How Artificial Intelligence (AI) Is Used in the Insurance Sector?

Artificial intelligence in insurance

The capabilities of artificial intelligence cannot be overestimated. The technology has made its presence felt in a variety of industries, the insurance sector being no exception. But how exactly is AI set to help insurance companies make the grade?

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Artificial intelligence has demonstrated an impressive capacity to bring about meaningful transformation in any business domain, from supply chain and healthcare to retail and education.

Insurance companies worldwide have rushed to embrace this sophisticated technology too, and have successfully leveraged it in multiple processes and operations.

The demand for artificial intelligence among insurance businesses is bound to rise, and it is expected that the global market for AI insurance will reach $45.74 billion by 2031.

Read on to find out more about artificial intelligence in insurance, its benefits and applications, and check out the top 5 AI use cases in the insurance sector.

What challenges does the insurance sector have to deal with?

Over the years, the insurance sector has traditionally faced numerous issues, the most common being inefficient processes, insufficient security, rising operational costs, excessive use of outdated systems and solutions, and chiefly, an overall reluctance to change.

On top of that, according to a 2023 insurance outlook report from Deloitte, the industry has been directly influenced by other global and socio-economic challenges such as rising inflation, interest rates, and loss costs, along with the looming threats of recession, climate change, and geopolitical upheaval.

What are the benefits of leveraging artificial intelligence in insurance?

Leading-edge technologies such as artificial intelligence, machine learning, and computer vision can help the insurance industry face its challenges and streamline its operations as well as bringing a host of benefits such as optimization of operations, providing an enhanced customer experience, reducing costs, and supplying an enriched data pool.

Workflow optimization and automatization

With AI-powered tools, it is possible to set different insurance processes on autopilot. For example, by using AI-enabled chatbots, customer support agents can substantially reduce their response times and focus on more important tasks that require their involvement.

Enhanced customer service and experience

The optimization of processes results in better customer service and outcomes since the quicker a client has their request addressed, the more satisfied they will be.

Importantly, the clustering methods of AI also empower businesses to better understand their customers and even deepen their segmentation, which comes in handy in directions such as determining customized pricing policies and adopting preventive anti-churn measures.

Reduced costs and loss ratios

By implementing AI algorithms, businesses stand to cut down on the unnecessary spending that is often caused by human error. In addition to this, machine learning tools are capable of detecting fraudulent activities in time, helping insurers to avoid huge losses.

Enriched data pool

Artificial intelligence empowers insurers to collect and operate with more significant amounts of data and create sophisticated predictive models. These can help gain detailed information about consumer requirements and pull out valuable insights for producing fully-fledged solutions of the future.

Besides, by relying on computer vision, insurers have the ability to effectively collect underwriting data and uncover previously untapped sources of information.

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Top 5 use cases of artificial intelligence in insurance [2023]

To better understand how exactly artificial intelligence benefits insurance businesses, it is necessary to look into the most transformative use cases and see how the technology helps insurance to upgrade to a whole new level.

1. Artificial intelligence in claims management

Insurers can utilize advanced AI algorithms to boost the operational efficiency and accuracy of the entire claims management cycle, from registration to settlement.

Natural language processing (NLP), a branch of AI, is perfectly capable of processing gigantic amounts of policyholder and claims data and extracting valuable information from language-based documents. Thanks to NLP, insurers can better organize and operate with their data and make more informed decisions.

More applications of AI, such as machine learning and predictive models, empower insurers to acquire a clearer picture of claims costs, which enables them to save enormous amounts of money through the fast settlement of claims and more effective case management.

In addition, 87% of policyholders who took part in the EY Global consumer insurance survey admitted that the claims experience impacted their decisions to remain with insurers. With this in mind, it is wise for insurers to start thinking about the implementation of AI in their claims management processes so as to retain their customers and win their loyalty.

2. Artificial intelligence in customer support

By using AI-enabled chatbots, customer support agents can bolster their response times, which results in better customer service and outcomes. The majority of interactions with policyholders can be executed via AI-based customer service apps that are reliant on self-learning scripts interconnected with different internal systems.

Essentially, insurance companies can make use of AI-enabled claim processing bots to allow their clients to easily and quickly report their claims and record any damage, substantially simplifying the communication and reporting process.

3. Artificial intelligence in fraud detection and prevention

Fraudulent claims have been a critical issue for insurers worldwide, causing billions of dollars of losses. This comes as no surprise at all, since the vast majority of insurance companies are still reliant on obsolete rule-enabled platforms that are not good at spotting sophisticated fraudulent claims. Meanwhile, the more fraud insurers have to tackle, the more money they lose in the long run.

Artificial intelligence and machine learning can help reverse the situation by enabling insurers to detect and prevent fraudulent claims faster and much more accurately. ML and AI algorithms are able to tap into unstructured and semi-structured data, including claim notes and other documents in order to spot and analyze possible frauds that are oftentimes invisible to the human eye or an outdated system.

4. Artificial intelligence in underwriting optimization

The combination of machine and deep learning models speeds up the execution of underwriting to just a few seconds. These models are based on internal and external datasets (e.g. information collected from product distributors and manufacturers) and can be accessed via APIs as well as outside data and analytics providers.

Thanks to the insights gained this way, insurers can make better informed decisions regarding underwriting and pricing, which will benefit all stakeholders in the long run.

What’s more, computer vision coupled with the capabilities of the Internet of Things (IoT) empowers insurers to record the state of assets at the time of underwriting and to make any adjustments in real time.

5. Artificial intelligence for predicting customer churn

With artificial intelligence and machine learning algorithms, insurance companies can predict if their customers might leave, and take action accordingly.

AI is capable of effectively spotting changes in user behavior, e.g. frequency of interacting with customer support services or app usage. By extracting and analyzing such valuable insights, insurers can come up with ways to retain customers, which will allow them to reduce the customer churn rate and stay profitable.

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What do insurers need to know before embracing artificial intelligence?

Before adopting artificial intelligence in their core processes, insurers may encounter challenges such as lack of relevant expertise, unwillingness among staff to work with new technologies, fear of change, absence of a detailed strategy, insufficient security measures, and so on.

To avoid costly blunders and ensure the smooth integration of artificial intelligence into insurance processes, businesses need to take their time and make sure that they are armed and ready for a huge shift within their processes.

For example, McKinsey recommends insurers take the following steps to get prepared for accelerating change:

Keep a watchful eye on AI trends and technologies to be well aware of how the tech is revolutionizing and which AI solutions have proven to have a transformative impact on the insurance sector.

Create and start implementing a consistent strategic plan that includes a detailed and comprehensive roadmap of the AI implementation process and anticipates all risks and dependencies.

Map out and execute an all-encompassing data strategy that will cover multiple means of obtaining and securing access to external data, as well as methods of combining this data with internal sources.

Educate your staff and establish the right talent and technology infrastructure to augment your in-house capabilities and ensure your organization is ready to embrace artificial intelligence.

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Closing thoughts

Artificial intelligence is set to disrupt the insurance sector and introduce it to a host of benefits, namely optimization of numerous internal processes, an enhanced customer experience, reduced operational costs, and an enriched data pool enabling insurers to extract valuable insights.

Though AI is not a panacea for all of the issues that insurers have to address, it can help streamline numerous operations if implemented and leveraged correctly and wisely.

Should you want to incorporate artificial intelligence in your business, reach out to our seasoned AI/ML developers. By relying on our solid expertise and using an advanced tech stack, we will help you deliver a solution that will help you grow your bottom line and take your business to a whole new level.

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