‍How is AI transforming the insurance industry?

As per KPMG, almost 70% of CEOs globally are heavily investing in Generative AI to gain a competitive advantage and secure their bright future. This is a clear indication of the potential of Generative AI across industries. The insurance industry is no exception, as Generative AI is paving its way into it.

Insurance companies must see Generative AI as a unique opportunity to grow and improve their quality of service. In this blog, we will discover how AI can transform the insurance industry once and for all.

Insurance industry snapshot: current market trends 

More than half of the insurance executives, 55%, confirm that implementing technology is their top priority. This gives an overview of the entire insurance industry landscape and the direction in which it is growing. Here are some of the trends in the insurance industry to begin with:

• AI innovation

Among others, insurance companies are highly interested in AI innovation. Whether it is to improve business productivity or boost sales, there are plenty of ways AI can innovate how insurance companies work.

Natural language processing (NLP), conversational AI, sentiment analysis, and generative AI are among several key innovations of AI that can be relayed to different insurance applications. This will be covered in greater depth later in the blog.

Almost 68% of insurance and wealth management companies are either using AI, or using it on a pilot basis, or are considering the use of it. This number emphasizes the major trend among insurance companies and their prioritizing AI in it.

• Better agent retention

Poor staff retention leads to poor quality of service, this stands true for any company or industry. Unfortunately, the insurance company suffers from an almost 30% agent attrition ratio which brings major inefficiencies and additional costs to insurance companies. 

Better agent retention is the only way insurance businesses can survive and offer consistent quality of service. 

• Better customer experience

Even with such a vast burden on agents and manual support, the overall customer experience still suffers. Longer queues, lack of digital accessibility, and poor personalization still affect insurance customers. Improving customer experience could help companies get an edge over their competitors. 

• Improved operational efficiency

Insurance companies have to deal with a lot of operational challenges, including hiring new agents, training them efficiently, resolving customer concerns timely, and working on sales conversion. With the vast competition, these operational processes become vital for insurance companies to conduct efficiently.

• Managing compliances and regulations

Regulatory compliance for the insurance industry keeps updating from time to time. These compliances need to update as businesses and the industry keeps growing. However, the real challenge of the insurance industry is to keep up with these updates.

Especially the challenge for companies is to pass these updates to their agents, educating them effectively can be tricky. False comprehension of regulatory compliances can lead to misconduct and liabilities.

In summary, the insurance industry has been fighting on many fronts altogether to survive the competition. These key trends emphasize making life easy for insurance companies, agents, and customers.

Use cases of AI in the insurance industry

AI can be helpful in different areas of an insurance business. Depending upon how it is implemented, it can assist in several functions of an insurance company. Here are unique use cases of AI in different business functions:

Customer Service:

Customer service is a critical force behind any thriving business. Losing a customer would require acquiring a new customer to make up for that revenue, however acquiring new customers is comparatively costlier. Better customer service can improve customer retention and customer lifetime value.

Here are some use cases of AI in Customer service:

• AI chatbots and agents: AI agents can be a great aid to customer service operations as they can help manage customer inquiries by understanding their underlying queries and providing them with the right information about policies and claim processes.

• Sentiment analysis: AI can complement chatbots and agents by understanding the customer sentiments through their messages, emails, or conversations. It can assist insurance companies to address customers accordingly and improve their satisfaction.

• Personalized customer care:

71% of customers expect personalization when they interact with a company, and 76% of customers would be frustrated if they do not receive personalized care. In the insurance industry, the relevant user history, policy information, and regulatory compliance knowledge are several roadblocks.

AI solutions can help connect all these dots easily to provide customers with personalized and unique treatment, leading to better customer treatment and satisfaction.

Sales

Sales is always the root of the growth of any business. For companies to scale up, they must start by making more sales and outperforming their competition. Here are some use cases of AI in sales:

• AI for sales insights: AI can help empower insurance agents in their sales cycle by assisting them before, during, and after sales calls. AI can assist agents in gathering key insights about customers and suggesting the best solutions accordingly.

• Personalized targeted marketing: Sales and marketing is about efficiency. The use of AI can help understand the audience through different data points and market the solutions in a targeted manner. It can be essential in generating useful leads through a company’s marketing initiatives.

• Quicker sales conversion: The quicker the sales cycle, the better conversion ratio. AI can help sales agents through right recommendations, quickly drafting proposals, and generating marketing collaterals. AI’s assistance in these areas can drastically expedite sales conversation.

• Quicker ramp-up for sales reps: Training new sales agents is no way an easy task. It is critical to guide new agents with accurate practices so they can effectively nurture leads. AI can help with training and onboarding of the new agents so they can ramp up quickly and start giving results.

Self Support

AI can also help empower customers and agents so that they can be self-sufficient. Here are some of those examples:

• Self-support for customers: AI can help empower customers by providing them with AI chatbots and virtual assistants. These tools can help customers find answers to their questions and queries without the need for any support from insurance agents. 

Self-support for customers can be as easy as browsing through FAQs but would be much more personalized and accurate for their unique concerns. Customers can interact with an AI agent on a website to find the right information and bring leads that fit company offerings.

• Independent agents: Not only the customers, AI can also assist new agents by helping them find the right knowledge and information to function independently. AI assistants can be by their side throughout the customer interaction to share customer requirements, recommend the right policies, and even answer any doubts agents may have.

Such tools by the side of agents can make them much more productive and effective. This would allow agents to function independently without any dependencies from the senior staff. This gift can end up closing more sales by making every agent more productive.

Fraud detection

• Claim processing & anomaly detection: AI can also be helpful in gathering the customer details and documents. These pieces can then be processed with the use of AI to verify consistency through any claim application. Using AI, companies can easily process claims automatically to identify anomalies and frauds.

• Image processing and OCR: AI can help companies with image processing and optical character recognition to extract the details out of claim documents. Here AI can process them to verify their authenticity quickly and accurately. This would mean less frauds and quicker claim processing.

 Benefits of using AI in insurance

The discussed use cases demonstrate that AI can be used in several applications. All of which can bring unique advantages to insurance companies. Here are some of the key benefits AI presents:

• Eliminating long waiting queues and entertaining customers right away for instant care and customer satisfaction with the help of AI.
• Better customer experience with personalized and tailored interactions so that the customers can find answers to their queries.
• Recommending the right solution to the customer based on AI analysis of their needs and finding the best match.
• Assisting insurance agents in collecting customer requirements, transcriptions, and CRM data to help sell the right solution.
• Easier jobs for sales reps by reducing laborious activities and research work through AI assistance, bringing better agent retention.
• Organization-wide education for new and existing sales reps so that they can keep up with the latest regulatory updates.
• Training the new sales rep quickly and effectively. Alltius’ AI solution can reduce ramp-up time for agents by 67%.
• Raising median productivity by helping different areas of an AI business, bringing overall positive impact.

• Reaching higher sales conversion so that the agents are able to convert more leads into customers, possibly even without requiring as much hard work.
• Enforcing consistent customer care quality across the organization by assisting all human agents deliver a standard level of support.

• Automated claim processing can reduce fraud and anomalies in insurance claims, making insurance claim processing easier.

How can insurers prepare for implementing AI?

The effectiveness of AI is entirely about how and where it is implemented. It is crucial for insurers to better perceive and plan AI solutions. Without proper considerations, touchpoints, data filtering, and application interface, there’s a lot that can go wrong with an AI implementation.

1. Understanding the gap and prioritizing

First and foremost, an insurance company must start by making a list of challenges that they are facing. Once that is done, it boils down to prioritization. To start with high-impact challenges, companies can evaluate the potential and capabilities of AI.

Generative AI, natural language processing, recommendation engine, sentiment analysis, OCR, etc, are some of the branches of AI that insurance companies can understand and evaluate when applying them. CIOs or CTOs can enable their teams to evaluate such solutions.

2. Developing a strategic plan to implement AI

Insurance companies can devise a strategic plan as to how and where they can start implementing AI. Once an insurance company has decided to solve a particular problem, they can start defining the right AI suite or solution for their needs.

Once a set of requirements is drafted, companies can start evaluating their available options through ready-made, proven solutions or in-house developments. This is the crucial step to deciding the way forward. 

3. Execute a comprehensive plan for AI implementation

Once the company decides which problem(s) to solve and how, they can start investing in an execution strategy. This execution strategy for implementing AI can start with a solid proof of concept so that insurance companies can validate the solution beforehand.

Understanding different data points to collect information, filter data, feeding machine learning models, and training them from time to time would help an AI application function efficiently. Likewise, companies must make sure they have the right data and can add a third-party solution to their workflows perfectly if they choose to rely on a read-to-use solution tailored to a certain problem. 

Opting for a third-party solution makes sense for an insurance company. Going through an entire software development lifecycle would just lead to immense time and costs. On the other hand, solutions like Alltius’ sales enablement suite are very much tailored to solve the problems of the insurance industry.

4. Implementing the right solution & training agents

Insurance companies can find the best-fit solution to overcome their challenges and implement them within their processes. To do so, insurance companies must first educate their agents so that they can effectively leverage the abilities of AI, assisting them in their jobs.

5. Collecting feedback to improvise

AI implementations must ease the customers while they work with insurance companies rather than the other way around. Therefore, The last stage of AI implementation is collecting customer feedback within a set time frame. It can help understand how effectively an AI solution is helping customers or agents. 

To answer the question,

AI can transform the insurance industry to a drastic extent. If the industry leverages AI effectively, it can overcome all of its long-standing challenges. 

At Alltius, we have already helped insurance industry leaders overcome their challenges, including helping Assurance IQ enable their agents quickly, reducing the ramp-up time by 70%.

If you are still wondering how and if AI can help you, drop a message to discuss further.

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