How Artificial Intelligence Impacts The Insurance Industry, Agents & Consumers
By Joe Peters
Artificial intelligence (AI) has changed many industries, and insurance is no stranger to AI these days. The question is, how has it impacted agents and consumers and will it lead to significant changes?
Artificial intelligence (AI) and automation rest on a simple concept: They refer to computers being programmed to think, learn and solve problems as a human would, but much faster. This capability rests on “machine learning,” which allows computers to adapt without needing explicit instructions. They apply algorithms and statistical models to extract conclusions from data patterns.
Artificial intelligence and automation started slowly in insurance, but they accelerated rapidly in recent years. Data Bridge Market Research shows that the global insurance AI market is likely to increase 24% annually from 2021 to 2028, with an ending value of $6.92 billion. McKinsey, a global management consulting firm, believes insurers’ AI investments will ultimately create $1.1 trillion in additional annual value. Much of it— $888.1 billion— will come from applying AI to marketing and sales functions.
AI/Automation Transforming the Insurance Value Chain
The true value of AI will depend on how it reshapes the customer journey from initial query through application, renewal and claims. It will have a revolutionary impact if it eliminates paper and increases transaction volume while delighting customers. Here’s a quick tour of how AI and automation might revolutionize several insurance functions in the coming years:
- Insurance underwriting: Until recently, underwriting has primarily been a human function, relying on a system of arcane rules. As a result, it has often produced backlogs and frustration due to processing delays. Fortunately, AI has sped up processing and reduced backlogs because of its advantages over the human brain— high accuracy due to its algorithms and computational techniques and low bias versus human underwriters due to algorithms and sheer processing power.
Thanks to AI, insurance underwriting has crossed an efficiency frontier. For example, underwriting departments now process and extract data using document-capture applications. Moreover, they collect risk-related data from multiple sources, using machine learning to develop accurate consumer risk profiles.
Because AI-armed underwriters can evaluate more risk data, they can base their pricing decisions on actual consumer statistics rather than lowest-common-denominator pricing models. This results in more customized insurance, which will likely stay on the books longer.
- Claims processing: For consumers, filing a claim is where the rubber meets the road. Receiving a prompt and accurate settlement is their moment of truth. If something goes wrong, customer satisfaction and loyalty damage are often incalculable.
As with underwriting, claims processing has been a labor-intensive process. Many tasks still require manual processing, and too much paper continues to flood the system. AI and automation have begun to address these shortcomings, reducing errors and expediting claim adjudication.
Today, insurance companies are using AI bots to receive customers’ first notice of loss (FNOL). Bots can cue policyholders to submit information, take photos of damaged property and submit them without human involvement. Cost forecasting is also possible, as is triaging losses, then routing them to claims handlers based on workload and expertise. Similarly, bots using neurolinguistic processing (NLP) can extract data from claim documents, sort and classify them and input data into the claims system.
Another use of AI in claims processing is fraud prevention. Here, crime-detecting algorithms evaluate claim submissions to identify data patterns suggesting fraud. Using AI, insurers’ ability to uncover criminal activity has kicked into high gear.
- Policy management: Policy management is the process of quoting and issuing a policy, along with handling data updates, renewals and cancellations, among other functions. Traditionally, policy management has been tedious, relying on paper-intensive manual tasks. However, slowly but surely, the insurance industry has deployed computer technology to automate many essential policy administration functions.
The most crucial policy administration functions are policy issuance, updating and cancellation. AI and automation have systematized workflows so that when customers or agents make changes, all data fields holding the same information get updated. AI, specifically robotic process automation (RPA), reduces the amount of human exertion involved in policy administration. RPA tools can process customer emails, call transcripts, web forms and other data sources, extracting service requests and executing them independently.
AI has also revolutionized policy quoting and renewals, reducing the amount of human work required and increasing the number of quotations generated compared with legacy methods.
The same is valid with policy checking. For years, agents had to review newly issued policies by hand before delivering them to customers. This entailed diligently checking the entire policy and related documents to ensure the information was complete and consistent. With documentation for complex accounts amounting to hundreds or thousands of pages, policy checking has been incredibly cumbersome for most agents.
Enter AI and automation tools, which have fully automated this function. Thanks to computer processing, what might have taken hours to complete now takes minutes. AI can review all policy documents to ensure nothing’s missing or inconsistent. For example, correcting misspellings of insured or entity names can prevent costly problems— especially during litigation.
- Agent marketing and sales: Insurtech platforms have allowed consumers to buy insurance without using an agent. They’ve devised an appealing value proposition for young clients who prefer to purchase insurance online. They interact with bots to determine which type of insurance they need, enter their data for policy quoting and establish accounts and payment preferences within minutes. After the sale, some insurtechs also provide online certificates of insurance and other support functions, eliminating the need for customers to deal directly with insurers.
For agents selling commodity insurance products, such as term life or low-limit business owner’s policies (BOPs), insurtechs have been a serious competitive threat. But, for agents who specialize in complex life insurance solutions, such as buy-sell or large commercial insurance coverage, they have only been a minor concern.
AI should significantly help automated insurance agents sell their products. It will support their efforts to:
- Generate leads: AI can qualify prospects with additional data to help agents make a successful approach.
- Provide 24/7 customer assistance: From agents’ websites, using virtual digital assistants, AI can determine the optimal form of prospect engagement— human, machine or a combination of both— and coordinate assistance seamlessly.
- Boost productivity: AI can review all data on a customer to advise the agent on the best sales opportunity to pursue next.
- Improve service quality: Because AI can sort through and access customer data faster than humans, it can generate quick answers about prior policies purchased, filed claims, upcoming renewals and more.
What will be the future effects of AI on insurance agents’ jobs? The experience of robo-advisors in the registered investment advisor (RIA) space suggests they won’t be fatal.
Will Automation Replace Insurance Agents?
Most experts expect human insurance agents to be around for decades. Their role may evolve, but it’s unlikely agents will become obsolete. Here’s why:
- Human agents are better than machines at performing insurance needs assessments: Identifying insurance needs requires more judgment and nuance than computers are capable of at the moment.
- Computers are excellent at generating insurance quotes: However, human agents have a deeper knowledge of non-quantitative factors for why one insurance company may be better than another.
- Computers have automated parts of the claims-handling process: But human agents can better advise clients on how to submit claims and negotiate with insurers.
- Service chatbots can handle routine service tasks: Yet, when consumers have an urgent matter to address, they will typically appreciate dealing with an empathetic human agent.
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