Etiqa shares how its small beginnings can create a name in the insurance industry

According to a report by Allianz, the global cyber insurance market is expected to reach $20 billion by 2025, driven by increasing awareness of cyber risks and regulatory requirements. Insurers that offer comprehensive cyber insurance coverage, backed by advanced risk assessment tools, can provide valuable protection to businesses and individuals. Microsoft’s Azure platform offers multiple AI and machine learning-powered services, but their NLP and chatbot capabilities are prominent among them. Clients can use the Azure service to build their own chatbot for customer service.

Skeptics point to instances where computers misunderstood users, and generated potentially damaging messages. But, because all AI systems actually do is respond based on a series of inputs, people interacting with the systems often find that longer conversations ultimately feel empty, sterile and superficial. Tekin says there’s a risk that teenagers, for example, might attempt AI-driven therapy, find it lacking, then refuse the real thing with a human being. “My worry is they will turn away from other mental health interventions saying, ‘Oh well, I already tried this and it didn’t work,’ ” she says.

The early-stage venture fund will focus on innovative technology and services specifically designed for the insurance industry. This is a timely initiative considering that motor-vehicle fatalities in 2016 peaked at 40,200; the highest amount recorded in nearly a decade. From an economic perspective, in a single year, the estimated healthcare costs totaled over $80 billion. The Bureau of Labor Statistics estimates that the median salary of an insurance adjuster who assesses auto damage was $63,510 in 2016.

By providing customized support, timely information and constant communication, chatbots have proven to enhance the user’s experience. For example, chatbots can help with timely dosage instructions, medication management, health monitoring, follow-ups and reminders. With this dynamic avenue of interaction, they help in active participation of users and healthcare providers. A November YouGov survey reported that 60% of consumers felt at least fairly confident in their ability to tell a human customer service agent from a robot. And over 80% of customers are willing to wait for some period of time—for some, as long as 11 minutes—to talk to a real person, even if an AI chatbot is available immediately, according to data from Callvu, a customer service platform provider. Our future work will focus on developing threat models that contain the identified security threats and vulnerabilities in chatbots and mitigation strategies, culminating in formulating security requirements.

How Car Insurance Providers Benefit From Using AI

Progressive claims to use a predictive analytics application that uses driving data collected from their clients to offer usage-based insurance (UBI). This means that Progressive could price their customers’ insurance policies based on how well they drive. Human resources has been slower to come to the table with machine learning and artificial intelligence than other fields—marketing, communications, even health care. Last but not least, we need to make sure that we continue to monitor the customer satisfaction level through all customer touchpoints.

And chatbots are already being used to screen patients by administering standard questionnaires. Many mental health providers at the U.K.’s National Health Service use a chatbot from a company called Limbic to diagnose certain mental illnesses. Allstate supports small business owners with ABIE (“Abbie”), an AI-powered tool that helps customers get answers to questions and locate critical documents via an onscreen avatar that can have naturalistic conversations with insurance agents. Through the use of contextual knowledge and intelligent content, ABIE is able to address what coverages work best for certain businesses, what incidents each coverage covers and more. The ultimate goal is to help companies boost underwriting profits while diminishing risk.

This technology simplifies the music-creating process, making it accessible to both amateur and professional musicians. The insurance industry is very language and picture driven, with a lot of unstructured data. For insurance chatbot examples example, large claims historically required loss adjusters on the ground to write down what happened and take pictures. This improves insights into losses and, ultimately, helps us better understand our customers.

AI Insurance Applications

Traditional underwriting processes are often time-consuming and reliant on manual data collection and analysis. AI-driven data analytics streamlines these processes by automating data gathering, analysis, and decision-making. For example, Zurich Insurance has implemented an AI-powered underwriting platform that uses machine learning algorithms to analyse vast amounts of data, including customer demographics, behaviour patterns, and external risk factors. Insurance is a highly regulated and process-oriented industry, so the company is looking to leverage ChatGPT’s machine learning capabilities to support its employees for inquiries. It has the potential to offer the appropriate data, forms, and processes to perform specific tasks, like customer KYC or claim applications.

These solutions also act as highly experienced digital assistants, tirelessly examining claims and surfacing those that require attention while automatically processing the straightforward ones. Snapsheet digitizes the claims process with its AI tools and cloud-based claims management software. Snapsheet Cloud is an insurance platform that automates various parts of the claims process, reducing the time it takes to calculate appraisals and receive online payments. The company’s AI features also snuff out false claims, allowing insurance teams to operate with a higher degree of efficiency. CCC Intelligent Solutions digitizes and automates the entire claims process with artificial intelligence.

Insurance uses AI for recommendation engines, marketing automation, and retention management systems. Chatbots help insurers ease the burden of standard customer service, just like in fintech companies, where AI-based communication solutions such as Cleo, Eno, or Wells Fargo Bot work great to enhance the customer support process. In Ref.8, it was observed that chatbots with AI features might encroach on client security and individual protection.

We decided that this topic is worth covering in depth since any changes to the healthcare system directly impact business leaders in multiple facets such as employee insurance coverage or hospital administration policies. They have full control of questions they want to ask and the answers they’d expect back to facilitate straight through processing for a section of customers. They have a variety of tools at their disposal for those who choose to ensure regular checks are made for any automated outcomes. Healthcare chatbots have become a valuable tool for healthcare, with their ability to improve user engagement.

The application of I4.0 technologies to the insurance industry creates value for the insurance company, and heterogeneous transformational capabilities are sources of competitive advantage (Stoeckli et al., 2018). They may enhance internal processes (e.g., exploiting data to handle claims), create new products, and develop new channels to provide professional advisory services. Cao et al. (2020) outline artificial intelligence (AI), machine learning, robotic process automatization, augmented reality/virtual reality, and blockchain as principal impacting technologies. These data could be transferred to the insurance company by using blockchain technology and then processed to fit policy prices by using AI algorithms such as those obtained from machine learning.

For instance, how to add memory to these QnA systems so you can use them in a chat-like manner. Let’s create a new tool — perc_diff()that takes two numbers as inputs and calculates the difference in percentage between these two numbers. LangChain library can be a bit daunting at first and if you would like to debug how things are working under the hood ChatGPT w.r.t. react agents, here are some useful breakpoints to set in your debugger. Interestingly enough, LLM was able to use the exchange rate as part of the calculations and the answer it gave (i.e. $338,164.25) was very close to the actual answer (i.e. 338,478.20). Having manually reviewed the policy document, it is safe to say the answers make sense.

How We’ve Helped Clients

As a global player, we are monitoring regulation across different jurisdictions, and we update our AI assessment tools accordingly. I believe that for insurance carriers who operate in different markets, it is easier to use the same tools globally, as this simplifies AI solution design and rollout across multiple countries. We assess all cases, while also aiming to make our assessment tools very user-friendly.

• This impact will be most pronounced in personal lines of insurance, where the risks and products tend to be simpler.
• Clients can use the Azure service to build their own chatbot for customer service.
• If the documentation says that a fracture was expected but the customer did not turn out to have one, the software could detect this and mark the claim as fraud or likely to be fraud.
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Developers grapple with morphological ambiguity, when one word has many meanings, and syntactic ambiguity, when a sentence has more than one possible structure. If you’re enjoying this article, consider ChatGPT App supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.

The reputational and ethical consequences of deceptive chatbot use

Statton explains that RAG overcomes the limitations of traditional language models by incorporating a retrieval step that allows the AI system to access relevant information from a knowledge base before generating a response. “This helps ensure that the generated responses are more accurate, contextually relevant, and coherent,” he elaborated. Insurance is being swept up in the technological revolution, with the Internet of Things, artificial intelligence, robotics and other advanced technologies impacting the way the industry operates. For many, the impersonal nature of automated systems can be an obstacle, especially when discussing sensitive health issues.

Solaria Labs, an innovation incubator established by Liberty Mutual, has launched an open API developer portal which integrates the company’s proprietary knowledge and public data to inform how these technologies will be developed. An Application Program Interface or API is essentially a toolkit that provides the blueprint for building software applications. The insurance industry is a competitive sector representing an estimated $507 billion or 2.7 percent of the US Gross Domestic Product. As customers become increasingly selective about tailoring their insurance purchases to their unique needs, leading insurers are exploring how machine learning (ML) can improve business operations and customer satisfaction. As ever, while customers appreciate the speed of response from a robot, it can’t replace the need for real-life interaction with a human who can empathise with a customer’s situation and offer support when they need it most. Lost luggage and flight delays can be simple to deal with, but when it comes to a sick child in a remote country with limited or basic medical care, then speaking to an experienced assistance coordinator is invaluable.

This question is especially relevant in I4.0 technology, which is a very dynamic and active field in rapid and continuous growth and improvement. We found that perceived ease has a positive significant impact on ATT but that this does not apply to PU. Insurtech has the main objective of improving the value of products offered to customers (Riikkinen et al., 2018) and their own value (Lanfranchi and Grassi, 2022). This fact may enhance trust in insurers’ main service, which covers satisfactorily honest claims (Guiso, 2021).

Etiqa shares how its small beginnings can create a name in the insurance industry

Generative AI is changing the insurtech space for 2024, and financial marketers should pay attention. (4) A typical example of digital insurance is smart contracts that rely on the IoT and blockchain (Christidis and Devetsikiotis, 2016). Once you click save, you’ll be brought to the screen where you’ll configure the chatbot. If you select a template, a decision tree with predetermined rules and script options will automatically populate in the configuration stage.

Also, look for services that provide templates and easy design tools to make the setup process easier. While customer service chatbots can’t replace the need for human customer service professionals, they offer great advantages that sweeten the customer experience. Startups like Lemonade, Root Insurance, and Metromile continue to disrupt traditional insurance models by introducing cutting-edge products and services. Meanwhile, established giants such as Allianz, AXA, and Aviva are increasingly integrating AI and IoT technologies to boost operational efficiency and customer engagement. The idea of boosting profits by shrinking call centers seems to be gaining ground. The chatbot can then purportedly send that response to the customer, or it can hold it until a human agent approves it.

There are too many decisions that require personal judgment for humans to be fully replaced by AI in investing. However, the cost-saving potential of artificial intelligence allows for decisions to be made more rapidly and inexpensively, and it could eliminate lower-level work in areas like research and underwriting. Given the wide range of applications, it is likely that AI will continue to grow throughout the finance industry in the future. One of the most common applications of artificial intelligence in finance is in lending. Machine learning algorithms and pattern recognition allow businesses to go beyond the typical examination of credit scores and credit histories to rate borrowers’ creditworthiness when applying for credit cards and other loans. CrowdStrike Charlotte AI allows users to interact with the Falcon platform using natural language, supporting threat-hunting, detection, and remediation efforts.

• Additionally, users can write to the chatbot from the Symptomate website if they are at a desktop computer.
• In the area of personalised marketing and sales efforts, he noted that RAG-driven AI can analyse customer data to generate personalised content and recommendations, improving customer engagement and conversion rates.
• Lost luggage and flight delays can be simple to deal with, but when it comes to a sick child in a remote country with limited or basic medical care, then speaking to an experienced assistance coordinator is invaluable.
• Having the prototype freely available for individuals and the online viral sharing of their experiences with ChtatGPT are also the reasons for its sensational popularity, said Chun.

In addition to UBI, IoT and telematics technologies are also transforming claims management processes. Real-time data from connected devices can provide accurate and timely information on accidents and damages, enabling faster and more efficient claims processing. For example, State Farm uses telematics data to expedite claims handling and improve accuracy in assessing damages. Embedded insurance is transforming the traditional insurance buying process by integrating coverage directly into the purchase process of products and services. This trend simplifies the insurance acquisition journey, improves customer experience, and opens new distribution channels for insurers.

Progressive also worked with Microsoft Azure to create a natural language processing-enabled chatbot that emulates its popular mascot character, Flo. The Flo chatbot is a virtual assistant for customer service that customers could access through the company’s Facebook messenger account. It also references some of the commercials that Flo appears in and purportedly uses Progressive’s knowledge base to identify answers to customer service questions.

Figure 9 depicts when the user has already been given rights to access the Claims chatbot. Then, the user requests information and asks FAQ (frequently asked questions) related to the claim. All the interactions, including query processing results, are stored in the log file for auditing purposes. Chatbots are mostly accessible through different platforms of messenger apps such as Facebook and Skype, and there is no proper security implementation on these platforms.

AI impact is proving to be greater than the digital transformation that preceded it. The insurance industry is facing a significant talent crisis as many experienced workers approach retirement age. Fortunately, AI solutions offer a remedy for this “brain drain” by capturing the experience of seasoned professionals and enabling new employees to learn from it.

However, collaborative efforts are being made to adapt these applications to more challenging situations. Marine insurance companies use satellite photos and ML image-recognition solutions to verify a claimant’s credibility and claim integrity. She writes and edits in a variety of industries including cybersecurity, healthcare, and personal finance.

If something like the time of day when driving is taken into account to build a car insurance model, that could be a proxy for income level. When a patient needs detailed advice or is dealing with a sensitive issue, it’s best that they connect with a healthcare professional. For example, insurance claims processing can be done via the online portal instead of in-person, reducing the number of resources required for communication and follow up procedures. In fact, healthcare chatbot’s market size was valued at $194.85 million in 2021 and is forecasted to reach $943.64 million by 2030, according to Verified Market Research study. By using neural networks plugged into sources coming from internal and external data providers (including reinsurers and product manufacturers), insurers can present instant quotes. As a result, a commercial, car, or life insurance purchase can take mere minutes or even seconds.

Calculate the potential savings and efficiency gains to determine the best bang for your buck. As your customer base grows, the chatbot should be able to handle increased volumes without compromising performance. Evaluate the service’s ability to manage peak times and provide consistent support. Before you pick a chatbot service, make sure you know exactly what you want to achieve and the specific situations you need it for. Figure out if you need a chatbot to handle FAQs, offer personalized support or manage complex interactions. Getting clear on your goals will help you choose a service that fits your business needs.

Hence, conversational bots lack the ability to discern the nuances of a talk through users’ voice tones; thus, they cannot display human competencies such as empathy and critical assessments and are unable to meet complex requirements. These abilities were not present in chatbots at the end of the 2010s (Eeuwen, 2017) or at the beginning of the 2020s (Vassilakopoulou et al., 2023). This resistance has also been documented by Van Pinxteren et al. (2020) and PromTep et al. (2021).

Additionally, credit card companies and financial institutions could use AI software to improve customer service and develop customer-targeted marketing campaigns. Digital Genius also offers a chatbot software called “Co-Pilot” and claim to help businesses like travel agencies automate the most repetitive customer support questions. The applications of natural language processing (NLP) have been increasing as more companies find uses for their text data. This includes insurance companies with large stores of data from claims and customer support tickets. It could simplify the user experience and reduce the complexity of banking operations, making it easier for even nonnative speakers to use banking and financial services worldwide. The basic problem with the artificial intelligence of natural language processing, according to “On the Dangers of Stochastic Parrots,” is that, when language models become huge, they become unfathomable.

Therefore, this approach applies to conversational chatbots (Gkinko and Elbanna, 2023) and in the realm of fintech (de Andrés-Sánchez et al., 2023; Firmansyah et al., 2023) and insurtech (Zarifis and Cheng, 2022) powered by AI. The main arguments for its significance center on the relevance of its cognitive and relational dimensions defined in Glikson and Woolley (2020). In our context, the cognitive dimension of trust is manifested in the perceived effectiveness of chatbot technology for implementing procedures linked with active policies. Relational trust is identified as the confidence that policyholders have in the insurer’s implementation of chatbots, with the intention of enhancing their ability to provide satisfactory service (Zarifis and Cheng, 2022).

It’s a disciplined new option for a business result, not magical technology powder to sprinkle on flawed data. Generative AI is a type of artificial intelligence that can create new content such as text, images, audio or code using patterns that it has learned from existing data. It employs complex models such as deep learning to produce outputs that closely resemble the features of the training data. Buffer is a social media management application that allows organizations to plan, schedule, and analyze their social media content. Its AI capabilities include post idea generation, post timing optimization, and content distribution automation across different platforms.

This technology is enabling financial institutions to offer more tailored services, improve decision-making processes, and increase operational efficiency. A 2024 Conning survey found that 77% of insurance industry executives were somewhere in the process of adopting AI. But many property and casualty (P&C) insurers are expected to focus initially on claims operations in their journey to adopt generative AI, according to EY. This preference stems from the quicker ROI that claims operations tend to offer compared with other segments of the insurance life cycle. The potential to generate value in claims operations—through improved efficiency, precision, and an elevated customer experience— makes it an appealing entry point to implement genAI. You can foun additiona information about ai customer service and artificial intelligence and NLP. This guide to insurtech explores how technologies such as AI, blockchain, the internet of things (IoT), and machine learning (ML) are reshaping the traditional insurance landscape.