New Cake & Arrow report explores how AI can humanize the insurance experience, ushering in a new golden age for the industry

These challenges contribute to doubts about whether AI will ever truly revolutionise the insurance industry in the way that many predict. The respondents who believe AI has already met expectations may represent those who have seen early successes in specific areas. For example, insurtech Lemonade has effectively used AI in customer service, using chatbots to handle routine inquiries and free up human agents for more complex tasks.

Customers are concerned about privacy, data security, potential scams, and inaccurate responses without sufficient oversight. Insurers, on the other hand, believe that AI ethics policies are sufficient to address these concerns. The survey found that 77% of insurance industry executives said they need to adopt GenAI quickly to avoid falling behind rivals. As a result, investments in GenAI are expected to surge by over 300% from 2023 to 2025 as insurers move from pilots to implementations across more business functions. Join the webinar to learn how Design Thinking techniques can bring insurance concepts to life, allowing insurers to capture richer, more actionable insights into customer needs and create more intuitive human-centric solutions. Dentons is a global legal practice providing client services worldwide through its member firms and affiliates.

Standard Chartered partners with RegTech to fight financial crime

This means that they can hallucinate, creating implausible scenarios that are not relevant to the world we live in. The 1990s then brought the digital revolution and the birth of catastrophe models that enabled (re)insurers to simulate a large number of hypothetical natural disasters quickly and at scale. Despite these advances, scenario science has remained a relatively static field of research, requiring a blend of foresight, analytical thinking, and – most importantly – imagination. Today, Royal Dutch Shell maintains a scenario team of over 10 people from diverse fields such as economics, politics, and physical sciences, which can take up to a year to develop a full set of scenarios[2]. Fifty percent of respondents to Insurity’s 2024 AI in Insurance Report oppose the idea of AI in claims management, and 45% don’t want it used in underwriting, either. As Insurity notes, consumers are especially skeptical about the notion of AI taking on more decision-critical roles in general.

The $3m seed round highlights investor confidence in Agentech’s potential to disrupt the insurance industry. The company was co-founded by InsurTech veterans Robin Roberson and Alex Pezold, both of whom have a track record of successful tech exits worth a combined $182m. The rapid advancements in AI, notably generative AI, outpace existing legal structures, prompting a need for updated regulatory measures. Recent initiatives, such as the US President’s chatbot insurance executive order, underscore the commitment to safe and secure AI deployment. This order, along with emerging global initiatives, aims to establish accountability and address the challenges posed by AI innovations in the insurance sector. The journey involves more than adopting new technology; it’s about transforming organisational processes, building the right capabilities, and making strategic decisions that position the company for long-term success.

VIPR welcomes new CRO to spearhead global expansion plans

Sandeep Kumar is a technology leader in artificial intelligence for SAP enterprise solutions and analytics. When approached strategically, using the GBM model for premium modeling can help impact the insurance sector where there are several variables to manage for predictive premium pricing. In insurance, features typically include customer data such as age, gender and region, as well as vehicle information like car type and the car’s age. Driving history, including accidents and claims, along with other relevant factors, also play a role. The target variable could be the premium amount or, in classification tasks, the probability of a claim. With the new funding, Agentech intends to expand its AI-driven technology into adjacent claims processes like First Notice of Loss (FNOL), reserving, and file review.

And yet there remains an inherent uncertainty of error for everyone, which is naturally inherent in any AI model. As risk is the source of our business model, Munich Re sees AI insurance as a strong growth area with a lot of potential. For example, job applicants who feel discriminated in the selection process could take legal action against the hiring organisation for an AI-supported decision. In addition to the risk of error with AI, there are other risks that we consider insurable. In the case of generative AI, we are looking at the risk of copyright infringement and discrimination. For both scenarios, we are currently cooperating with clients to structure specific insurance solutions.

• In the end, collaboratively, we finetuned the values and were providing an assessment that was consistent.
• Selected use cases have been deployed to pilot user groups and we expect to deploy them to a broader user base this year.
• It also notes that insurers “may have also been getting better at creating their own in-house data teams”, which could partly explain the drop-off.
• The study is based on a survey of 1,000 insurance c-suite executives and 4,700 insurance customers.

There is also growing recognition among insurers that a successful AI journey will likely be intrinsically linked to the maturity of their digital transformation. AI thrives on quality data and is best supported by cloud-based infrastructure and agile operating models; firms that are yet to fully embrace this are becoming aware of the urgency to do so. 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 customer experience.

In contrast, Australians were the least open to engaging with an AI tool for this purpose, with just 23% quite or very comfortable with the idea. … before turning to your favorite LLM, it’s important to note … the difference between AI-generated scenarios and AI-assisted scenario development. And I hope to report similar positive results with our climate goals as I have done with our property insurance. We experienced a lot of disagreement, for example, about the calculations of our exposed assets. The main pushback was that our insurers considered this as ‘more known’ before the new process.

Why is the insurance industry stuck?

You can foun additiona information about ai customer service and artificial intelligence and NLP. The company’s software-as-a-service platform is designed to help commercial insurers enhance their underwriting results, reduce claim costs and streamline operations. A year ago, we predicted a more stable, if not stellar, performance for insurers in 2024 after a couple of years of higher-than-expected claims costs. In 2025, we predict that insurers will continue to pass on higher costs of rising claims expenses to customers. This improving profitability will translate into increased tech spending as insurers prioritize innovation, data, AI, and automation, but most insurers won’t see immediate, material, and direct benefits from AI.

However, the organisation highlighted, mandatory insurance can only work for mature and homogenous markets, and this is not currently the case. Insurers can only support AI innovation within a framework guaranteeing contractual freedom. With this in mind, AI could reduce the strain on insurer’s phone lines and staff having to deal with such issues. On the other end of the spectrum, insurers in countries with consumers more receptive to using AI should be reacting ChatGPT App to consumer sentiment and investing strongly in the technology to stand out from their competitors. GlobalData’s 2024 Emerging Trends Insurance Consumer Survey found that well over a third (39%) of all respondents would be quite or very comfortable having an AI tool decide the outcome of an insurance claim. From the selected countries shown in the chart above, Brazilian consumers were the most open to AI in this scenario, with 51% being comfortable with it.

For Customers

Everest expanded its accident and health (A&H) offerings with the launch of Innovator, an artificial intelligence (AI) powered international private medical insurance product designed to enhance employee health coverage standards. While AI offers automation and efficiency, Schmalbach warns that firms must strike a balance between human oversight and automation. As such, it is important to maintain a human element in decision-making and ensure that AI systems are regularly monitored and updated to prevent errors. Despite the many advantages, the adoption of AI in captive insurance is not without challenges. One of the primary concerns is data privacy, as AI systems rely on the processing of large amounts of data to function effectively. Ensuring robust data protection measures is essential to prevent data breaches and maintain client trust.

Without the proper expertise in data science and other relevant fields, insurers may struggle to achieve their AI goals. In addition, claims adjusters and related personnel will require proper training to use AI for claims processing effectively. Gen AI offers some fascinating potential use cases specifically suitable for trade credit insurance.

Compliance with Consumer Duty involves demonstrating that we are consistently acting in the best interests of our customers. AI can aid in maintaining and proving compliance by providing a clear, auditable trail of decision-making processes. Through natural language processing (NLP), AI can monitor communications ChatGPT and ensure that all customer interactions are transparent, fair, and within regulatory guidelines. Consumer Duty ultimately requires insurers to put the customer at the centre of their business, prioritising customer outcomes by ensuring fairness, transparency, and clarity in all interactions.

Insurance executives see personalization as a service issue, but customers are looking for more fundamental changes. For example, 22% of insurers in direct and agent channels reported large or very large improvements in sales, while 29% reported similar gains in customer experience due to GenAI. However, the study also revealed a significant disconnect between insurers’ and customers’ expectations and trust in the technology, highlighting the need for careful strategy evaluation and responsible AI practices. IBM surveyed 1,000 insurance C-suite executives in 23 countries and 4,700 insurance customers in nine countries.

This anticipation is fueled by AI’s promise to transform underwriting, claims processing, and fraud detection, offering insurers the chance to boost efficiency and deliver more personalised services as the technology advances. By combining deep industry and functional knowledge with the right technologies, KPMG firms can help you to unlock business value and harness the full power and potential of AI with speed, agility, and confidence. KPMG professionals are experienced in developing proof-of-concepts and scaling these into integrated digital solutions. And these processes have been used internally to review and enhance KPMG firms’ capabilities. With this focus on transparency, compliance, and customer-centricity, insurers can leverage AI to provide clear insights into how data is used, ensuring clients understand AI applications and their benefits.

The funding will fuel the company’s expansion into new insurance claims workflows, including Property & Casualty (P&C), Workers’ Compensation, and Travel claims, according to InsurTech Insights. The report points to the surge in interest in artificial intelligence (AI) as a likely driver of that excitement. GlobalData figures show that the AI market grew in value from $81bn in 2022 to $103bn in 2023 – a rise of over 27%, with a greater still compound annual rate of 39% forecast between 2023 and 2030. As these technologies become more prevalent, the insurance landscape is shifting from reactive methods—such as processing claims after accidents—towards proactive strategies that emphasize prevention and safety. Their combined expertise in AI, machine learning, and treasury management is revolutionizing fintech, optimizing operations, and advancing financial strategies. These pilots should be designed to test critical assumptions and de-risk larger initiatives.

Despite the industry’s emphasis on AI for cost-cutting and efficiency, Cake & Arrow’s report stresses how AI can do more than automate and cut costs. While some experts caution against the overhyping of AI’s capabilities, others are optimistic about its potential to revolutionise risk management, underwriting, and operational efficiencies. However, the nuances of AI adoption in the captive insurance industry are complex, and there remain questions about the long-term implications. As the insurance industry grapples with evolving climate risks, transparency in risk assessment models has emerged as a critical concern.

Whilst this is mandated as part of the regulatory framework, it has also given insurers the opportunity to embed exceptional customer service and innovative practices that can drive long-term customer loyalty and satisfaction. This proactive approach not only ensures compliance; it can also position insurers as leaders in customer-centric service. While insurers and customers may not always see eye-to-eye on the priorities for generative AI, the technology presents significant opportunities for savvy insurers to jump ahead of competitors, IBM contends.

This gap underscores the slow progress in transitioning from traditional systems to advanced technology. The 2024 Earnix Industry Trends Report has revealed that the insurance sector faces pressing challenges with AI adoption, legacy system modernisation, and compliance pressures. Online pharmacies aren’t very common in France due to regulatory and logistics hurdles, so Alan could be well-positioned to offer over-the-counter drugs and more in the near future. We will look at what analysts and other third parties think about the information provided to try to glean what the investor base will think and how they will act. But ultimately, it is what the company says, and the way they say it, that we will assist in defending, if need be, and so we make sure to listen and learn from the company leadership. It’s about trusting their character rather than just the policies and procedures in place,” Guild said.

Customer service chatbots held the lion’s share of market growth in 2022, accounting for more than two-fifths of global insurance chatbot market revenue. While this kind of technology was already in the works before, the pandemic accelerated its development and adoption in sectors such as insurance with increasing demand for digital-first solutions. Regular audits and third-party reviews of AI models can ensure accuracy and fairness, helping insurers comply with evolving regulatory demands. However, AI also presents opportunities for employees to become more productive and competitive by automating repetitive tasks and providing faster access to vital information.

Described as the first AI-powered digital assistant of its kind in the Canadian individual life insurance industry, BMO’s solution aims to streamline the field underwriting process. The data clearly varies from country to country, which is something insurers must be aware of when launching new products and features in different geographies. However, the findings show that enough consumers are already open to interacting with AI to make it worthwhile to invest in.