AI’s impact on the Insurance industry 2030

Where the Insurance Industry stands for Digitalization

The insurance industry is highly competitive, and companies have been facing numerous challenges through the years. Unfortunately, it is too slow in implementing new technology in the work process.

However, the disruption from the pandemic changed the timeframe for adopting AI, accelerating the process of digitalization in insurance. Organizations were forced to switch to remote work mode. They had to expand their digital capabilities to support their processes and upgrade the company’s online platforms. The development of technology is reshaping customer experience and as result customer expectations are increasing. Nowadays clients demand a more personalized experience and efficiency that AI can deliver. To meet those expectations, insurers have to step out of their comfort zone and embrace the technological revolution.

The integration of automation will help the industry achieve great success. AI enables the automation of several elements to free up insurance agents to focus on complex tasks while improving accuracy and efficiency.

How AI trends will shape the insurance industry by 2030?

AI will have a huge impact on the whole insurance industry. New technologies and data have already affected some of the processes like distribution, underwriting, pricing, purchasing, and fraud detection. However, AI is going to bring fundamental changes. The result will be noticeable in customer offerings and the way of communication.

Data flow and product development are needed for a more personalized customer experience

Data is crucial for 90% of the processes, and every company, whether it wants it or not, has to become a data company. According to the report of McKinsey & Company, the next few years will bring a great increase in the number of connected devices. It is expected that by 2025 we will have more than one trillion connected devices. As a result, those devices will be able to understand customers more deeply and provide a more personalized experience and real-time services. The personalization will allow new features to be added to the existing products and services. Any data that consumers may provide from smartwatches and home assistants can be used for offering more customized insurance services.

The usage-based insurance (UBI) departs from the usual insurance model that clients are used to. Instead, UBI products continue to breed and adjust to the behaviour patterns of the individuals. These more customized insurance services transform from purchasing and renewal to a continuous innovation cycle, as products constantly adapt to the lifestyle, habits, and behaviour of the consumers. Moreover, customers will be able to customize services to their needs and compare the prices of numerous insurance providers.

Insurance sales Distribution is shifting to self-service rapidly

According to the findings in the report of McKinsey & Company concerning distribution, insurance companies will shift to self-service. Therefore, the purchasing of insurance will become easier and faster, as the process will require less interaction between insurer agents and consumers. Personalization will allow insurers to identify and prevent potential risks with the help of IoT devices. Smart contracts will facilitate payments directly from the customer’s financial account.

Underwriting could benefit significantly from an AI implementation

Underwriting is a complex process that requires a lot of research. According to a recent study, 50% of the executives claim that the automation of underwriting is one of the most important areas for a company’s growth. Even though they are aware of the importance of automating key processes, insurance companies are struggling in implementing AI. McKinsey has found that while some of the leading companies in the industry have begun the process of digitalization, most are failing in automating the underwriting process.

‘“The traction of many companies’ accelerated, or automated underwriting programs has been limited, largely because insurers have taken a cautious, incremental approach to scaling automated decision making. These companies opt for small improvements to their risk frameworks and processes rather than considering the potential to rebuild and take a more modern approach to underwriting.”, wrote McKinsey.

AI will provide new approaches to underwriting and predicting losses. In the coming years, the process of underwriting will be reduced to just a few seconds. (McKinsey) This will be possible because most of the process is automated and backed up by machine learning (ML) and deep learning (DL). Insurers will be able to use more sources powered by both internal and external data and analytics when making evaluations.

Traditional Pricing models won’t serve any more

“By 2030 the digitization of the incumbent insurance sector will be at a mature level, including some use of AI/ML across the value chain which leads back to what the differentiator will be for companies and ultimately who succeeds. When insurance products, pricing, and technology stop being that differentiator, the brand will be the deciding factor. But you can’t switch that on overnight like a chatbot. So companies need to make investments now, and many insurtechs are always way ahead in that space.” (Bikmo)

Customer decision-making heavily depends on price. Traditional pricing models which are based on simple matrix systems that use few variables, lead to high risks and huge loss ratios. According to McKinsey, AI will enable real-time pricing based on usage, dynamic, risk. Automation will let people make informed decisions regarding their coverage, insurability, and price. AI will help insurance companies to offer a more competitive price and personalize the individual experience.

Increase the efficiency and fraud detection of the claims

Claim processing is overcomplicated because different types of claims follow different processes and require the involvement of different departments. The process of claims starts with the customer reporting a claim and until it is resolved, the insurance company can prove itself. IoT devices and data-driven technologies automate manual methods of submitting a claim. Then the data will make a library of consequent events that can either direct the claim to the right department or complete the process automatically. In other words, from the moment of submitting a claim, AI can facilitate the administrative process through automation. Al, powered by ML, can easily spot fraud claims. IoT devices will be used by insurance companies for risk monitoring. According to McKinsey, consumers will receive real-time notifications for automatic interventions such as repair, maintenance, or inspection.

Conclusion

Companies need to understand that the integration of AI will take some time. The implementation of new technologies will give access to insurers to use data to their advantage. Insurance companies that successfully manage to become data-driven will flourish by improving both customer experience and internal processes.

At Digitech Consult, our mission is to help the adoption of AI and Analytics across the insurance industry and help companies achieve their full potential by closing the knowledge gap. Our team of experienced developers has worked hard to bring the best practices to help insurance businesses solve the challenges they are facing.

Contact us to learn more.