While almost all insurance companies have adopted some form of "traditional" AI and have felt somewhat let down by the lack of transformative change that was promised in the past, there is no doubt that Generative AI has kicked off a tidal shift across the industry that will far surpass previous expectations.
In fact, the Boston Consulting Group estimates "that up to 35% of customer service agents’ time is spent retrieving information in policies, terms, and other documents. In such tasks, GenAI can more than double agents’ productivity." In addition, the consulting firm sees "considerable efficiency gains of 20% to 30% [that] can be achieved through streamlined documentation."
While Generative AI is most effectively implemented by completely rethinking and redesigning a contact center's operating model rather than approaching it use case by use case, we have seen insurance companies we work with evaluate the impact that AI could have on their operations by looking at examples of how you could use it.
When a customer calls to apply for a new insurance policy, they have to provide a lot of personal and financial information to the contact center. The conversation will also involve other important details, such as the policy preferences, coverage details, and more. This process is often lengthy and complex.
Generative AI-generated call summaries (also called Auto Call Summaries) can help streamline policy underwriting and insurance application processing in three distinct ways:
Auto Call Summaries summarize the call within seconds, highlighting key information from the conversation. Because prompts are written in natural language, they are fully customizable to what you need. In this case, the call summary could include details like customer name, age, medical history (for health and life insurance only), driving records (auto insurance), beneficiaries (life insurance), coverage preferences, and more. The automatic extraction of this important information saves time and reduces the likelihood of human error and accidental omissions.
Screenshot of the MiaRec AI Call Summary feature, showing the Summary of the Insurance call with structured summary, key facts, indicating call type and product and showing customer sentiment.
With key information readily available and organized, the application processing becomes faster as it cuts out the constant back and forth between the application processing department and the contact center to get missing information. This leads to quicker policy issuance, enhancing customer satisfaction and improving the efficiency of the insurance contact center. Also, agents will receive their commissions faster as most insurance agents receive commissions upon issuance of a policy.
Agents typically need to manually enter customer information into databases or application forms. Auto Call Summaries can partially or fully automate this process, reducing the workload on agents and minimizing the risk of errors in data entry. And if errors are made on the application and they are caught by processing/underwriting, the application can be quickly kicked back to the agent to fix the errors and get them resigned by the customer.
Another example where Auto Call Summaries can be very helpful is in claims processing. Insurance claims, whether they are for health, life, or auto insurance, involve detailed conversations where customers provide critical information about the claim event, such as the date of an incident, damages, injuries, or other relevant circumstances. These details are vital for the claim’s assessment, approval, and processing.
These calls often contain an enormous amount of details and bits and pieces of information. The agent is trying to capture everything while trying to remain calm and collected with a customer who might be very upset. Auto Call Summaries ensure that all the required information is accurately captured.
A screenshot of the MiaRec AI Call Summary feature shows the summary of the health insurance call with a structured summary and follow-up items after the call.
Oftentimes, follow-up calls are required from claims-processing teams to verify certain information regarding the customer’s claim. Because Auto Call Summaries capture all the pertinent information, the need for follow-up calls to clarify or collect additional information is significantly reduced.
With key information neatly summarized and accessible, claim processors can quickly review the claim’s specifics without needing to listen to entire call recordings. This expedites the decision-making process.
Training new agents in the insurance industry requires exposing them to a diverse range of scenarios, including policy inquiries and claims processing. Real-life examples play a crucial role in this training process.
Auto Call Summaries offer a plethora of real-life situations that new agents may come across. This encompasses frequently asked questions, intricate inquiries, claim particulars, policy modifications, and much more. Training with these scenarios equips agents to handle the wide array of situations they may face.
Agents should possess a comprehensive understanding of policy details. Summaries of calls that delve into specific policy information prove invaluable in aiding new agents to effectively communicate these intricacies to customers.
Generative AI-generated call summaries are a game-changer for insurance companies in improving their operations. From faster policy underwriting and application processing to streamlined claims processing and enhanced agent training, the benefits are evident.
The ability to extract key information from customer conversations in a matter of seconds not only saves time but also reduces human error and improves overall efficiency. What makes Auto Call Summary even more impressive is its full customization, allowing it to be used in various ways where extracting vital information is essential.
If you want to experience the transformative power of Auto Call Summary firsthand, I encourage you to start a trial and witness its impact on your insurance operations.