The Insurance Industry in a New Era of Artificial Intelligence

The evolution of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) has transformed many industries, with huge shifts in the insurance industry as well. Yet, not every insurance company has adapted to this change. 

Late into the adaptation game or not adapting at all is a waste of potential revenue. In fact, there is a worldwide untapped potential revenue pool of $375 billion till 2023. However, this opportunity is only available to what Accenture terms as “Living Businesses”, where insurers are able to work around the needs of their clients and continuously adapt to change.

With AI, the various processes and procedures can be streamlined to become a more efficient one. This includes the use of AI in risk assessment, designing of insurance policies, underwriting and claims management, as well as fraud detection.

7 in 10 business leaders acknowledge AI is vital to staying competitive.

But only  26% have taken action.

If you have not incorporated AI into your business, it is high time to take action to ensure that your company gains an edge over your competitors. Adaptation is key to winning the profit game and if AI can give you a headstart, why not leverage it and make yourself more competitive?

Ways to use AI to gain a headstart in the insurance industry

1. Risk Assessment

Risk assessment is the identification of risks or events that can cause potential harm. It is needed in order to offer the most suitable products for your clients. There is always a risk involved in insuring the client, and the degree of risk depends on how well you know the client. 

By being able to understand your clients at a deeper level, it will be easy to profile them and assess their risk levels. For the company, offering a low-risk product to a high-risk client may come at an expense of frequent claims, serving as a financial burden. For the clients, being offered an irrelevant product will not benefit them. As such, it is important to accurately assess the risk level of each client to provide them with the best service and product. 

Thanks to the IoTs, information about objects, people, or even their health are made accessible due to the digitization of these data. Technologies such as wearables and sensors allow us to collect real-time information about subjects without having to do so manually. With these data, AI and its complex algorithms can easily analyze it and derive insights related to clients.

For example, with the insights derived, it will be a lot easier to determine the best health insurance policies for clients. Moral hazard is common where clients tend to expose themselves to more risk upon knowing they are insured. However, this is a heavy cost that insurance companies must bear. Using wearables such as fitness trackers, insurers can easily monitor their clients’ lifestyles and health habits. Those who are identified as low-risk of health problems can pay lesser premiums while those identified as high-risk clients will incur higher premiums. 

Risk assessment can be done with higher accuracy and in real-time, allowing insurers to offer the best policies and adjust the premiums accordingly. By segmenting clients based on their risk levels, insurers can target each individual with more personalization and better customer service.

2. Policy Designing

Your clients are unique individuals. What may work for one client may not work for the other. That is why customizing policies to target each client individually is needed to ensure that clients are provided with the most suitable and relevant policies. 

With the ability to profile clients accurately, insurance companies can use this data to draw deep insights from their clients and get a clearer picture of their insurance needs, lifestyle habits, and life stages. Such a clear customer profile will allow insurers to design policies for clients specifically based on their personal information and needs. 

With more personalized insurance plans, clients will be better taken care of. Moreover, this allows for a dynamic pricing strategy, where the ability to assess each client accurately enables flexibility in pricing based on the clients’ needs.

3. Underwriting and Claims Management

Insurance claims are made every single day, be it for a healthcare policy or for accident-related claims. Regardless, traditional insurance companies are still relying on manual assessments of claims and this is a highly time consuming and inefficient process. Moreover, the manual assessment of damage is made purely by personal judgments, so there will always be concerns on biases and inaccuracies as these will result in wrongful claims.

Instead, AI and ML can accurately assess the severity of damage based on data in real-time. For example, if a client is involved in a car accident and needs to submit a claim for the damaged vehicle, image recognition algorithms can come into play to give a more accurate assessment. The client can simply take a photo of the damaged vehicle and send it to the insurer, or submit it through an app. The technology will automatically analyze the photo to determine the severity of damage and the cost of repair and provide a recommendation of the claim accordingly. All this can be done within a matter of minutes, boosting the efficiency and accuracy of the claims process. Imagine the amount of time and resources that can be saved. 

4. Fraud Detection

In the US alone, fraud claims makeup $80 billion a year across all lines of insurance. To put it simply, a fraud claim occurs when a claimant attempts to deliberately put himself/herself at risk in order to obtain benefits under the policies. Not only are fraud claims illegal, but it is also a heavy cost for insurance companies to bear.

In some cases, fraud claims may be detected by the insurer. However, manual detection may not be efficient. To combat this problem, AI-driven predictive analytics technology can be depended on to process claims, uncover insights and identify fraudulent or inflated claims. With algorithms set, claims can be analyzed and suspicious claims can be easily flagged out, such as claims made just before policy maturity or multiple claims made for 1 policyholder.  

Putting in place protection measures to protect the insurance company from unnecessary spending is important. Fraud detection at a more accurate and larger scale can be easily achievable with AI-driven technology, and fraud prevention measures can be put in place before it is too late.

Opportunities lie ahead with AI

The insurance industry is continuing to grow and opportunities for profitability are never-ending. 90% of insurance executives state that they have a coherent, long-term plan for technology innovation in place. Digitization is happening in this industry and it is happening fast. Many have acknowledged this and it is time that you implement this in your business.

Integrating AI into daily operations and procedures can give you a competitive advantage over others. With the potential to digitize certain services and reduce manual labor, processes can be streamlined to increase efficiency and to provide better customer experiences.

At groundup.ai, we will support and guide you through the process of implementing such systems into your current operations to create revolutionary changes to your business and use innovative solutions to drive business value in the long run. 

Request a call from us today to find out more.

 

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