All of these entities and more will realize the remarkable value offered by increased hyper-personalized experiences, improved risk assessments, and data processing that AI provides to the customer experience.
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<\/div>\n\t\t\tAI and Insurtech \u2013 How Do They Work Together?<\/h2>\n
AI is not exactly new in the insurance industry and many of the tools that insurers use to operate effectively have been around for some time. What\u2019s changed recently is the significantly increased quality, quantity, and range of the tools available.<\/p>\n
The average insurance company can now be expected to use technologies like predictive modeling and machine learning (ML), contact center operations, claims processing, data forecasting, and risk modeling on a routine basis. The result is updated tools that are no longer just all-encompassing AI, but instead, AI for insurance only.<\/p>\n
AI in the insurance industry truly took off as a zeitgeist phenomenon when Chat GPT launched. Within two months of its public release, Chat GPT amassed over 100 million users. This in effect signaled mainstream acceptance of generative AI, a technology that can be used to identify patterns in data and draw inferences or projections from the findings.<\/p>\n
Insurance companies (and others in different industries) began to realize that by using large language models (LLMs)<\/a>, they could use generative AI to create content like interactive simulations, literature, images, music, coding, art, photographs, and the list goes on.<\/p>\n Tools like generative AI<\/a> offer insurance companies a simple route towards increased operational efficiency while also significantly improving their customer experience in the same process. It is a win-win scenario.<\/p>\n AI and ML combined will be able to analyze images posted on a client\u2019s social media pages to identify their risk profile, their interests, and associated products insurers may be able to provide to them. Predictive modeling based on several AI insurance technologies will be able to enhance forecasting for sudden events like natural cyberattacks and natural disasters, enabling insurers to take action to reduce their risk. Examples abound of the use of artificial intelligence in insurance.<\/p>\n Regtech is also playing an increasing role in determining how banks and insurers operate<\/p>\n Some of the examples outlined above highlight the benefits of the proper application of AI in insurtech but it\u2019s worth recapping them in more detail. Successfully adopting AL\/ML systems, along with other important tools, can be a difficult process especially if you are having to make the case for increased new technology for your team. If you\u2019re in that position, now or in the near future, then this list should help refine your argument.<\/p>\n AI for insurance is excellent at improving your risk assessment processes in many ways, not just in the example outlined above though it does provide a good indication. Factors including telematics<\/a>, remote sensors, satellite photos, digitized health records and more can be thoroughly analyzed using AI\/ML systems. This helps ensure that insurers do not grant or undertake policies with unreasonable risk, providing them with much more insurance than was previously possible.<\/p>\n Something to highlight for insurtech AI startups looking to maximize their efficiency is that AI technologies significantly improve claims processing for all involved. That\u2019s because it examines vast amounts of data more compared to the average human, and decides on the validity of each claim, while also acting as a virtual insurance agent if required. In time, AI-driven deep learning ensures that this data can be used to create detailed consumer profiles, which can be used to create more attractive policies and services.<\/p>\n Insurance companies have to contend with a huge amount of compliance regulations particularly in the American healthcare industry, which proves a particular challenge for those teams still working with outdated legacy systems. By utilizing AI in insurance workflows, designed specifically to deal with the vast compliance regulations insurance companies are subjected to, you can make the process almost entirely automated. More compliance legislation is a certainty and this will also insure you from major regulatory changes in the future.<\/p>\n So far the article has covered the general points about why AI in insurance works for so many companies in our industry, now you can examine how it improves the customer experience more specifically. As it\u2019s often the first process a customer will encounter with AI it\u2019s important to be sure it\u2019s a productive and enjoyable one. Clients used to long waiting times and outdated automated telephone systems will appreciate your company more if it goes through adopting new tech like AI.<\/p>\n For insurance companies, meeting their net producer score (NPS) targets is absolutely crucial; it\u2019s a hallmark that highlights the quality and application of the services you provide. NPSs are affected by many metrics, ranging from purely statistical claims processed to more intangible issues like the customer\u2019s feeling of appreciation or lack thereof. AI-driven data analysis can improve the results of the former, and generative AI can ensure that the customer\u2019s overall experience is individualized and efficient at the same time.<\/p>\n Your customers will appreciate how streamlined your processes become after combining AI and insurance, as every engagement they\u2019ll have with your company will become simpler and less stressful. Conversational AI can ensure their interaction with your chatbots is meaningful and effective; they\u2019ll be able to enjoy better policies via improved data and analysis; and it\u2019ll be easier for them to submit evidence for claim processing. Every part of the customer experience is boosted by AI in insurtech.<\/p>\n Insurance customers frequently report their frustration when they want to make a relatively small claim on their policies, only for the process to take an unreasonable amount of time. This is usually due to the underwriting having to be overseen by a customer agent, who often has numerous hoops to jump through and paperwork to fill in to ascertain the severity of any damage involved. Thanks to AI, the vast majority of small and routine claims can be automated, making the overall process much smoother for customers.<\/p>\n Other technologies are going to play an important role in the insurance this year too<\/p>\n AI in insurtech is comprised of a large number of technologies, and while they are all interrelated with one another, they also operate as distinct elements to provide value to companies and customers alike. This is particularly apparent in the customer experience process, where various related innovations are siloed into specific processes.<\/p>\n Three areas highlight this particularly, namely AI chatbots for banking<\/a> and insurance services<\/a>, AI-driven personalization used in the generation and updating of service offerings, and machine learning that\u2019s used during claims processing. The Intellias team has worked on developing each of these factors for its clients, so let\u2019s examine them in more detail.<\/p>\n AI-driven chatbots carry out a multitude of specialized activities by generating conversations that seem more human-like and can be employed in thousands of encounters at once. By utilizing machine learning to harness natural language processing (NLP) and offer round-the-clock customer care, they can greatly enhance the user experience and make it simple for clients to obtain the banking services they require, whenever they need them. This makes them particularly popular with younger customers.<\/p>\n AI chatbots can competently process up to 80% of the average customers\u2019 requests, while insurance companies still need to rely on human staff members to help with the most complex 20% of tasks. This ensures that the cost efficiency of this AI-based technology is tremendous as your human employees can focus more on technically difficult or important transactions. As such, they highlight the ultimate efficacy of using AI in insurtech, not by replacing humans, but by helping them better focus their time.<\/p>\n While it\u2019s well known that AI in insurtech relies on a prodigious amount of data and analytics, what\u2019s less apparent to those coming to grips with new technology is how the results of this process can be applied to customer personalization. The vast amount of data collected by AI and machine learning, as well as other tools, can be analyzed to create far more detailed pictures of customers than was previously possible.<\/p>\n Insurance has historically been a \u2018one size fits all\u2019 industry, with offerings and services based on the average customer profile, but thanks to AI, this is beginning to change. Through the data-driven analysis of AI processes, insurance companies can create policies, services, etc. that are significantly more relevant to the individual customer.<\/p>\n Instead of providing travel insurance based on a customer\u2019s age and travel destination, for example, insurance companies can now also take their lifestyle, hobbies, and interests into account to create a more detailed risk profile. The customer would then receive more value for money, while the insurance company would cover itself from increased exposure as well.<\/p>\n While machine learning can be applied to the personalization process, it\u2019s also useful in the claims processing process as well. While this might seem like more of a benefit to the companies that use AI in insurtech, it also has numerous benefits for the overall customer experience. Nobody loses out on increasing efficiency during the underwriting process, automated claims analysis that can lead to significantly quicker payouts, and improved fraud detection processes.<\/p>\n For example, customers frequently report that many of the fraud detection processes currently employed by insurance companies makes their customer experience laborious and time-consuming, with some suspecting (erroneously) that they\u2019re designed that way to discourage claims. Machine learning and other tools can be combined to significantly improve the security process. This will help ensure customers feel confident in making claims, that the processing time is limited, and that they receive good-quality service.<\/p>\n Are you curious about how the wider financial services industry will shape up this year?<\/p>\n You can see the clear advantages of using AI in insurtech both generally and to boost the customer experience you can offer. The benefits are too numerous and too effective to ignore. However, while many sections of the industry are characterized by their embrace of progressive and forward-thinking initiatives, change in any part of the financial services sector can still be slow and challenging.<\/p>\n This can make it difficult for individuals responsible for digitization at insurance<\/a> companies to affect major change and ensure their team fully embrace AI-driven technologies. If that is a situation you find yourself in, then don\u2019t worry, as we have encountered this issue frequently and it is easily overcome, starting with your ability to highlight how AI will benefit your insurance company.<\/p>\n When you start onboarding AI in insurance technologies there will be two groups at your company that will likely be most affected: your clients and your internal teams that work with data regularly. In this case, your onboarding processes should focus on solutions that provide high-level data storage, which is essential for your new AI-driven systems to create as highly personalized responses as possible.<\/p>\n This will allow your data infrastructure to provide rapd reaction times for fetching data and routine requests and will also ensure that the personalized offers you\u2019re able to provide to new and existing customers are as detailed as possible. Remember, the more data you collect and process, the greater amount of personalized and quality offerings you\u2019ll be able to offer.<\/p>\n According to Stratflow, nearly 90% of insurance companies are already working with AI technologies<\/a>, are currently implementing them, or are planning to do so in the near future. Failure to take advantage of the benefits of AI-driven technology in this environment means that you risk falling behind as your rivals continue to use AI to expand their offerings and capture new customers with significantly improved customer experiences on offer.<\/p>\n Therefore, when you start adopting and integrating AI-driven technologies into your company’s infrastructure, you should keep two things in mind.<\/p>\n Firstly, consider the needs of your customers when adopting new tools as this will not only help you shape your AI portfolio but will have the added benefit of improving your company\u2019s brand.<\/p>\n Secondly, you should seek the support of a dedicated AI technology service that can provide you with expertise needed to ensure the adoption process goes well.<\/p>\n AI will change everything we know about the insurance industry, it\u2019s a revolution that\u2019s taking power and it\u2019s time for you to join. Learning about, adopting, and onboarding new technology can be a challenge, especially if you\u2019re relying on legacy systems, but it\u2019s one that you can overcome with our support. The Intellias team has the expert skills you need to make that happen.<\/p>\n Customer experience is at the heart of providing an insurance service<\/a> that is sustainable and can continuously attract new clients. Whether it be for travel, healthcare, or any other type of insurance, AI in insurtech will boost your customer experience to levels you never that were possible. All you need to do to take advantage of this is engage with our experts and in no time at all, you\u2019ll see the results.<\/p>\nWhat Are the Benefits of AI in Insurtech?<\/h2>\n
Improved Risk Assessment<\/h3>\n
Increased Claims Processing Efficiency<\/h3>\n
Reduced Compliance Complexity<\/h3>\n
How does AI improve the Customer Experience in Insurtech?<\/h2>\n
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<\/p>\nBoosted Net Promoter Score<\/h3>\n
Simplified Processes<\/h3>\n
Automated Underwriting<\/h3>\n
AI Technologies Employed in Customer Experience<\/h2>\n
AI Chatbots<\/h3>\n
Benefits of AI Chatbots<\/h3>\n
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Customer Personalization<\/h3>\n
Benefits of Customer Personalization<\/h4>\n
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Machine Learning for Claims Processing<\/h3>\n
Benefits of Machine Learning for Claims Processing<\/h4>\n
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How AI Will Transform Your Insurance Company<\/h2>\n
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<\/p>\nAdopting AI Technology to Boost Your Customer Experience<\/h2>\n
Join the AI Revolution in the Insurance Industry<\/h2>\n