AI in the Insurance Industry

As with many sectors, the commercial insurance industry is changing significantly with the adoption of the latest advancements in artificial intelligence (AI). While AI has been around for a while, the current accelerated development is rapidly automating tasks that have traditionally required substantial time and effort – improving efficiency, enhancing customer service, and bringing new insight.

Much of the potential impact is due to advances in document processing, generating essential information from complex documents. AI can automatically extract key information from the industry’s myriad of complex documents and forms, greatly reducing the need for manual reviews and data entry. Whether comparing policies, summarizing carrier plans, or decoding highly variable documents like Loss Runs and Statement of Values forms, AI can become a trusted assistant to the important work of relationship-building and protecting organizations from risk.

Document processing can unlock and structure the information from essential industry documents as the first step. Then several techniques and tools can be applied to evaluate and use the resulting data sets, to identify the best plan options for customers, to understand historical risk, to optimize pricing, to underwrite policies and portfolios, and to improve customer service.

This article explores how AI is reshaping the commercial insurance industry, highlighting tasks that can be streamlined by AI techniques, while describing the cautions, concerns, and operational guardrails to observe.

Sample applications of AI in the Commercial Insurance Industry

Here are some specific tasks that AI has the potential to improve in the commercial insurance industry:

1. Comparing Employee Benefit Plans: Accurately and consistently extract benefit information from a wide range of carrier plan documents, even when they’re in varied formats, with bespoke tables, and use complex language. Plan information can be extracted and structured into spreadsheets or apps, for brokers to sell optimal plans to customers at renewal time without expensive, time-consuming manual labor every season.
2. Analyzing Property & Casualty Insurance Customer and Portfolio Risk: Though it is difficult, some AI models can analyze Loss Runs, Statement of Values, numerous ACORD forms, policies, quotes, and other documents. Properly used, the right AI solutions can allow firms to see and use highly detailed information without massive human time and effort to read the source documents. The data can be used in small instances, for pricing a policy, or in large views, such as in catastrophe modeling.
3. Underwriting Risk: Loss Run documents hold the information that describes risk exposure for customers and across broker portfolios. An advanced AI solution can understand the semantics and structure of Loss Run document information, to extract Loss-Run Data even with the enormous variability from one carrier to the next. This software can then create a structured data stream to enable more rapid and data-driven underwriting and pricing.
4. Insurance Submissions: AI techniques, along with workflow tools, can automate the submission process for various insurance coverages. Documents can be submitted and classified, and the data can then be normalized and compared, to enable policy choices and risk assessments, to more easily close the decision loop.
5. Insurance Analytics: AI models trained on historical commercial insurance data can quickly analyze a business's operations, location, payrolls, safety records, and previous claims, to generate quotes. The quoting process that once took agents hours can be reduced to minutes using the proper AI tools, properly configured and trained by skilled personnel.
6. Fraud Detection: AI software can detect fraudulent claims more efficiently by analyzing data for key patterns and anomalies.
7. Generating Certificates of Insurance: Every time a customer requires a COI to validate coverage for their business, someone must dig up the current relevant policy and complete a form. This simple, but cumbersome process is tailor-made for AI, which can extract the information and automatically connect to a tool to populate the form, freeing up staff for more strategic work.
   
8. Compiling Insurance Quotes: Deconstructing disparate carrier plans and quotes so producers, renewal analysts, and account executives have the spreads they need to make the sales.
   
   

This is just a start. Each organization has unique business processes where artificial intelligence can play a role.

However, most organizations today are aware of the cautions that need to be addressed along the way, as this latest technology is being considered and operationalized. For example:

• Capability: Is the technology adaptable to handle a variety of complex documents with various structures and data patterns, or is it limited to certain predictable, programmed forms?
• Security, Confidentiality: Does the AI processing occur in a secure technical manner with appropriate data security safeguards? Is the modeling or training being shared with other organizations or kept uniquely for each client?
• Trust, Transparency: Where is the source of the information generated? Is info being pulled or influenced by data outside the organization? Can you easily confirm the sources?
• Development Difficulty, Expertise, Cost: Are there special skill sets required to implement the technology? Are there specific programming, development, or IT steps to implement? What is the potential time and cost involved?
• Operational implications: Is the organization prepared to validate the results? What ‘human in the loop’ effort and expertise is required? Does the organization have a plan for utilizing the data, and driving specific insight with the generated results?

Will AI replace Insurance Agents or other Professionals?

Given these advancements and cautions, it's natural to wonder, will AI technology take over the role of insurance personnel?

These changes may seem alarming to insurance professionals who have built careers around traditional roles and responsibilities. But while AI undoubtedly has useful applications in insurance, it's important to recognize the limitations of AI alongside its strengths.

Successful insurance agents rely on their industry experience, emotional intelligence, interpersonal skills, and the ability to build trust with clients—qualities that AI does not address at all. Professionals excel at understanding clients' unique situations, offering empathy, and providing personalized insight and guidance. Although AI assistants are becoming more sophisticated, they don’t replace but support the nuanced communication and relationship-building required in the industry.

The future of insurance is certainly to be one of greater productivity, where technology enhances and expands, rather than replaces human expertise.

By automating time-consuming tasks, AI frees people to focus on higher-value activities, such as building and maintaining customer relationships. While AI can identify and quantify potential, statistical risks, it is human judgment that contextualizes these risks and devises innovative solutions. For instance, explaining complex policy details or negotiating terms with underwriters requires a level of adaptation, empathy, trust, and nuanced communication that AI doesn’t address.

As AI takes on routine tasks, insurance agents have the opportunity to focus on more strategic activities. They can devote more time to helping clients navigate an increasingly complex risk and risk-mitigation landscape, offering tailored solutions. In this way, AI can augment personnel, enhance job satisfaction, and improve customer outcomes.

AI platforms can act as advanced decision-support tools for agents to enhance their work through automation, data-crunching, and analytics capabilities that support human efforts. The AI handles data-heavy analyses like automated data extraction, risk modeling, and quote generation, while the human provides high-level reasoning, advice, a personal touch, and ultimately makes the decisions.

Just as new technologies have enabled in the past, there will be leaders, laggards, new risks and new rewards and new elements to learn and build, that invite thoughtful approaches to adoption.

Benefits of Integrating AI Into the Insurance Industry

Integrating AI into the commercial insurance industry offers numerous benefits to carriers, brokers of all kinds, industry personnel, and customers:

• AI can process large volumes of documents and data at speeds far greater than human capabilities – with great accuracy and at lower operational costs.
• By automating routine tasks, AI reduces the need for repetitive tasks. Insurance personnel are then free to allocate resources toward more strategic areas that require human expertise.
• AI software improves the customer experience by improving access to information, shortening the response time for inquiries, processing claims faster, and providing policy recommendations.
• By analyzing previously untapped data and identifying trends, AI helps insurers make more informed and strategic decisions.

Thoughtfully adopting and integrating AI can streamline operations, enhance decision-making, and improve the customer experience within the insurance industry.

Conclusion

AI is undeniably transforming the commercial insurance industry. This important, inevitable shift offers organizations an opportunity to take advantage of the productivity benefits, or the likelihood of quickly falling behind. This is a choice and path that will be present at the personal and corporate levels.

Thoughtful adaptation to change is the foundation of the commercial insurance industry, and the opportunity and challenge to harness the new Artificial Intelligence tools is simply one more global, industry-wide example.