Everest launches AI-powered health insurance in Singapore

Doing so presents opportunity risks through reducing organizational knowledge, cutting abilities to develop new products and processes, and the risk of being overtaken by more technologically confident peers. This report is intended to support insurance leadership teams in using AI to transform their organizations. It also brings together insights from KPMG professionals and industry leaders from Generali Italia, PassportCard, Prudential and Zurich Australia who share their perspectives on how to unlock the technology’s full potential. As AI transforms auto insurance, concerns about algorithmic bias and data privacy remain pivotal. Advanced AI systems often rely on extensive vehicular data, necessitating rigorous data protection practices to maintain user trust.

Their insurance partners should strive to understand their business, identify areas of concern and craft coverage customized to meet their needs. For insurance partners, analyzing and aligning with their clients’ culture helps to solidify partnerships, chatbot insurance as well as open the lines of communication and understanding. “We believe that building and maintaining strong, long-lasting relationships with our customers is essential to navigating the inevitable fluctuations of the insurance market.

More Risk Transfer

By understanding the factors contributing to their risk assessment, policyholders can prioritize mitigation actions effectively, potentially reducing their overall risk profile and minimizing potential losses. Senior executives report higher confidence, with 75% of directors, 74% of vice presidents, and 73% of C-level officers believing their company is ahead of the industry in climate risk adaptation. In contrast, only 60% of managers and 64% of individual contributors share this level of confidence. Additionally, the proposal’s increased burden of proof on AI providers and users would also harm, rather than support, innovation and encourages litigation due to vague thresholds. With this approach, Munich Re is able to determine the predictive robustness of the AI, quantifying, for example, the probability and severity of model underperformance. Overarching AI related risks with respect to data privacy, data protection and confidentiality remain.

Insurers should continue to explore low-risk, high-reward AI use cases to help claims adjusters do their jobs more efficiently. For example, AI could help detect and prevent fraudulent claims or offer predictive insights. Seeking partnerships with AI solution providers that integrate with internal apps is a strong approach as well.

Harnessing AI And Gradient Boosting For Insurance Premium Modeling

As the Claims Director at ANDE-UK, I see the transformative potential of Artificial Intelligence (AI) not only in helping us meet regulatory requirements; it is also enhancing that customer-centric approach. Those using it significantly in customer-facing systems report a 14% higher retention rate and a 48% higher Net Promoter Score, the survey found. Insurers leveraging GenAI across direct, agent and bank assurance sales channels are seeing significant improvement in sales, customer experiences and customer acquisition costs, the survey found. Elad Tsur, former CEO and co-founder of Planck, acquired by Applied Systems, shared his thoughts on the future of AI and the insurance industry with Digital Insurance at ITC Vegas 2024.

The technology is at a nascent stage in the insurance industry and many chatbots do frustrate customers. Yet even in Australia (the least receptive of the countries shown in the chart) over one in five customers are open to the technology. The AI ecosystem, which is powered by Majesco Copilot, was introduced to help streamline operations in the insurance sector. Majesco is committed to advancing digital transformation, and this new product leverages ChatGPT App AI to automate tasks, improve efficiency, and offer advanced data insights. AI is advancing quickly, with breakthroughs now spanning beyond language models to areas like weather forecasting, including hurricane landfall predictions[6]. It is entirely plausible that within a few years, AI will not only generate natural catastrophe scenario narratives but also produce synthetic hazard data for these scenarios, such as hurricane wind fields.

Newsletters

This translates to faster payouts for customers and allows Prudential to manage a higher volume of claims, he added. One area that has sparked concern in the industry is the potential for AI to eliminate jobs. Queen asserts that much of the panic around AI-induced job losses is due to bad information and misunderstanding. You can foun additiona information about ai customer service and artificial intelligence and NLP. “AI is mostly just a buzzword for machine learning,” Queen said, emphasising that while machine learning is a powerful tool, it does not pose an imminent threat to employment in captive insurance.

The insurance industry is poised to harness the latest technologies, including artificial intelligence (AI), to innovate and shape the future. Insurance giant Prudential is tapping Google’s MedLM, a family of foundation models fine-tuned for healthcare industry use cases, to transform the complex and fragmented health insurance experience for its customers. “Wielded by a qualified data engineer or data scientist, AI tools offer deeper insights into risk than ever before,” Queen explained.

The adoption of AI in insurance may lead to job displacement, particularly in roles traditionally performed by humans, such as underwriting, claims processing, and customer service. Using the data, insurers can better assess risks and increase operational efficiencies. Among the other areas in which AI can be transformative for the insurance sector are improving underwriting processes, claims management, customer service and future trends prediction.

This suggests insurers should look to integrate AI into their operations going forward. Even if not all customers want to use it, the technology will appeal to new customers and reduce the strain on staff and phone lines. It is also important to note that the quality and specificity of a prompt provided to an LLM can significantly influence the accuracy, relevance, and usefulness of the scenario produced. Investing time in prompt engineering – the practice of carefully crafting inputs to elicit the desired outputs from generative AI – is therefore vital.

Contact your local member firm to talk through insights from this article, or to discuss your unique technology and AI requirements. The KPMG 2023 Insurance CEO Outlook also highlights a significant degree of trust in AI with 58 percent of CEOs in insurance feeling confident about achieving returns on investment within five years. If you aren’t yet a client, you can download our complimentary Predictions guides, which cover more of our top predictions for 2025.

Enhancing Customer Experience

Our aim is to continue driving employee efficiency and creativity and thus achieving better results for our clients. What is important is the users of this novel technology always remain in control; they decide when to use what kind of AI-powered outcomes in a secure environment. While traditional AI has already demonstrated its prowess in insurance, the industry is yet to explore generative AI’s full potential, while also keeping track of its emerging risks. At Swiss Re, we have been testing the capabilities of large language models (LLMs) for more than three years. Selected use cases have been deployed to pilot user groups and we expect to deploy them to a broader user base this year. Artificial intelligence (AI), in its present form, has proven invaluable in insurance, providing more accurate data insights, enhancing operational efficiency and fostering innovation.

Agentech’s platform currently automates up to 50% of manual tasks for desk adjusters, resulting in faster claims processing, improved customer satisfaction, and increased accuracy. The company integrates seamlessly with existing claims management systems, enhancing overall efficiency without disrupting operations. Rohan Malhotra is the CEO, founder and director of Roadzen, a global insurtech company advancing AI at the intersection of mobility and insurance. Roadzen has pioneered computer vision research, generative AI and telematics including tools and products for road safety, underwriting and claims.

How can the world’s largest global law firm help you today ?

Mea platform is set to bolster AXIS Capital‘s operational efficiency by leveraging its advanced GenAI technology, as part of its renewed partnership. Insurers must ensure the seamless integration of AI in claims management from the outset, or risk discouraging consumers from embracing automated tools. While insurers and customers agree on the importance of using generative AI to deliver personalized pricing or promotions, many insurers haven’t yet translated that view into action.

• Their cloud-based software enables insurers to modernise their operations and deliver customer-centric experiences.
• Those using it significantly in customer-facing systems report a 14% higher retention rate and a 48% higher Net Promoter Score, the survey found.
• While race, gender, or income might not be direct variables, proxy factors highly correlated with these characteristics could lead to unfair pricing models.
• The company’s flagship product GridProtect will offer immediate, technology-driven financial relief businesses impacted by power outages responsible for $150 billion in annual losses.
• Since 2002, Cake & Arrow has partnered with leading insurance and finance companies, including MetLife, Aflac, Citigroup, Travelers, Chubb, Amwins, and The General.

Increasing global demand for insurance services necessitates a continuous quest to optimise processes across the entire value chain. We will go through a steep learning curve this year when it comes to applying generative AI – it is ChatGPT an exciting time to be at the confluence of insurance and digital technology. A GlobalData poll reveals that most insurance insiders believe AI has not met expectations yet, but they remain optimistic about its future potential.

Leading digital product organizations are already leveraging AI to research consumer and user needs, understand product usage, and synthesize customer feedback. For insurers, this translates into delivering not just personalization, but an actual match between customers, their risks, and the insurer’s products. Executives anticipate this AI-powered approach will accelerate product creation in 2025, reducing time to market by 3.6 months and increasing the number of new products launched by 50%. In the words of Queen, the key takeaway is that AI is “a net benefit for captive professionals” when wielded by qualified individuals. As the technology matures, the captive insurance industry stands to benefit from deeper insights and more sophisticated tools—ushering in a new era of innovation and efficiency.

• “Leaders should have the room to concentrate on their vision for the company and what it can achieve — not be burdened by potential risks that keep them awake at night.
• As AI systems take over repetitive and analytical tasks, the human workforce can shift towards roles that require empathy, ethical judgment, and complex problem-solving.
• At Swiss Re, we have been testing the capabilities of large language models (LLMs) for more than three years.
• Two recent One Call hires demonstrate the positive effect external talent and perspectives have on bringing forth successful workers’ compensation solutions.

As both companies deepen their partnership, the use of mea’s AI-driven technologies is set to play a critical role in AXIS’s long-term strategy to deliver faster, more accurate services. Similar technology can be used to summarise customer interactions, saving the handler having to complete extensive notes after a call and allowing them to immediately support another customer. The key is to ensure we achieve the optimum human/AI collaboration because nothing will replace the human touch when it’s needed most. When combined with live voice transcription, AI can listen and provide handlers with answers and next best action recommendations in conversations with customers. This ensures that handlers have the information they need to provide timely and accurate support, directly contributing to positive customer outcomes as mandated by the Consumer Duty. Only 26% of customers trust the reliability and accuracy of advice from generative AI.