Gen AI Innovation in the Insurance Industry Deloitte US

gen ai in insurance

For example, there may be public health datasets that show what percentage of people need medical treatment at different ages and for different genders. Generative AI trained on this information could help insurance companies know whether or not to cover somebody. In the underwriting process, smart tools are embedded to assess and price risks with greater accuracy. For instance, GAI facilitates immediate routing of requests to partner repair shops. This advanced approach, integrating real-time data from sources like health wearables, keeps insurers abreast of evolving trends.

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.

Getting Started with Generative AI in Insurance: Benefits and Use Cases – Coverager

Getting Started with Generative AI in Insurance: Benefits and Use Cases.

Posted: Tue, 11 Jun 2024 06:02:42 GMT [source]

This content creating powerhouse can do everything from text, image, and video generation to answering questions through natural language queries. Setting up a cohesive approach covering all these dimensions will be key for insurance leaders to unlock the full power of GenAI. It will enable them to steer clear of disjointed and loosely connected applications, guide them on where to focus key resources, and set their organizations on a trajectory that will leave them fundamentally transformed. These applications are early-stage examples, providing simple yet significant capabilities. As the technology evolves, more sophisticated applications will further leverage conventional machine learning for enhanced functionality.

The Generative AI’s self-learning capability guarantees continuous improvement in predictive accuracy. This also gives them a competitive edge in the market, as the providers of fair and financially viable policies. It actively identifies risk patterns and subtle anomalies, providing a comprehensive overview often missed in manual underwriting. This way companies mitigate risks more effectively, enhancing their economic stability. Artificial intelligence adoption has also expedited the process, ensuring swift policy approvals.

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.

Gen AI in Insurance

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.

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.

Personalize Products and Services

Advanced algorithms handle initial claims routing, increasing efficiency and accuracy. Embracing AI isn’t a bold move; it’s a necessary step towards the future of work in the insurance industry. And it requires significant behavior and mindset shifts for successful, sustainable transformation. In addition, generated synthetic data might not perfectly represent the complexities and nuances of the real world. For portability, the Lenovo Yoga Slim 7i (14”, 9) is a thin and light Intel Evo™ edition premium laptop powered by Intel Core Ultra Processors and a WUXGA OLED screen.

It also alerts him that his life insurance policy, which is now priced on a “pay-as-you-live” basis, will increase by 2 percent for this quarter. The Appian AI Process Platform includes everything you need to design, automate, and optimize even the most complex processes, from start to finish. The world’s most innovative organizations trust Appian to improve their workflows, unify data, and optimize operations—resulting in better growth and superior customer experiences. Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities.

Additionally, the COVID-19 pandemic led to a surge in insurance claims, ranging from business interruption to health-related costs. This unprecedented event has added pressure on reinsurers to adjust their pricing models to accommodate such large-scale, unexpected claims. Others may soon follow, as 85% of insurance executives globally say their organizations plan to increase spending on generative AI this year, according to Accenture’s most recent Pulse of Change survey. Almost three-in four (72%) are confident that they have the right data strategy and core digital capabilities – including the use of structured, unstructured and synthetic data – in place to effectively harness generative AI. For one, it can be trained on demographic data to better predict and assess potential risks.

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.

Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4).

Generating value from the AI use cases of the future will require carriers to integrate skills, technology, and insights from around the organization to deliver unique, holistic customer experiences. Doing so will require a conscious culture shift for most carriers that will rely on buy-in and leadership from the executive suite. Developing an aggressive strategy to attract, cultivate, and retain a variety of workers with critical skill sets will be essential to keep pace. These roles will include data engineers, data scientists, technologists, cloud computing specialists, and experience designers.

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.

In other words, AGI is “true” artificial intelligence as depicted in countless science fiction novels, television shows, movies, and comics. You can foun additiona information about ai customer service and artificial intelligence and NLP. 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.

gen ai in insurance

We’ve seen engineers build a basic chatbot in a week, but releasing a stable, accurate, and compliant version that scales can take four months. That’s why, our experience shows, the actual model costs may be less than 10 to 15 percent of the total costs of the solution. It’s important to bear in mind that successful gen AI skills are about more than coding proficiency. A pure coder who doesn’t intrinsically have these skills may not be as useful a team member. Much of gen AI’s near-term value is closely tied to its ability to help people do their current jobs better.

Understanding the Factors Behind High Car Insurance Premiums

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.

It streamlines policy renewals and application processing, reducing manual workload. Consequently, it frees staff to focus on more strategic, customer-centric duties. As with any nascent technology, new risks are emerging in areas such as hallucination, data provenance, misinformation, toxicity, and intellectual property ownership. To manage risks, insurers should adopt a responsible AI strategy that relies on successive waves of use cases, testing and learning as they go (see Figure 2).

Auto accidents will be reduced through use of vehicles with self-driving capabilities, in-home flooding will be prevented by IoT devices, buildings will be reprinted after a natural disaster, and lives will be saved and extended by improved healthcare. 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. As these changes take root, profit pools will shift, new types and lines of products will emerge, and how consumers interact with their insurers will change substantially. The experience of purchasing insurance is faster, with less active involvement on the part of the insurer and the customer.

InScope leverages machine learning and large language models to provide financial reporting and auditing processes for mid-market and enterprises. Info-Tech Research Group is one of the world’s leading research and advisory firms, proudly serving over 30,000 professionals. The company produces unbiased, highly relevant research and provides advisory services to help leaders make strategic, timely, and well-informed decisions. For nearly 30 years, Info-Tech has partnered closely with teams to provide them with everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

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.

Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2). Integrating AI into insurance technology would allow for continuous risk assessment and, thus, adjustment of premiums. Once the raw data has been captured, it can be converted to structured data in the insurance company’s format and sent directly to their quoting portal or underwriting workbench. To assemble a group benefits quote, sales and underwriting teams need to collect and process several key pieces of information from different sources. The exact future of legal obligations is still unclear and may differ across geographies and depend on the specific role AI will play within the value chain. Still, there are some no-regret moves for organizations, which can be implemented today to get ahead of looming legal changes.

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.

One insurance company, for example, created a gen AI tool to help manage claims. As part of the tool, it listed all the guardrails that had been put in place, and for each answer provided a link to the sentence or page of the relevant policy documents. The company also used an LLM to generate many variations of the same question to ensure answer consistency.

Another threat is financial loss from falloff in customer or investor trust that could translate into a lower stock price, loss of customers, or slower customer acquisition. The incentive to move fast is heightened by the fact that if the right governance and organizational models for AI are not built early, remediation may become necessary later due to regulatory changes, data breaches, or cybersecurity incidents. Fixing a system after the fact can be both expensive and difficult to implement consistently across the organization. Finally, insurance companies can use Generative Artificial Intelligence to extract valuable business insights and act on them.

Future junior lawyers won’t be replaced by AI, as some fear, but they will need to harness it to be successful, said Brendan McDonnell, a K&L Gates partner and member of the firm’s AI solutions group. That includes understanding how to effectively interact with generative AI chatbots to unearth the most useful information for clients, he said. Personalized medicine and targeted therapies are becoming a reality, thanks to AI’s ability to analyze vast amounts of genetic and molecular data. Sun Life’s AI-enabled “digital coach,” Ella, encourages plan members to take action on important deadlines, cost-savings and product offerings.

What is generative AI?

GenAI’s exponential growth in the market has forced organizations to assess the gaps in their current technology and security landscape to make the organization AI-ready. EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. The transformative power of this technology holds enormous potential for companies seeking to lead innovation in the insurance industry. Amid an ever-evolving competitive landscape, staying ahead of the curve is essential to meet customer expectations and navigate emerging challenges. As insurers weigh how to put this powerful new tool to its best use, their first step must be to establish a clear vision of what they hope to accomplish.

The hotel guest management technology company’s platform digitizes the hotel guest journey from post-booking through checkout. LinkedIn is launching new AI tools to help you look for jobs, write cover letters and job applications, personalize learning, and a new search experience. To apply for media passes to cover the insights presented at Info-Tech LIVE or to gain access to research and expert insights on trending topics, please contact [email protected]. For example, self-driving cars use a form of limited memory to make turns, observe approaching vehicles, and adjust their speed. However, machines with only limited memory cannot form a complete understanding of the world because their recall of past events is limited and only used in a narrow band of time.

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.”

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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 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.

The integrated NPU is dedicated to handling light, continuous AI tasks, while the NVIDIA GPU runs more demanding day-to-day AI processing. This combination enables smooth and reliable functioning of AI technologies, serving professionals engaged in diverse tasks ranging from 3D modeling and scene development to AI inferencing and training. April 23, 2024 – Today, Lenovo™ launched its latest mobile workstation offerings meticulously crafted to deliver the exceptional power and performance essential for handling complex workloads.

To retain knowledge while also ensuring the business has the new skills and capabilities necessary to compete, many organizations will design and implement reskilling programs. As a last component of developing the new workforce, organizations will identify external resources and partners to augment in-house capabilities that will help carriers secure the needed support for business evolution and execution. The IT architecture of the future will also be radically different from today’s. Carriers should start making targeted investments to enable the migration to a more future-forward technology stack that can support a two-speed IT architecture. NVIDIA RTX Ada Generation laptop GPUs with Tensor Core technology for AI processing offer powerful AI, ray-tracing, and graphics capabilities to tackle a variety of professional creative, design, and engineering workflows. NVIDIA AI Workbench gives data scientists and developers the freedom to work, manage, and collaborate across Lenovo laptops, workstations, and servers.

For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found last year—as well as meaningful revenue increases from AI use in marketing and sales. And many fintechs and insurtechs are at the forefront of applying generative AI to assess underwriting risks and transform insurance operations. Failure to handle AI and gen AI prudently can lead to legal, reputational, organizational, and financial damages; however, organizations can prepare themselves by focusing on transparency, governance, technology and data management, and individual rights. Addressing these areas will create a solid basis for future data governance and risk reduction and help streamline operations across cybersecurity, data management and protection, and responsible AI.

The ThinkCentre neo Ultra exploits the very latest technology to deliver a new generation of ultra small form factor AI PC, and the ThinkCentre neo 50a Gen 5 all-in-one desktop will be available in 24- and 27-inch form factors. The Lenovo ThinkBook laptops, ThinkCentre neo desktops, and the Magic Bay Studio are the latest products and accessories that showcase Lenovo’s innovation and leadership in the SMB market. Users can leverage GPU-accelerated AI to enhance workflows in a wide range of applications, including content creation, rendering, and business productivity tools. The seamless integration of NVIDIA RTX technology, with Intel Core Ultra processors, boosts the overall performance, enabling professionals to reduce time to outcome. “Lenovo’s latest ThinkPad P series mobile workstations are taking a significant step forward by featuring cutting-edge Intel Core Ultra processors equipped with a dedicated neural processing engine. The latest ThinkPad P series mobile workstations powered by Intel Core Ultra processors and NVIDIA RTX™ Ada Generation GPUs deliver flexible, high-performance, and energy-efficient AI-ready PCs.

This, in turn, boosts customer satisfaction, which eventually leads to increased retention and cross-selling opportunities. Generative AI models can be employed to streamline the often complex process of claims management in an insurance business. They can generate automated responses for basic claim inquiries, accelerating the overall claim settlement process and shortening the time of processing insurance claims.

Per MIT, the incorporation of diffusion models improved task performance by 20%. That includes the ability to execute tasks that require multiple tools, as well as learning/adapting to unfamiliar tasks. The system is able to combine pertinent information from different datasets into a chain of actions required to execute a task. TORONTO, June 12, 2024 /PRNewswire/ – Global IT research and advisory firm Info-Tech Research Group has announced the next round of keynote speakers for the upcoming Info-Tech LIVE 2024 conference. This new lineup of featured experts will complement the previously announced keynote speakers, Dr. Timnit Gebru and Meredith Whittaker.

It will introduce transformative capabilities to the industry, offering innovative solutions across the insurance value chain—from customer service, sales, and marketing at the front end to underwriting and claims processing at the back end. These value-driven opportunity areas will have a significant and tangible impact on insurers’ bottom line, from growth to cost savings. The world of artificial intelligence (AI) continues to evolve rapidly, and generative AI in particular has sparked universal interest. This is certainly the case for the insurance industry, where generative AI is fundamentally reshaping everything from underwriting and risk assessment to claims processing and customer service.

Generate customized recommendations and experiences for customers based on their preferences and behaviors. It is the combination of a predominant mindset, actions (both big and small) that we all commit to every day, and the underlying processes, programs and systems supporting how work gets done. Helping clients meet their business challenges begins with an in-depth understanding of the industries in which they work.

Fore more on risk assessment, check out our article on the technologies to enhance risk assessment in the insurance industry. Generative AI can analyze existing customer data and create synthetic data from the existing data, which can be particularly useful when there’s a lack of certain types of data for modeling. Cem’s work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence. Last but not least are the new Lenovo Yoga 7i 2-in-1 (16”, 9) and Lenovo Yoga 7i 2-in-1 (14”, 9) convertible laptops that give creators on the go quick access to tools that complement their creativity.

CEOs will be uniquely positioned to help their organizations support human and Gen AI teams across the enterprise and unlock the value of their talent. Answer customer inquiries in real-time and provide customer service agents with summarized and all relevant customer information. Latest market insights and forward-looking perspectives for financial services leaders. Latest market insights and forward-looking perspectives for financial services leaders and professionals.

These information sources enable insurers to make ex ante decisions regarding underwriting and pricing, enabling proactive outreach with a bindable quote for a product bundle tailored to the buyer’s risk profile and coverage needs. While this scenario may seem beyond the horizon, such integrated user stories will emerge across all lines of insurance with increasing frequency over the next decade. In fact, all the technologies required above already exist, and many are available to consumers. With the new wave of deep learning techniques, such as convolutional neural networks,1Convolutional neural networks contain millions of simulated “neurons” structured in layers. Artificial intelligence (AI) has the potential to live up to its promise of mimicking the perception, reasoning, learning, and problem solving of the human mind (Exhibit 1). In this evolution, insurance will shift from its current state of “detect and repair” to “predict and prevent,” transforming every aspect of the industry in the process.

Its evolving sophistication is reflected by the third of CEOs (32 percent) who are worried about increasing threats and the quarter (24 percent) who highlight vulnerable legacy systems. The KPMG global tech report also highlights that 63 percent of respondents either agree or strongly agree that improving cybersecurity and privacy will help them provide a loyalty-winning gen ai in insurance customer experience. Again, the KPMG global tech report reveals that better data management and integration have been the top benefits for 42 percent of respondents. They’re aware that data quality before cloud migration is key to effective AI applications, and that clean, well-organized data is essential for AI to ensure accurate, transparent and fair decision-making.

How insurers can leverage the power of generative AI – EY

How insurers can leverage the power of generative AI.

Posted: Thu, 18 Apr 2024 09:47:16 GMT [source]

Prior to joining Info-Tech, Wong was the AI and Data Analytics Practice Leader at Dell Technologies for five years. He also held consulting, development, product management, and executive roles at Microsoft, Oracle, and IBM. Brittany Lutes, MSc., Research Director, CIO PracticeBrittany Lutes is a Research Director in the CIO Practice at Info-Tech Research Group. She works alongside IT executives and functional IT leaders to create visual representations of how their IT organizations will achieve their strategic goals with an IT Operating Model and Organizational Structure.

gen ai in insurance

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, Chat GPT 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.

We also provide detailed documentation on their operations, enhancing transparency across business processes. Coupled with our training and technical support, we strive to ensure the secure and responsible use of the technology. With its natural language processing capabilities, GenAI can analyze claim documentation and extract relevant information, such as policy details, incident descriptions, and supporting documents. This automation leads to faster claims processing, allowing insurers to provide quicker resolutions to policyholders.

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