Just like all the other industries, AI in insurance is not just a trend, it is now the norm.

In the last couple of years, we've seen rapid advancements in AI, transforming any sector you can think of.

From healthcare to entertainment, AI has gradually become an essential tool for improving efficiency, reducing costs, and enhancing service delivery.

The insurance industry, known for its traditional long, boring paperwork, as well as repetitive processes and reliance on human intervention, is now experiencing a similar transformation thanks to AI.

In an industry built on data, risk, and predictions, AI offers new possibilities in the world of insurance.

Background

The insurance industry always relies on heavy data. It has always been known as a huge pain to deal with insurance and to file insurance claims. It's a hassle no one is ever looking forward to. But unfortunately, it’s a necessary evil that we must have in today’s world. Moving without insurance is like flying blind nowadays, it’s just a risk not worth taking.

Like other financial services, this data is what determines what type of insurance people receive and which premiums they are charged. AI comes in to determine the best predictions possible to determine how risky a person is to ensure and to predict and assess their situation.

In fact, the entire premise of insurance is to assess risk and predict future events based on historical data. With the increasing volume and complexity of data, as well as rising populations and the need for more people to be insured,  the need for more advanced tools to manage and analyze this information is more apparent than ever.

According to a report by Accenture, AI could save the insurance industry $1.5 trillion in claims and expenses by 2030. Furthermore, McKinsey & Company has predicted that AI adoption in the insurance sector could boost global profits by 20-30%. They have also reported that AI can contribute to the global insurance market more than $1.1 trillion in value.

As the demand for faster, more personalized services grows, the integration of AI in insurance is no longer optional, but it’s essential in order to compete with any business or service out there with advanced AI technologies boosting its service. But, like anything new, AI presents both opportunities and challenges. 

How It Works

There are several functions or applications of AI that insurance providers use in their services. These applications are basically what allows AI to work.These applications are APIs, Automation, Generative AI, Machine Learning, Natural Language Processing, and Optical Character Recognition.

APIs, while not an AI function, allow software applications to communicate with each other and exchange information. They help different parts in the machine to connect and collaborate with each other. It can connect users to third parties, and even the service providers themselves.

Automation is basically how it sounds, just doing all repetitive tasks and processes automatically. These tasks can be customer onboarding, claims processing, calculate payments, and even estimate rates and address compliance needs.

Generative AI uses large language models to help streamline tasks, like customer service or analyzing large documents or texts. It also helps some customer service representatives respond better to issues and customer claims.

The use of chatbots and virtual assistants is basically functioning on Generative AI. Gen AI has become so important in any industry. In fact, according to IBM, 77% of industry executives said that they needed to embrace Gen AI quickly to match their competitors.

Machine learning algorithms use data to allow AI to imitate the way humans learn and adapt, improving its accuracy and performance as time goes on.

MLA can be used to analyze customer data and provide recommendations for service providers regarding their customers and potential clients.

Natural language processing enables AI to basically speak the language. It allows the AI to understand and communicate using the human language or the lingo of the industry.

Certain key terminologies or phrases that exist within the industry, AI will know them and use them accordingly using NLP.

Optical character recognition, or text recognition as it is more commonly known, basically extracts data from images into text. For example, it will look at a person’s ID and extract information from it like name, birth-date, etc, and type it out on the systems, turning it into text information that is machine readable.

This is a very important aspect of insurance companies as processing this kind of information is basically step one in any insurance process.

Insurance

AI Use Cases 

AI is transforming the insurance game through many different ways. From underwriting and claims processing to customer service, AI applications are enabling companies to streamline operations and provide more tailored solutions to their customers. The main use cases of AI in insurance are:

Fraud Detection and Prevention

Fraud is one of the insurance industry’s biggest challenges. I mean, there are entire scam industries built on insurance fraud. It is a whole crime in itself. Insurance companies can lose millions, if not billions, from insurance fraud, and in the end this is just going to come out of the people’s pockets.

AI’s ability to read through massive datasets allows it to detect patterns and anomalies that would be impossible for humans to spot. Companies like Allianz are using AI to flag suspicious claims by analyzing historical data and identifying irregularities. In fact, AI has been shown to reduce fraud detection costs by as much as 30% while improving detection accuracy by 20%.

Examples of insurance fraud are false insurance claims by inventing accidents or exaggerating what actually happened. You can also falsify medical records or use other people’s identities. By using AI, it will monitor transactions, applications, and user behavior to detect fraud and prevent it in real time.

Claims Processing

Processing claims is a time-consuming task that involves reviewing complex documents and making decisions based on a lot of different factors. AI speeds up this process by automating document processing and analyzing data in real time. Instead of waiting days or weeks waiting for an insurance claim to be granted, this process can happen in minutes. AI will interpret and process documents and images, then come to a decision.

Additionally, AI will be able to generate a preliminary report and summarize the data of any given claim or situation.

In 2022, an insurance company, Lemonade, introduced an AI-powered claims processing system that can settle claims in just a few seconds without human intervention. We’re not talking about minutes here, but we’re talking seconds. How insane is that. This significantly reduced costs and improved the overall customer experience.

Customer Service and Chatbots

AI-powered chatbots are transforming customer service in the insurance industry. Rather than waiting on hold or speaking to a representative, customers can now interact with intelligent bots to get quick answers to their questions, file claims, or even purchase policies. According to a study by PwC, 75% of insurance customers are open to using chatbots for claims processing and inquiries.

According to a report by IBM, AI-driven customer service is projected to save the insurance industry over $1.3 billion annually by reducing the need for call centers and increasing operational efficiency. This allows insurance companies to focus on more complex customer issues while routine inquiries are handled by AI.

Risk Assessment

Risk management is perhaps the biggest key component when it comes to the insurance industry. Since profit is always a priority, if someone is a major health risk or suffers from a risky condition, of course they are going to be priced higher than a healthy young person. It is sometimes tricky to determine that using the available data, but now AI is taking care of it.

Before making a claim, insurers study a client to understand the risk they’re dealing with. To them, every client is a risk. In every type of insurance, the customer is assessed through large amounts of data from everywhere, hospitals, cars, and houses. These are all used to price their own policies and to basically anticipate any big surprises. 

Underwriting

Underwriting is the process of basically deciding the insurance policy you are going to offer an applicant and the appropriate pricing for it. This policy is drawn up after assessing their risk factor and how likely they are going to cost you as an insurance provider. Traditional underwriting relies heavily on manual processes and historical data to determine risk.

AI can enhance this process by considering a wider range of factors, including social media activity, data from vehicles, and health metrics from devices that you wear like smart watches. This leads to a more personalized pricing and more accurate risk assessment. AI also enables insurers to continuously update their models.

Benefits of AI in Insurance

The integration of AI into the insurance industry offers numerous benefits, making it an essential tool for modern insurers, and making it an early Christmas gift for clients that benefit from it.

AI-powered automation reduces the time needed for data processing, underwriting, and claims approval. This not only speeds up customer service but also cuts operational costs. AI can process large datasets in a fraction of the time it would take a human, enabling insurers to respond faster to customer needs.

Now, the customer doesn’t have to spend weeks fighting with their insurance provider over a claim. The matter is resolved instantly through the use of AI.

AI allows insurers to offer more personalized policies by analyzing customer data and behaviors. With machine learning, insurance companies can segment their customers more accurately and design policies tailored to individual needs.

This level of personalization can lead to higher customer satisfaction and loyalty. You now don’t have to feel like you’re being cheated by your insurance provider. AI will do you justice.

By automating routine tasks and improving risk assessment, AI helps reduce administrative and operational costs. In fact, a study by PwC found that AI could reduce underwriting costs by up to 40% and claims processing costs by 50%, leading to substantial savings for insurance companies.

AI can assess risk more accurately by analyzing a wider range of datasets, allowing insurers to make more informed decisions. With real-time data analysis, AI helps insurers identify emerging risks faster and take preventive measures, ultimately improving overall risk management, which is basically the name of the game.

Challenges of AI in Insurance

As always, nothing is perfect. AI still has several weaknesses and poses a few risks. But you would find that even with these challenges, the benefits greatly outweigh the setbacks. 

As with anything online, security is always a risk. AI requires vast amounts of data to function effectively, but this data often includes sensitive personal information. Ensuring the security of this data is a significant challenge. Insurers must implement complex security measures to protect customer privacy and comply with data protection regulations.

AI can also be biased. AI algorithms can sometimes reflect the biases present in the data they are trained on. If historical data contains biased patterns, AI may perpetuate these biases, leading to unfair decisions in underwriting or claims processing. Insurers must ensure that their AI systems are transparent and regularly audited for fairness.

In fact, this opens up a space for abuse. Just recently, United Healthcare were accused of intentionally using AI to deny medicare claims. This is also largely what people fear about AI, is that it is used for personal motives and agendas, but you can argue that anything can be abused in the same manner.

The insurance industry is perhaps one of the most highly regulated industries, and AI adoption must comply with numerous laws and regulations.

From ensuring transparency in AI decision-making to protecting consumer rights, insurers must abide by a complex regulatory sea, and sailing it might not be easy, especially with the dynamic change of laws regarding AI today.

The final challenge is basically just evolution. Many insurance companies still rely on outdated software systems, which can be difficult to integrate with new AI technologies. Transitioning to AI processes requires significant investment in infrastructure and training, which can be a barrier for some insurers, and some people just aren’t up to the task.

Conclusion

AI is not just a trending word in the insurance industry, it’s a game changer that is here to stay. From underwriting and claims processing to customer service and fraud detection, AI is improving efficiency, cutting costs, and transforming how insurers operate.

However, as with any technological shift, the road to AI adoption is not without challenges, but this shouldn’t deter any companies from seeking to adopt it.

The future of AI in insurance looks promising. As the technology continues to evolve, the potential for more innovative and personalized insurance products is vast. In fact, there is an entire use case dedicated to applying AI in any new products or developments.

For companies looking to stay competitive in an ever changing dynamic world, embracing AI is no longer a choice, it’s a necessity, and in insurance, you snooze you lose.

By taking advantage of AI’s capabilities, insurance companies can streamline operations, reduce costs, and provide better, more personalized services to their customers. The question now isn’t whether AI will shape the future of insurance, but how quickly insurers will hop onto the trend before everyone else to be ahead of the race.

Interested in getting ahead and adopting AI? Book a free consultation with experts and get started.