“Companies can prepare and stay competitive by starting to assess the impact of machine learning on their business by prototyping their own algorithms,” Wolanow said. “An individual machine learning algorithm that performs its analysis on a stand-alone basis is actually quite inexpensive, [and] in many cases, a stand-alone analysis tool is more than fit for purpose.”

AI’s market outlook will continue growing.

According to Gradient AI data, 90 percent of insurance companies plan to increase their AI investment to improve operations, with 75 percent focusing on underwriting and claims management AI technology. Additionally, the AI-influenced insurance sector’s market value is projected to reach $35.77 billion by 2030, which represents a compound annual growth rate of about 33 percent.

Embracing the AI revolution: The future of insurance industry transformation

The insurance industry is embracing a digital revolution driven by artificial intelligence. AI technologies are transforming how risk is assessed, fraud is detected and claims are processed, resulting in more efficient and accurate operations.

The reduction in human error and enhanced customer service provided by AI significantly improve the overall customer experience. As the industry continues to integrate these advancements, the potential for even more streamlined and effective processes is vast. Insurers that adopt AI will stay competitive in a rapidly evolving market, benefiting both themselves and their clients with superior service and optimized products.

Amanda Clark contributed to this article.