Generative AI in Insurance: Top 7 Use Cases and Benefits

What Is Artificial Intelligence? Definition, Uses, and Types

gen ai in insurance

In the case of an auto accident, for example, a policyholder takes streaming video of the damage, which is translated into loss descriptions and estimate amounts. Vehicles with autonomous features that sustain minor damage direct themselves to repair shops for service while another car with autonomous features is dispatched in the interim. In the home, IoT devices will be increasingly used to proactively monitor water levels, temperature, and other key risk factors and will proactively alert both tenants and insurers of issues before they arise. In industrial settings, equipment with sensors have been omnipresent for some time, but the coming years will see a huge increase in the number of connected consumer devices. Experts estimate there will be up to one trillion connected devices by 2025.2World Economic Forum, 2015. The resulting avalanche of new data created by these devices will allow carriers to understand their clients more deeply, resulting in new product categories, more personalized pricing, and increasingly real-time service delivery.

They also develop test policies for providers when determining rates in online plans to ensure the algorithm results are within approved bounds. Public policy considerations limit access to certain sensitive and predictive data (such as health and genetic information) that would decrease underwriting and pricing flexibility and increase antiselection risk in some segments. Just like the next wave of business laptops, the Lenovo ThinkVision™ 27 3D monitor is available now and ready to boost productivity and efficiency. The glasses-free 3D monitor now features an even more intuitive and interactive user interface version of 3D Explorer, which welcomes creators to the 3D realm and can also be used in 2D. Additionally, the monitor now comes with increased software support through proprietary applications, including Design Engine, which eliminates the need for individual plug-ins to provide a true interdimensional hybrid design experience. Users can now design in 2D and visualize in 3D, or use its 2D-to-3D Converter, enabling AI-powered 2D to 3D image, video, and content conversion in real time.

Her insights have appeared in various industry outlets, including CIO, InformationWeek, and Technology Magazine. In some ways, this article is premature—so much is changing that we’ll likely have a profoundly different understanding of gen AI and its capabilities in a year’s time. How well companies have learned those lessons may largely determine how successful they’ll be in capturing that value. These are just some of the ways that AI provides benefits and dangers to society. When using new technologies like AI, it’s best to keep a clear mind about what it is and isn’t. As researchers attempt to build more advanced forms of artificial intelligence, they must also begin to formulate more nuanced understandings of what intelligence or even consciousness precisely mean.

gen ai in insurance

What’s your advice to insurance leaders embarking on this transformation journey? Leading insurers are already seizing the moment by deploying big-win GenAI applications that scale well. To go beyond isolated use cases, they’ve launched a transformation based on a multilayered operating model. It future-proofs the organization and culture, planning proactively for the shift in skills and talent required to run a GenAI-empowered organization. It builds the partnerships and tech architecture to develop and scale GenAI applications that generate true impact, as well as an underlying policy that shapes GenAI to strengthen corporate values. The second approach is to focus on transforming individual verticals end to end.

Automotive Industry

Several markets, including Italy, have already banned ChatGPT because of privacy concerns, copyright infringement lawsuits brought by multiple organizations and individuals, and defamation lawsuits. While no country has passed comprehensive AI or gen AI regulation to date, leading legislative efforts include those in Brazil, China, the European Union, Singapore, South Korea, and the United States. Each approach has its own benefits and drawbacks, and some markets will move from principles-based guidelines to strict legislation over time (Exhibit 1). Key gen AI concerns include how the technology’s models and systems are developed and how the technology is used. In this article, we explain the risks of AI and gen AI and why the technology has drawn regulatory scrutiny. We also offer a strategic road map to help risk functions navigate the uneven and changing rule-making landscape—which is focused not only on gen AI but all artificial intelligence.

  • This automation leads to faster claims processing, allowing insurers to provide quicker resolutions to policyholders.
  • One bank, for example, bought tens of thousands of GitHub Copilot licenses, but since it didn’t have a clear sense of how to work with the technology, progress was slow.
  • Answer customer inquiries in real-time and provide customer service agents with summarized and all relevant customer information.
  • Harnessing the technology will require experimentation, training, and new ways of working—all of which take time before the benefits start to accrue.
  • Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

His leadership experience spans the private, public, and not-for-profit sectors. He is actively involved in his local community, fostering sustainable inter-generational social impact. Gordon MacMaster, Vice President, Data and Analytics Consulting PracticeA seasoned data strategist, Gordon MacMaster is the VP of the Data & Analytics Consulting Practice at Info-Tech Research Group. MacMaster has dedicated his career to helping organizations use data effectively, staying at the forefront of every data revolution. “The expertise shared by our first round of speakers will empower attendees to anticipate 2025 trends, define robust data strategies, and understand the next generation of AI and technology operating models, ensuring they are well-prepared for the future.”

Mains, who majored in apparel merchandising and media studies, has applied to hundreds of public relations and marketing jobs but has had just a few interviews in a cooling labor market. New grads are competing not just among themselves but with laid-off white-collar workers in fields such as tech and consulting, according to a LinkedIn report. Her auto insurance premium has climbed $200 to $300 a year in the past few years, she estimates. Young people also spend 5.5% of their income on dining out, compared with 4.5% for the average person; 5.3% on gasoline versus an average of 3.2%; and 2.6% on auto insurance versus an average of 2.3%, the Moody’s analysis shows.

Meanwhile, contract processing and payment verification are eliminated or streamlined, reducing customer acquisition costs for insurers. The purchase of commercial insurance is similarly expedited as the combination of drones, IoT, and other available Chat GPT data provides sufficient information for AI-based cognitive models to proactively generate a bindable quote. As AI becomes more deeply integrated in the industry, carriers must position themselves to respond to the changing business landscape.

As the insurance industry grows increasingly competitive and consumer expectations rise, companies are embracing new technologies to stay ahead. The effects will likely surface in both employee- and digital-led channels (see Figure 1). For example, an Asian financial services firm developed a wealth adviser hub in three months to increase client coverage, improve lead conversion, and shift to more profitable products. Helvetia in Switzerland has launched a direct customer contact service using generative AI to answer customers’ questions on insurance and pensions. And HDFC Ergo in India has opened a center to apply generative AI for hyper-personalized customer experiences.

Some are adapting their product offerings and distribution methods — think comparison sites, Internet of Things (IoT) and usage-based policies. Get the guide to driving responsible generative AI adoption in the insurance industry. The versatility of generative AI in the insurance industry is immense, and its power cannot be overstated. While many industries are still in the experimental phase, the insurance sector is poised to benefit significantly from the integration of artificial intelligence into its ecosystem.

If you’re an insurance company looking to leverage AI for insurance, you’ve come to the right place. At Aisera, we’ve created tools tailored to enterprises, including insurance companies. We offer products such as virtual assistants, personalized policy recommendations, claims automation, dynamic forms, workflow automation, streamlined onboarding, live AI agent assistance, and more.

Rapid advances in technologies in the next decade will lead to disruptive changes in the insurance industry. Most important, carriers that adopt a mindset focused on creating opportunities from disruptive technologies—instead of viewing them as a threat to their current business—will thrive in the insurance industry in 2030. In augmented chess, average players enabled by AI tend to do better than expert chess players enabled by the same AI. The underlying reason for this counterintuitive outcome depends on whether the individual interacting with AI embraces, trusts, and understands the supporting technology. To ensure that every part of the organization views advanced analytics as a must-have capability, carriers must make measured but sustained investments in people. The insurance organization of the future will require talent with the right mindsets and skills.

In their attempt to clarify these concepts, researchers have outlined four types of artificial intelligence. In this article, you’ll learn more about artificial intelligence, what it actually does, and different types of it. In the end, you’ll also learn about some of its benefits and dangers and explore flexible courses that can help you expand your knowledge of AI even further. Artificial intelligence (AI) refers to computer systems capable of performing complex tasks that historically only a human could do, such as reasoning, making decisions, or solving problems. It is important to note, that medical expenses also have been rising, which means higher costs for insurance companies when they cover injuries from accidents. In 2023, the average medical cost per claim reached nearly US$20,000, up from US$17,000 just five years ago.

GenAI Will Write the Future of Insurance Claims

Now that you know the benefits and limitations of using Generative Artificial Intelligence in insurance, you may wonder how to get started with Generative AI. It could then summarize these findings in easy-to-understand reports and make recommendations on how to improve. Over time, quick feedback and implementation could lead to lower operational costs and higher profits. Anthem’s use of the data is multifaceted, targeting fraudulent claims and health record anomalies. In the long term, they plan to employ Gen AI for more personalized care and timely medical interventions.

gen ai in insurance

While developing Lilli, our team had its mind on scale when it created an open plug-in architecture and setting standards for how APIs should function and be built. They developed standardized tooling and infrastructure where teams could securely experiment and access a GPT LLM, a gateway with preapproved APIs that teams could access, and a self-serve developer portal. Our goal is that this approach, over time, can help shift “Lilli as a product” (that a handful of teams use to build specific solutions) to “Lilli as a platform” (that teams across the enterprise can access to build other products). Let’s briefly look at what this has meant for one Pacific region telecommunications company. The company hired a chief data and AI officer with a mandate to “enable the organization to create value with data and AI.” The chief data and AI officer worked with the business to develop the strategic vision and implement the road map for the use cases.

Appian empowers you to protect your data with private AI and provides more than just a one-off, siloed implementation. Appian is your gateway to the productivity revolution, helping you operationalize AI across your organization and streamline end-to-end processes. Cem’s hands-on enterprise software experience contributes to the insights that he generates.

As a result, 74% of insurance executives plan to increase their investments in AI. Create a taxonomy and inventory of models, classifying them in accordance with regulation, and record all usage across the organization in a central repository that is clear to those inside and outside the organization. Create detailed documentation of AI and gen AI usage, both internally and externally, its functioning, risks, and controls, and create clear documentation on how a model was developed, what risks it may have, and how it is intended to be used. There is, however, an economic incentive to getting AI and gen AI adoption right. Companies developing these systems may face consequences if the platforms they develop are not sufficiently polished.

As a result, the underwriting process will be much more thorough, and overall claims costs will be lower. Plus, underwriters will be able to work more efficiently by processing applications faster and with fewer errors, which, in turn, can lead to higher customer satisfaction ratings. In this overview, we highlight key use cases, from refining risk assessments to extracting critical business insights. As insurance firms navigate this tech-driven landscape, understanding and integrating Generative AI becomes imperative.

Info-Tech Research Group’s comprehensive blueprint offers insurance leaders a roadmap to integrate Exponential IT principles, emphasizing data… For information about Info-Tech Research Group or to access the latest research, visit infotech.com and connect via LinkedIn and X. Media professionals can register for unrestricted access to research across IT, HR, and software and hundreds of industry analysts through the firm’s Media Insiders program. Updates and new details about speakers, agendas, and exclusive event experiences can be found via LinkedIn and X over the coming months. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Insurance Claims Process is Changing due to GenAI BCG – BCG

Insurance Claims Process is Changing due to GenAI BCG.

Posted: Wed, 13 Dec 2023 08:00:00 GMT [source]

They were accused of using the technology which overrode medical professionals’ decisions. Large-scale adoption of AI solutions, including GenAI, always requires an integration of talent and technology. Companies should introduce the technology as a means to an end; they should carefully explain GenAI’s role to employees and provide them with adequate support and incentives for its use.

Selecting the right Gen AI use case is crucial for developing targeted solutions for your operational challenges. So now that we’ve delved into both the benefits and drawbacks of the technology, it’s time to explore a few real-world scenarios where it is making a tangible impact. While these statistics are promising, what actual changes are occurring within the sector? Let’s delve into the practical applications of AI and examine some real-world examples. As the CEO and founder of one of the top Generative AI integration companies, I will also share recommendations for the successful and safe implementation of the technology into business operations.

The insurance industry has long relied on human expertise and manual processes to handle claims. But the advent of advanced technologies, particularly generative AI, has opened up new possibilities to transform and streamline the insurance claims process. As insurers stand at the precipice of a transformative era shaped by GenAI, they need to act now to succeed in it. CEOs have a pivotal role in adopting advanced technologies, creating a culture of continuous learning, and adjusting operational models. By making Gen AI a core part of their innovation strategy, insurance CEOs can become leaders in the evolving insurance innovation landscape. CEOs will need to make determined choices, act quickly but purposefully, and invest wisely to keep a competitive advantage in the market.

With our comprehensive approach, we strive to provide timely and valuable insights into best practices, fostering innovation and collaboration within the InsurTech community. Global economic uncertainties, including inflation and market volatility, gen ai in insurance also make it more expensive for reinsurers to predict and manage their risk exposures. Inflation rates, which have been fluctuating around 3-4% annually, impact the overall cost of claims, thereby increasing reinsurance costs.

Comarch Diagnostic Point: Next Gen European Health Insurance

Info-Tech LIVE 2024 promises actionable insights and transformative strategies for IT leaders and professionals. The first round of featured experts for the September conference in Las Vegas has been revealed, setting the stage for a groundbreaking event focused on the future of technology and next-gen IT operating models. Building a gen AI model is often relatively straightforward, but making it fully operational at scale is a different matter entirely.

You can foun additiona information about ai customer service and artificial intelligence and NLP. The Mechanical Energy Harvesting Combo is a product that uses mechanical movement and solar irradiation to power a mouse and a keyboard, eliminating the need for external charging. The mouse and the keyboard are ergonomically designed to provide comfort and engagement for the user. The product also supports both Bluetooth® and 2.4G wireless connection modes, ensuring easy connectivity with multiple devices.

Cem’s work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. The regulatory environment for AI in insurance is evolving, and companies will need to navigate these changes carefully. Regulators may require companies to demonstrate the robustness, fairness, and transparency of their AI systems, and especially of the generative AI solutions due to their ethical concerns. Generative AI can be used to generate synthetic customer profiles that help in developing and testing models for customer segmentation, behavior prediction, and personalized marketing without breaching privacy norms. At the core of this new gaming lineup is the family of Lenovo’s proprietary hardware AI chips—called LA AI chips–and the advantages they bring to both Lenovo Legion and Lenovo LOQ gaming laptops. First introduced last CES, this year’s LA AI chips are mightier than ever, enabling Lenovo Legion and Lenovo LOQ laptops to achieve even higher FPS, increased power efficiency, and more.

Some carriers are already beginning to take innovative approaches such as starting their own venture-capital arms, acquiring promising insurtech companies, and forging partnerships with leading academic institutions. Insurers should develop a perspective on areas they want to invest in to meet or beat the market and what strategic approach—for example, forming a new entity or building in-house strategic capabilities—is best suited for their organization. AI’s underlying technologies are already being deployed in our businesses, homes, and vehicles, as well as on our person. The disruption from COVID-19 changed the timelines for the adoption of AI by significantly accelerating digitization for insurers. Virtually overnight, organizations had to adjust to accommodate remote workforces, expand their digital capabilities to support distribution, and upgrade their online channels. While most organizations likely didn’t invest heavily in AI during the pandemic, the increased emphasis on digital technologies and a greater willingness to embrace change will put them in a better position to incorporate AI into their operations.

According to a report by Sprout.ai, 59% of organizations have already implemented Generative AI in insurance. It brings multiple benefits, including enhancing staff efficiency and productivity (61%), improving customer service (48%), achieving cost savings (56%), and fostering growth (48%). Fraudulent claims can now be enhanced and embellished in new and convincing ways with GenAI, including the generation of fake imagery and the creation of personas that act human. Insurers could also incorporate additional layers of verification in the claims process, such as the use of biometrics, geolocation data, and image recognition to validate the authenticity of claims.

Operating model

Instead of building or buying, many insurers are testing the waters with partnerships. Insurance executives should plan now to chart a course that can adapt as the technology evolves. GenAI can also dive into mundane details faster and more efficiently than people. It can scroll through the complex terms and conditions typically present in commercial policies and quickly assess the validity of the claims coverage.

  • Insurers that embrace it stand to gain a competitive edge by leveraging its capabilities to meet the evolving needs of their customers and the industry.
  • Similarly, in the UK, the Association of British Insurers (ABI) reported a 25% increase in motor insurance premiums in 2023 compared to the previous year.
  • Likewise, vehicles will still break down, natural disasters will continue to devastate coastal regions, and individuals will require effective medical care and support when a loved one passes.
  • Generative AI can map patterns and connections within the data inputs, allowing it to understand the essence and context of an object.

The insurance industry is poised to harness the latest technologies, including artificial intelligence (AI), to innovate and shape the future. The field of robotics has seen many exciting achievements recently, and this innovation will continue to change how humans interact with the world around them. Additive manufacturing, also known as 3-D printing, will radically reshape manufacturing and the commercial insurance products of the future. By 2025, 3-D-printed buildings will be common, and carriers will need to assess how this development changes risk assessments. In addition, programmable, autonomous drones; autonomous farming equipment; and enhanced surgical robots will all be commercially viable in the next decade.

She noted AI tools in use by Orrick include DraftWise, a drafting and negotiation assistant, Kira, an AI contract analyzer, and WestLaw’s Precision, an AI-assisted research tool. Still, legal experts caution that future lawyers need to address the technology. Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7). Forecasts of a “well above-average” 2024 Atlantic are a timely warning for insurers and companies with portfolios and assets at risk. A recent session shows how convening leaders of at-risk communities can help provide them the tools they need to tackle climate change. Additionally, AI can prioritize quotes with the highest chance of closing based on past successes.

Fraudulent Activities Threat Management

As soon as the car stops moving, its internal diagnostics determine the extent of the damage. His personal assistant instructs him to take three pictures of the front right bumper area and two of the surroundings. By the time Scott gets back to the driver’s seat, the screen on the dash informs him of the damage, confirms the claim has been approved, and reports that a mobile response drone has been dispatched to the lot for inspection. If the vehicle is drivable, it may be directed to the nearest in-network garage for repair after a replacement vehicle arrives.

gen ai in insurance

Gen AI also enhances support services quality during the indemnification process. It provides policyholders with real-time updates and clarifications on their requests. Furthermore, the technology predicts and addresses common questions, offering proactive assistance – a must-have for elderly people. Besides the benefits, implementing Generative AI comes with risks that businesses should be aware of. A notable example is United Healthcare’s legal challenges over its AI algorithm used in claim determinations.

gen ai in insurance

Harnessing the technology will require experimentation, training, and new ways of working—all of which take time before the benefits start to accrue. The technology will augment insurance agents’ capabilities and help customers self-serve for simpler transactions. GenAI gives insurers the ability to analyze vast amounts of data from multiple sources, including customer profiles, historical claims data, and external databases. This allows them to assess risk factors accurately and make more informed decisions regarding claim eligibility.

Today, we work closely with clients to embrace a transformational approach aimed at benefiting all stakeholders—empowering organizations to grow, build sustainable competitive advantage, and drive positive societal impact. In addition to productivity gains, there is significant potential to save cost on claims management during the claims settlement process. While considerable efficiency gains of 20% to 30% can be achieved through streamlined documentation, these effects will be dwarfed by the savings generated from reducing assessor-related spending using end-to-end automated claims appraisals. Generative AI models can generate thousands of potential scenarios from historical trends and data. The insurance companies can use these scenarios to understand potential future outcomes and make better decisions.

Insurers adopting this approach rethink the entire customer journey and internal processes within a vertical, making the most of the new possibilities afforded by GenAI. One prime example is the end-to-end automation of the claims process in auto insurance. Using an uploaded image, GenAI can automatically generate an instant settlement offer, relying on an archive of millions of vehicle damages photos and incident reports.

Even traditional risk information can be overwhelming, with the result that underwriters are unable to give submissions they review the attention they deserve. As a result, risk assessment is increasingly patchy and imprecise, pricing is inexact, and the process can be daunting. Add disinformation to these concerns, such as erroneous or manipulated output and harmful or malicious content, and it is no wonder regulators are seeking to mitigate potential harms. Regulators seek to establish legal certainty for companies engaged in the development or use of gen AI. Meanwhile, rule makers want to encourage innovation without fear of unknown repercussions.

Equipped with the latest Intel® vPro, Evo™ Edition featuring Intel Core Ultra processors, integrated NPU, and up to the NVIDIA RTX™ 3000 Ada Generation laptop GPU, the ThinkPad P1 Gen 7 delivers incredible power and performance. By harnessing the collective strength of the CPU, NPU, and GPU, this Lenovo workstation is optimized to meet AI processing requirements effectively. Justin St-Maurice is a Principal Research Director at Info-Tech Research Group. He specializes in helping Technology Service Providers modernize service delivery models by using business reference architectures, industry insights, and systems thinking. He also supports cloud engineering teams as a technical counselor, utilizing his professional certifications in solution architecture, development, and data analytics to build and manage modern systems.

Generative AI can be used to simulate different risk scenarios based on historical data and calculate the premium accordingly. For example, by learning from previous customer data, generative models can produce simulations of potential future customer data and their potential risks. These simulations can be used to train predictive models to better estimate risk and set insurance premiums. In addition to performance, Lenovo workstations are known for their reliability and security. Lenovo prides itself in producing high-quality products that customers can depend on, day in and day out.

For large-scale catastrophe claims, insurers monitor homes and vehicles in real time using integrated IoT, telematics, and mobile phone data, assuming mobile phone service and power haven’t been disrupted in the area. When power goes out, insurers can prefile claims by using data aggregators, which consolidate data from satellites, networked drones, weather services, and policyholder data in real time. This system is pretested by the largest carriers across multiple catastrophe types, so highly accurate loss estimations are reliably filed in a real emergency. Detailed reports are automatically provided to reinsurers for faster reinsurance capital flow. Large-scale adoption of GenAI does present some risks, as well as a number of technical implications for organizations to consider—among them the ability to keep personal customer data secure. What approaches are leading insurers taking to transform their businesses through GenAI?

Increasing customer convenience and engagement are key to loyalty in an industry where personalized experiences are most valued. But how AI will ultimately enhance productivity and performance, and deliver the benefits and ROI are still being understood. Four core technology trends, tightly coupled with (and sometimes enabled by) AI, will reshape the insurance industry over the next decade. Apart from assisting employees, GenAI applications provide fresh opportunities to boost sales and cross-selling. GenAI lends new strength to “next best action” engines based on traditional machine learning, for instance, and could enable hyper-personalized policies, even for retail clients.

Lenovo unveiled new business and consumer laptops designed to unlock new AI experiences and boost productivity, creativity and efficiency. The new Lenovo ThinkPad X1 Carbon, ThinkPad X1 2-in-1, and IdeaPad Pro 5i are Intel Evo laptops powered by the latest Intel Core Ultra processors and Windows 11 that deliver optimal power efficiency, performance, and immersive experiences. Dedicated AI acceleration support will help users embrace new experiences and enhance efficiency in work and play, including capabilities enabled by Copilot in Windows. Whether for business or leisure, these Lenovo laptops are amongst the first that are driving an AI PC revolution that will fundamentally change how people create, collaborate, and interact with PCs. Designed to offer users the most comprehensive PC experiences yet, the new ThinkPad X1 and IdeaPad Pro 5i will help users embrace a new generation of AI computing.

Getting to scale means that businesses will need to stop building one-off solutions that are hard to use for other similar use cases. One global energy and materials company, for example, has established ease of reuse as a key requirement for all gen AI models, and has found in early iterations that 50 to 60 percent of its components can be reused. This means setting standards for developing gen AI assets (for example, prompts and context) that can be easily reused for other cases. Part of the training for maintenance teams using a gen AI tool should be to help them understand the limitations of models and how best to get the right answers.

For example, Generative Artificial Intelligence can collect, clean, organize, and analyze large data sets related to an insurance company’s internal productivity and sales metrics. With Generative AI making a significant impact globally, businesses need to explore its applications across different industries. The insurance sector, in particular, stands out as a prime beneficiary of artificial intelligence technology. In this article, we delve into the reasons behind this synergy and explain how Generative AI can be effectively utilized in insurance.

In other words, AGI is “true” artificial intelligence as depicted in countless science fiction novels, television shows, movies, and comics. Learn what artificial intelligence actually is, how it’s used today, and what it may do in the future. The COVID-19 pandemic has disrupted global supply chains, causing shortages in new and used cars. This scarcity has driven up the cost of car parts and vehicle replacements, further increasing the cost of car insurance. Additionally, the rise in car hire costs due to vehicle shortages has added to the financial pressures on insurers. Accident rates have climbed, partly due to the increased use of mobile devices while driving, leading to more distracted driving incidents.

The influx of requests for proposal (RFPs) can produce unwanted friction and increase quote turnaround time. AI can assist underwriting managers in suggesting the most effective distribution of quotes across the underwriting team, taking into account an individual underwriter’s current capacity, their expertise and their performance history. Underwriters have varying levels of expertise across different products and quote complexities. As a result, quotes might be sitting for days or even weeks before they can be turned around.

While gen AI might help with productivity in such cases, it won’t create a competitive advantage. Artificial intelligence (AI) is the theory and development of computer systems capable of performing tasks that historically required human intelligence, such as recognizing speech, making decisions, and identifying patterns. AI is an umbrella term that encompasses a wide variety of technologies, including machine learning, deep learning, and natural language processing (NLP). By using AI-powered chatbots, group insurers can provide immediate assistance and answers to customer queries, providing a better customer experience. These tools can be trained to learn an insurance company’s products, policies and general “language,” helping customers fully understand their benefits plan.

If a claim does not align with expected patterns, Generative AI can flag it for further investigation by trained staff. This not only helps ensure the legitimacy of claims but also aids in maintaining the integrity of the claims process. Typically, underwriters must comb through massive amounts of paperwork to iron out policy terms and make an informed decision about whether to underwrite an insurance policy at all. Helvetia has become the first to use Gen AI technology to launch a direct customer contact service. Powered by GPT-4, it now offers advanced 24/7 client assistance in multiple languages.

As part of an effort to upskill the entire enterprise to better work with data and gen AI tools, they also set up a data and AI academy, which the dispatchers and service operators enrolled in as part of their training. To provide the technology and data underpinnings for gen AI, the chief data and AI officer also selected a large language model (LLM) and cloud provider that could meet the needs of the domain as well as serve other parts of the enterprise. The chief data and AI officer also oversaw the implementation https://chat.openai.com/ of a data architecture so that the clean and reliable data (including service histories and inventory databases) needed to build the gen AI tool could be delivered quickly and responsibly. InsurTech Magazine connects the leading InsurTech executives of the world’s largest and fastest growing brands. Our platform serves as a digital hub for connecting industry leaders, covering a wide range of services including media and advertising, events, research reports, demand generation, information, and data services.

Intelligent chatbots or voice-bots powered by GenAI provide policyholders with instant access to information and assistance. It can also guide customers through the claims process, offering step-by-step instructions and collecting necessary information for a seamless experience. The customer journey is gradually becoming a more omnichannel experience, with a significant portion of remote interaction directly with the insurance company. This starts with the first notice of loss and increases in the subsequent phases of the claim. GenAI virtual assistants have the potential to revolutionize such customer interactions, though the speed of the transition varies widely by market and company. They can enhance customer satisfaction, reduce wait times, and provide round-the-clock support, ultimately improving the overall customer experience.