Gen AI with Allianz Trade, part 2: applications for trade credit insurance

Financial services firms are performing better because of technology investments but now they need to fine-tune their digital transformation journeys. This collaboration underscores AXIS’s commitment to digital transformation and improving service efficiency for its global client base. For example, ‘virtual agents’ can be highly effective in automating and resolving straightforward customer queries. With the right GenAI capability, virtual agents can respond to customers in a natural and conversational manner, while delivering precise answers whenever they need them. AND-E UK has seen 36% of calls successfully directed to virtual agents, freeing up human agents to deal with the more complex customer needs.

• This helps to democratise access to AI and foster a culture of innovation within the organisation.
• Rohan Malhotra is the CEO, founder and director of Roadzen, a global insurtech company advancing AI at the intersection of mobility and insurance.
• Some of the initial AI partners in the ecosystem include Charlee AI, CyberCube, Fenris, Gradient AI, and CoreLogic.
• While some companies have begun deploying GenAI for tasks like claims processing and underwriting automation, they’re often missing the bigger picture.
• Through natural language processing (NLP), AI can monitor communications and ensure that all customer interactions are transparent, fair, and within regulatory guidelines.

AI’s promise of transforming underwriting, claims, and customer experience remains untapped, and only a tiny fraction of insurers will harness its full potential by 2025. Tech-driven product innovation such as embedded insurance and usage-based insurance may yield faster results, but long-term AI gains remain on the horizon. Industry applications today predominantly rely on traditional AI methods with a focus on automating routine tasks and extracting insights from vast datasets. This technology has played a vital role in portfolio management, risk assessment, streamlining claims and submissions processing, making it more efficient for insurers and customers alike.

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. GBM for insurance premium modeling can help the handling of complex model relationships with improved predictive power. The need to balance the model performance and follow the regulatory requirements is crucial, and it can be managed by using tools like SHAP to make it more transparent. The process utilizes an initial model often with a constant prediction, such as the mean of the target variable for regression tasks like a decision tree with limited data depth. Limiting the depth ensures that each tree has high bias and low variance, making it a weak learner. Gradient boosting machines (GBMs) are a powerful ensemble learning technique that builds a model incrementally by combining weak models (typically decision trees) to form a strong predictive model.

For instance, AI-driven chatbots and virtual assistants are streamlining customer queries and claims processing, providing quick and CX-friendly responses 24/7. Generative AI (GenAI) already offers insurers a powerful way to better support customers. The key is to deploy this technology where it can best support customers, rather than just focusing on operational efficiency.

Transparency and accountability in AI systems are essential for fair and ethical operations. Insurers should provide detailed documentation and explanations of AI models, including data sources, algorithms, and decision-making criteria. To ensure ethical AI development and deployment, insurers must establish clear guidelines and policies. These should promote fairness, transparency, and accountability in AI-driven decisions, protect customer privacy, and mitigate biases. Insurers are keen to ensure that AI produces fair and equitable outcomes that represent customers’ best interests.

Products

Of the leaders surveyed who have already adopted AI risk models, 81% believe they are ahead of their competitors when adapting to the challenges of climate change. However, stochastic models remain the most popular approach for storms with 45% saying it is their go to tool and traditional actuary models based on historical data are favoured by 54% for wildfires. Alan said it has facilitated 900 conversations between its users and Mo over the past few weeks. But given that 680,000 people are currently covered by Alan’s health insurance products, Mo is quickly going to become a widely used healthcare-related AI chatbot. It will be interesting to see how people react to this new feature and how Alan tweaks the bot over time. While Alan is better known as a health insurance company, the French startup has always tried to offer more than insurance coverage.

Alan recently raised a $193 million funding round at an impressive $4.5 billion valuation. After France, Belgium, and Spain, the company last month announced plans to expand to Canada, where it will be the first new health insurance company in almost 70 years. In addition to the AI features, Alan unveiled a mobile shop from which users can buy dietary supplements, sports accessories, baby-related goods, and other health-adjacent products. But given that AI chatbots tend to hallucinate, healthcare professionals may not want to rely on inaccurate information or risk misdiagnosing a patient. This issue has come up in the news lately with AI-based medical transcriptions — eight out of ten audio transcriptions exhibited some level of hallucinated information, according to a study by a University of Michigan researcher. Clear communication, a strong relationship and emphasis on sustainability are just the start.

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.

Michel Josset outlines how automotive technology leader FORVIA Faurecia is now using the powers of AI to crunch a lot more data, getting them where they need to be in half the time. Our solutions architects are ready to collaborate with you to address your biggest business challenges. Equip your clients with a Roth IRA approach to navigate potential future tax increases effectively.

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Gen AI could enhance the processing of extra comments a customer may add to explain a situation, so our teams can provide faster responses to customers. You can foun additiona information about ai customer service and artificial intelligence and NLP. Additionally, gen AI may one day serve as an assistant to claims assessors, pre-assessing claims before the expert carries out a thorough analysis. However, avoiding AI altogether may also expose insurers to the risk of missing out on potential opportunities and benefits, and losing competitive advantage.

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.

It could also mean making transparency the norm or simply asking people what they need and encouraging everyone to contribute ideas. At the very least, it’s investing in training and development that help employees understand how to apply these new technologies effectively to benefit both personal and organizational productivity. Insurance companies are already transforming their operations, exploring new technologies and in some cases leading the charge on AI.

In practice, this could be setting up systems where feedback loops are integral and inform continuous improvement and adaptation. Beijing Dacheng Law Offices, LLP («大成») is an independent law firm, and not a member or affiliate of Dentons. 大成 is a partnership law firm organized under the laws of the People’s Republic of China, and is Dentons’ Preferred Law Firm in China, with offices in more than 40 locations throughout China. Dentons Group (a Swiss Verein) («Dentons») is a separate international law firm with members and affiliates in more than 160 locations around the world, including Hong Kong SAR, China. For more information, please see dacheng.com/legal-notices or dentons.com/legal-notices. Almost half (49%) of insurers have incurred fines for compliance lapses, spurring renewed attention to regulatory tools and frameworks.

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.

He should be an evangelist, too—last year, he observed, some 2.6 billion insurance quotes were run through Earnix’s platform. But tension remains between the ‘move-fast-and-break-things’ nature of AI and the wider insurance industry, which prefers its changes to be gradual and well considered – and ideally backed by decades of historical data. A significant proportion of consumers across the world are open to interacting with AI for their insurance policy, even in the often stressful situation of making a claim, according to a GlobalData survey.

“AI currently excels at automating repetitive tasks and assisting professionals in the captive insurance sector with routine activities. However, when it comes to more nuanced tasks such as deliberating what data to use for ratemaking, or issuing underwriting credits, AI remains largely supplementary, rather than a replacement for human expertise,” he said. BMO Insurance has introduced a new AI-powered digital assistant designed to enhance the field underwriting process for life insurance advisors.

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 ChatGPT 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.

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.

A quantum leap for financial services: Harnessing technology for innovation

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.

In such situations, the mind’s eye narrows, dismissing the unprecedented and sticking too closely to the beaten track of past experiences. This results in potential risk blind spots, leaving organizations vulnerable to highly disruptive events. To maximize ROI for AI investments, insurance companies should also ensure claims adjusters receive proper training on using it. Likewise, if they do not yet possess sufficient in-house expertise in related fields like data science, insurers should consider partnering with technology providers that have deep experience in the field. Insurers who carefully integrate AI into their claims processes will find themselves ideally positioned to maximize the ROI they seek. For starters, a global Workday study found that only 41% of surveyed insurance executives believe their organization has the skills to keep pace with emerging finance technology.

Insurers have also begun incorporating AI capabilities into other facets of the business, such as underwriting and the investigation of suspected fraud. As AI continues to impact how insurers are conducting business, various states are responding with regulatory frameworks to address purported risks. Accordingly, a patchwork of guidance has emerged, focused on governance, oversight, and disclosure regarding the use of consumer data and AI technology. The integration of AI into captive insurance has already demonstrated several key advantages, particularly in risk management, operational efficiency, and customer satisfaction. For firms with captives, AI offers the ability to analyse vast datasets and identify emerging risks with greater accuracy. From a business perspective, there are promising use cases applying LLMs to efficiently analyse and process large documents and datasets powered by advanced natural language processing (NLP) applications.

Issues like data privacy, algorithmic bias, and the potential for AI-generated errors (or “hallucinations”) pose significant risks. For instance, GenAI could be misused to generate fraudulent claims or manipulate images, exposing insurers to new forms of fraud. Creating a culture of innovation is not just equipping teams with the right tools but also inspiring them to think creatively about how to use them. From back office to front office, insurance functions can see potential benefits in automating claims handling, enhancing fraud detection, and optimizing agent and contact center operations. For now, these tend to be human-in-the-loop processes — with potential to fully automate. “There are also significant opportunities in connecting customers to the right products.

According to a recent KFF study, even when patients received care from in-network physicians, insurer denial rates reached 49% in 2021. Since risk management is in the very DNA of the insurance business, it is perhaps not a surprise that many insurers feel due diligence will be necessary before embracing a transformative technology like generative AI in insurance. Integrity Marketing Group, founded in 2006 and based in Dallas, Texas, is one of America’s top distributors of life and health insurance products.

Through this partnership, LWCC will utilize Akur8’s proprietary machine-learning technology, which facilitates accelerated model building and provides transparent Generalized Linear Model (GLM) outputs. This technology is set to transform LWCC’s approach to insurance pricing and risk assessment. The launch of the Majesco Copilot AI ecosystem is part of Majesco’s larger mission to foster innovation in the insurance sector by providing their customers with access to best-in-class AI solutions. This creates mutual benefits for the partners and Majesco’s customers, enhancing operational intelligence across the insurance industry.

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, 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.

• KPMG firms are excited about AI’s opportunities and equally committed to deploying the technology in a way that is responsible, trustworthy, safe, and free from bias.
• 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.
• It’s about trusting their character rather than just the policies and procedures in place,” Guild said.
• Insurance companies use this technology in a wide variety of ways, including for customer service needs, to expedite claims processing and more.

AI algorithms can assess various factors, such as driving behavior and accident history, to create personalized insurance policies that reflect the true risk of each driver. This level of accuracy not only improves profitability for insurers but also makes premiums fairer for customers. One reason many insurers struggle to scale AI initiatives is their reliance on isolated use cases that fail to deliver significant ROI. Instead, companies should consider reimagining entire business domains—like claims processing, underwriting, and distribution—by integrating GenAI with traditional AI and robotic process automation (RPA). This holistic approach allows for a complete overhaul of how data is collected, processed, and utilised across the organisation.

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 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.

The former could be the advent and rise of AI across the world’s industry, the latter might be applied to the pace set by the insurance industry. These collaborations bring cutting-edge AI solutions to Majesco’s clients, elevating the capabilities of its platform. Majesco, a leading provider of cloud-based insurance software, has announced the launch of its new AI ecosystem designed to streamline insurance workflows. Herman Kahn, an American futurist, is often credited as one of the pioneers of modern scenario planning. During the 1950s and 1960s, Kahn used scenarios at RAND Corporation and the Hudson Institute to model post-World War II nuclear strategies.

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 ChatGPT App 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.

AI-powered systems analyze accident data, assess damage through image recognition to automate the claims process, and assess driving behavior for personalized insurance premiums. They also know that innovation is a journey that requires ongoing effort, investment, and most importantly, a willingness to embrace change at all levels of the organization. While there are risks to every technology wave, the biggest risk could be missing the opportunity to shape what’s possible chatbot insurance in insurance. Artificial intelligence (AI) isn’t new in insurance — existing use cases are seen across risk modeling, data forecasting, claims handling and contact center operations, with an abundance of potential opportunities in the pipeline. The company plans to use the newly raised funds to further develop its platform, allowing insurance agencies to improve their workflows, offer better customer experiences, and scale their businesses with increased efficiency.

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.