Insurtech: Types, top trends, companies, & AIs impact

They also say that the more someone uses the chatbot, the better it will be at determining their mental health needs. This could provide an immediate line of defense against mental health ailments until the patient can find a human professional or reach a healthy state of mind to do so. For example, a patient can use the iOS or Android app to input their symptoms or access the app using a voice assistant such as Alexa. Additionally, users can write to the chatbot from the Symptomate website if they are at a desktop computer. Mickman also characterizes the AI capabilities at Optum from the time the video was taken in 2019 as “early” in the adoption phase. However, those familiar with developing such a platform understand the capabilities presented – even from an IT perspective – are indicative of long-term strategizing by data teams and business leadership at UnitedHealth.

The TRUST scale was used by Farah et al. (2018) and Kim et al. (2008) and is based on Morgan and Hunt (1994). In the second section, we propose a TAM-based model to explain behavioral intention (BI) and attitude toward chatbots. The third Section describes the material and quantitative methods used in this article. Finally, we discuss our results and implications for the insurance industry and outline principal conclusions.

They use predefined scripts for simple queries and AI for more complex interactions, offering a balanced and flexible solution. Rule-based chatbots are ideal for handling frequently asked questions, basic inquiries and straightforward tasks such as providing account information, tracking orders and answering common questions. Their predictable nature guarantees consistent responses for routine interactions. IBM is working with several financial institutions using generative AI capabilities to understand the business rules and logic embedded in the existing codebase and support its transformation into a modular system. The transformation process uses the IBM component business model (for insurance) and the BIAN framework (for banking) to guide the redesign. Generative AI also aids in producing test cases and scripts for testing the modernized code.

More Science and Technology

Health Fidelity focuses on risk adjustment and offers a thorough process for adjusting risk from every angle. This would eventually require unstructured data, such as a long email or an insurance claim. These types of documents, as well as clinical documents for health insurers, would need to be run through NLP software before the data points could be interpreted as indicative of high risk. IBM claims to have helped a leading insurance provider organize their data from large storage systems and multiple sources. The data was supposed to be funneled into a database for call center agents processing insurance claims. According to the case study, Watson’s Explorer software reduced their client’s claims processing time from two days to ten minutes and saved 14,000 agents 3 seconds per call on average.

We checked that all the assessed explanatory factors, trust (TRUST), PU, and PEOU, were significant in explaining BI through the mediation of ATT. They don’t use AI traditionally but follow specific paths determined by the input they receive. Working together, these technologies help ‌chatbots understand and respond to customer queries more accurately and naturally. 3 min read – Solutions must offer insights that enable businesses to anticipate market shifts, mitigate risks and drive growth. IBM watsonx™ AI and data platform, along with its suite of AI assistants, is designed to help scale and accelerate the impact of AI using trusted data throughout the business. With a strong focus on AI across its wide portfolio, IBM continues to be an industry leader in AI-related capabilities.

Advanced risk models powered by AI will play a crucial role in forecasting increasingly unpredictable weather events. Presently, Verisk’s AIR Worldwide provides a hurricane catastrophe model tailored for the US, alongside the First Street Foundation Wildfire Model. It has been developed in a single country, Spain, and many responses come from social networks such as LinkedIn, whose users are usually persons with university degree studies and professional status that may rank from medium to very high. Of course, educational level and economic position may be relevant for explaining attitude toward chatbots.

Generative AI with Large Language Models, by AWS and DeepLearning

Likewise, improvements in the utility and ease of use of robots are also needed to prevent customers’ reluctance toward their services. Traditional document processing in insurance involves manual data entry, verification, and analysis, which can be time-consuming and prone to errors. Automated digital document processing solutions use AI and machine learning algorithms to extract and process data from various documents, such as claims forms, policy applications, and customer correspondence. This automation improves accuracy and efficiency, reducing the burden on human agents and allowing them to focus on more complex tasks.

Being part of the Maybank group, which is an established name in Malaysia and Singapore, helps our brand. The bulk of our business is through Maybank bancassurance, which provides the basic business-as-usual (BAU) level of business that we do. We want to make sure that all terms and conditions are clearly explained and settled explicitly.

AI and insurtech

The tool applied to solve many natural language processing problems is called a transformer, which uses techniques called positioning and self-attention to achieve linguistic miracles. Every token (a term for a quantum of language, think of it as a “word,” or “letters,” if you’re old-fashioned) is affixed a value, which establishes its position in a sequence. The positioning allows for “self-attention”—the machine learns not just what a token is and where and when it is but how it relates to all the other tokens in a sequence.

In an April 2024 post on X, Grok, the AI chatbot from Elon Musk’s xAI, falsely accused NBA star Klay Thompson of throwing bricks through windows of multiple houses in Sacramento, Ca. Hold on—this is not a one-way street, and there are serious issues that need careful thought. Much of this growth was driven by property and casualty, which saw a 19.8% rise in investment. The number of insurtech deals climbed in Q3, from 97 to 119, with P&C leading the pack at 90.

Business Insider Intelligence predicts that the global annual cost savings derived from chatbot automation across the insurance industry alone will surge from $0.5 billion in 2020 to $5.8 billion in 2025. KAI Consumer Banking, KAI Business Banking, and KAI Investment Management are all built with an API-centric design on top of conversational AI technology. According to Kasisto, 90% of conversations with KAI are carried without human intervention. Artificial Intelligence (AI) in finance refers to the use of machine learning to enhance how financial institutions analyze and manage investments. The financial industry encompasses several subsectors, from banking to insurance to fintech.

INZMO, a Berlin-based insurtech for embedded insurance & a top ten European insurtech driving change. For instance, a February 2023 Ipsos survey of 1,109 U.S. adults found that less than one-third of respondents trust AI-generated search results. Just a couple of months after ChatGPT’s release (what I call ”AC”), a survey of 1,000 business leaders by ResumeBuilder.com found that 49% of respondents said they were using it already.

Advanced Threat Detection and Analysis: Google Cloud Security AI Workbench

Koala is also working on specific insurance products for the unusual circumstances that travellers face in the pandemic era. For example, policies could protect those barred from boarding a flight because they fail a temperature screening. The huge amount of data created can be sifted through via AI, enabling travel insurers to offer real-time service delivery and claims, which ultimately is what the customer wants. Customers in the Middle East are becoming increasingly familiar with being greeted by friendly chatbots — virtual helpers that are available day or night for all kinds of burning questions. From Dubai’s sprawling malls to Cairo’s bustling hospitals, Arabic-speaking chatbots are streamlining the customer experience while offering lucrative growth opportunities to businesses that adopt them. Cheung believes that RAG-based conversational solutions will greatly improve companies’ ability to retrieve and present targeted information to their customers or employees.

The company’s strategic move aligns with research on insurance trends published by The Boston Consulting Group and Morgan Stanley. The report projects an increasing decline in personal lines and a “65 percent reduction of the personal auto insurance market by 2030.” A contributing factor to this trend is the anticipated debut of autonomous vehicles. Competition scores were calculated using a log loss metric ranging from a minimum value of 0 to a maximum value of 1. The goal of a machine learning model is to achieve a score that is as close to zero as possible, which indicates the level of accuracy of a given model. This article aims to present a comprehensive look at the four leading insurance companies and their use of AI.

Marriott International’s Hotel Chatbot

While there are pro and cons to the technology, insurers and customers have widely reaped the rewards of AI-based algorithms, making processes simpler and safer. To get a better sense of how AI impacts the insurance industry, check out these AI insurance applications. For example, since chatbots interpret and process human-understandable language within the spoken context, they understand the depth of the conversation and realize general user commands or queries.

Phoenix Ko, co-founder and head of business development, says customers are more likely to trust ChatGPT than an agent because people know that agents are biased in how they select products. ChatGPT, because of its natural tone and unscripted fluidity, can influence users. As a contribution, this study deepens understanding of the application of STRIDE modelling. It also offers a case study on chatbot security regarding the insurance industry, which is a first attempt to the best of our knowledge. The fact that the case study is also from the South African context constitutes an empirical contribution because case studies on chatbot security from developing countries, particularly Africa, are uncommon in the literature.

Rather, the conversation would end in the app recommending the customer to an agent, who would come armed with the chatbot’s insights about the customer’s needs. That doesn’t temper their competitiveness, but it does mean that the more agents use PortfoPlus’s ChatGPT plug-in, the better job it does for all of them. Ultimately that means using technology to enable them to better serve customers rather than just sell products with high commissions. That’s the bet that one insurtech in Hong Kong is making, despite facing technological and regulatory questions. Lee offered a different approach, noting that generative AI could improve a company’s ability to reach out to customers.

This process leverages “institutional knowledge,” which includes the data, expertise and best practices accumulated by employees over time. Insurers can leverage this valuable knowledge to train AI models, effectively transferring it to newer employees. By providing new hires with AI-powered virtual “guardrails,” insurers can reduce learning curves mitigating the potential loss of expertise due to retiring underwriters and adjusters. By leveraging AI and advanced analytics, insurers can access a wealth of information that enables underwriters to make better pricing decisions. AI serves as a knowledgeable digital assistant, utilizing industry data lakes containing millions of policies to enhance underwriters’ risk assessment abilities and evaluate policies more efficiently.

Synthesia’s ability to update and edit videos quickly makes it easy to rapidly iterate and test marketing messages to keep content fresh and relevant. Cleo employs generative AI to provide personalized financial advice and budgeting assistance. By analyzing users’ spending habits and financial data, Cleo generates tailored suggestions to help users manage their finances more effectively, encouraging savings and reducing unnecessary expenditures. Its friendly and conversational interface makes financial management approachable and less intimidating for users. Duolingo uses generative AI to personalize the language learning experiences of its users.

Banks should provide relevant training data and integrate the model with their existing systems to ensure that it can provide accurate and appropriate responses to user queries. Auto insurers are also challenged with carefully monitoring driver trends as technology becomes increasingly adopted within the auto industry. Data interpretation through machine learning will be an important insurance chatbot examples application in the coming years for identifying business opportunities in an evolving market. ABle, who appears as an avatar, reportedly provides agents with step-by-step guidance for  “quoting and issuing ABI products” using natural language. Jordan says Pyx’s goal is to broaden access to care — the service is now offered in 62 U.S. markets and is paid for by Medicaid and Medicare.

Reducing risk is the bread and butter of running a car insurance company because it can reduce the number of claims payouts that have to be made. The company may also be able to leverage social media responses as data to improve the chatbot’s conversational capabilities. For example, some customers may not know about the chatbot ChatGPT and leave their question as a comment on a Facebook post. Despite the inspiring prospects that AI technology opens up for improving the customer experience in banking, implementing it into banking products can pose some challenges. One of the main challenges is safeguarding the security and privacy of customer data.

This paper analyses policyholders’ attitude toward conversational bots in this context. To achieve this objective, we employed a structured survey involving policyholders. The survey aimed to determine the average degree of acceptance of chatbots for contacting the insurer to take action such as claim reporting. We also assessed the role of variables of the technology acceptance model, perceived usefulness, and perceived ease of use, as well as trust, in explaining attitude and behavioral intention. We have observed a low acceptance of insureds to implement insurance procedures with the assistance of a chatbot.

Limbic, which is testing a ChatGPT-based therapy app, is trying to address this by adding a separate program that limits ChatGPT’s responses to evidence-based therapy. Harper says that health regulators can evaluate and regulate this and similar “layer” programs as medical products, even if laws regarding the underlying AI program are still pending. The other feature allows users to practice their conversation skills with simulated characters and situations in the app, which can provide experiences similar to that of the real world. The first ChatGPT-based feature allows users to enter a chat with the Duo chatbot to avail simple explanations on why an answer is right or wrong, and they can even ask for examples and better clarification.

It talks to users about their  mental health and wellness through brief daily conversations, taking into account what’s going on in the user’s life and how they are feeling that day. Woebot also sends useful videos and other tools depending on the user’s mood and specific needs. The cost-saving potential of artificial intelligence only adds to its appeal to banks and other financial companies.

• By automating routine tasks such as policy renewals, claims processing, and customer inquiries, insurers can reduce operational costs and improve efficiency.
• AI is used to analyze big data sets and geographic information systems (GIS) to map risk better.
• Of course, educational level and economic position may be relevant for explaining attitude toward chatbots.
• Chatbots could assist users with financial planning tasks, such as budgeting and setting financial objectives.

All of the claims would be labeled according to if they are fraudulent or not, and fields within the claims form that contain fraudulent information would be labeled to note this. The survey also showed that 34% of these customers have completed a claim without talking to a human. A whopping 92% of consumers want self-serve tools for managing claims, but that group is split on how technology should be integrated. While 49% want a fully digital self-service process, 43% want a hybrid of digital and human interaction. Another challenge is training an AI model to understand the language and terminology specific to the banking industry.

This would allow them to easily manage the data for verification through the client company’s specific procedures. At this point, you might have noticed AI in your car insurance company in a few ways. Perhaps you’ve interacted with customer service chatbots when you had a question about billing or coverage.

IBM Watson Explorer combs through structured and unstructured text data to find the right information to process insurance claims. This information usually comes from the customer making the claim, but further claims help the software to recognize more terms and phrases. This software can be applied to applications designed to help customer service agents, who may need to search for the correct information through an intranet or similar employee resource. Common chatbots ask what you need and then direct you to a self-service link or a human agent. A large language model trained on a company’s entire library of documentation can understand nuanced questions and give answers in real time. Despite the massive venture investments going into healthcare AI applications, there’s little evidence of hospitals using machine learning in real-world applications.

The insurance industry is understood and known as a subdivision of financial services27,28. In South Africa, insurance companies are divided into long-term or life insurance and short-term property or car insurance29. Good customer relationship management in the insurance industry is important as it helps to retain existing customers, which can be done effectively by adopting advanced technologies30. Although customers can go directly to the insurance company, insurance companies often use brokers or agents as intermediaries between them and customers. Brokers always work closer to the clients to help them understand the products offered by the insurance.

• Credit card companies could make use of AI applications across multiple business areas.
• The authors concluded that suitable precautionary analysis concerning chatbots’ security and privacy vulnerabilities in the financial industry must be executed before deployment.
• Nayya guides individuals and companies through health benefits with a selection process that runs on AI technology.
• Customers can ask questions and access information and services long after brick-and-mortar businesses have closed for the night.
• They are seeing unprecedented levels of personalization, content creation, and customer engagement.
• The compensation may impact how, where and in what order products appear, but it does not influence the recommendations the editorial team provides.

She has performed research through the National Institutes of Health (NIH), is an honors graduate of Rensselaer Polytechnic Institute and a Master’s candidate in Biotechnology at Johns Hopkins University. Woebot, a text-based mental health service, warns users up front about the limitations of its service, and warnings that it should not be used for crisis intervention or management. You can foun additiona information about ai customer service and artificial intelligence and NLP. If a user’s text indicates a severe problem, the service will refer patients to other therapeutic or emergency resources. That’s precisely why Ali’s doctor, Washington University orthopedist Abby Cheng, suggested she use the app. Cheng treats physical ailments, but says almost always the mental health challenges that accompany those problems hold people back in recovery. Addressing the mental-health challenge, in turn, is complicated because patients often run into a lack of therapists, transportation, insurance, time or money, says Cheng, who is conducting her own studies based on patients’ use of the Wysa app.

Banks should ensure that their chat interface is secure and that sensitive data is protected from unauthorized access or disclosure. Second, AI can automate many routine tasks, such as account balance inquiries ChatGPT App and password resets, freeing customer service representatives up to focus on complex issues. It could increase efficiency and reduce costs for banks while providing faster and more accurate customer support.

As a result, firms can make more informed decisions when underwriting insurance policies for, trading and investing in properties. Insurers can track the habits of drivers for organizations like Uber and Lyft with wearable technology. If drivers for a service demonstrate safer driving habits, insurers can then offer that service lower premiums. Devices can also be used to activate insurance coverage only when drivers are actually driving, cutting costs while insuring service workers who would otherwise have had to purchase their own policies.

If it was a simple claim, an AI tool could have analyzed the information and estimated your payout in minutes. We’re not yet in a world with continuous insurance underwriting like this, but we may not be that far off. Car insurance companies have used artificial intelligence for a variety of applications over the last decade, and the rate of adoption is increasing with advancements in technology. In this article, the MarketWatch Guides Team will take a look at how AI is transforming auto insurance for both providers and drivers.