Global Insurance Outlook :Regulators worldwide are actively working on guidelines and initial legislation for AI adoption. The widespread availability of GenAI apps in 2022 made the task more urgent. Industry groups would like to see the development of cross-jurisdictional standards, but regional variations — and a fragmented compliance landscape — seem more likely in the near term. The US is likely to go slow in adopting only limited regulation, while European insurers are preparing for comprehensive legislation in the form of the EU AI Act.
AI promises to deliver considerable benefits, from increased operational effectiveness and reduced costs, to elevated customer
experiences and greater predictive intelligence. But the risks — both financial and otherwise — are every bit as significant as the
potential benefits and closely intertwined. Consider the novel ability of GenAI to personalize product offerings and customer
communications; with that high degree of customization comes greater risk of privacy, suitability and discrimination violations.
Maximizing AI ROI requires a comprehensive understanding of these risks, including those that are unique to individual businesses or
specific parts of the organization. Those risks include:
- Sensitive data: the potential misuse or mishandling of sensitive data, including personally identifiable information (e.g., to fine tune
large language models, or LLMs) can lead to breaches of privacy, a risk intensified by the vast amounts of data AI systems process. - Transparency issues: the black-box nature of some AI models makes it difficult to explain or understand their decision-making
processes, raising concerns about accountability. - Biased and false outcomes: AI models, when trained on biased data, can spread or even worsen existing prejudices, leading
to unfair policy terms and pricing or claims denials; hallucinations, where AI applications present false information or fabricate
outputs from LLMs, are another concern. - Balanced human-AI collaboration: knowing when to apply human judgment versus following AI-generated recommendations
can be challenging. - Privacy concerns: continuous monitoring (e.g., through telematics and wearable devices) may be seen as invasive by consumers
worried about constant surveillance. - Reliability and replicability: if not properly maintained or updated as conditions change, AI systems could produce inaccurate
or outdated results that affect policy decisions and claim outcomes. Further, outcomes may begin to vary as inputs and LLMs
change and the use of AI tools within workflows is adjusted. - Cyber: adversarial prompt engineering, manipulation of inputs and other attacks can lead to unintended fraudulent activities and the loss of training data or even a trained LLM model. Because LLMs are built on third-party data streams, insurers may be affected by external data breaches.
Legal liabilities and regulatory exposures are also significant, from potential copyright and IP infringement, to data-use infractions, to compliance with the General Data Protection Regulation and other rules. Widespread uncertainty about what is allowed and what companies will be required to report is a major concern. See next page for more on the regulatory outlook for AI. Overall, the lack of insight into how AI systems use data and make decisions can erode confidence among customers, especially if outputs are not as expected or override human judgment. To a large degree, future consumer confidence will depend on the ethical deployment of AI and delivery of unbiased results, a challenge that will be faced by many firms, not just insurers.
Insurance Europe (IE), the federation of European insurers and reinsurers, has clear visibility into both thestate of AI adoption and the prospects for regulation. AI uptake still varies across the EU, with some insurers leading the charge and others in the early stages. But interest is high, given AI’s potential to “enhance insurers’ role as risk-absorbers in society,” according to Michaela Koller, IE’s Director General. “By helping to reduce the frequency and severity of losses over time, AI can benefit both individual policyholders and society as whole.”Those benefits include more accurate pricing, tailored protection, faster claims processing and round-the-clock customer support (through the use of AI-powered chatbots and virtual assistants).
But AI can also open up new avenues for innovative products and services. The likelihood of widespread adoption has attracted the attention of government and regulators, which perceive a need to write new rules for the use of new technologies, as the pending AI Act demonstrates. “Ideally, new regulations will blend smoothly with existing laws, like the General Data Protection Regulation, and sector-specific conduct rules,” said Koller.
“Balancing the risks and benefits of new technology within a comprehensive impact assessment, the best regulation promotes effective risk management controls, as well as product governance and transparency.” Koller notes that insurers have natural incentives to protect the vast amount of sensitive personal data customers entrust to them. “Ensuring fairness and protecting the privacy of consumer data are not only legal and regulatory matters, but also fundamental components of consumer trust,” she added. “By prioritizing privacy and fairness, insurers can not only comply with regulatory requirements but also show their commitment to delivering fair and trustworthy services to all.”
With a hard market continuing in commercial insurance, captives have become a fixture on the industry landscape. Up until a few years ago, captives were rightly considered to be part of an alternative risk transfer market. That is no longer the case. Nearly every Fortune 500 firm owns and operates its own captive insurer. Captives now represent nearly 25% of the overall commercial
insurance market, having diverted hundreds of billions of dollars in premiums from traditional channels in the last decade. The European captive market is also growing, thanks to a friendly legislative and regulatory environment in multiple jurisdictions.
Captives have grown because companies weren’t finding what they wanted on the open market. They came to believe they could devise more effective risk solutions in more direct alignment with their needs than could traditional carriers. Their outperformance on key metrics confirms they were right. Superior combined ratios have not only led to remarkable growth in captives’ retained earnings and surplus, but also translated into billions of dollars in savings for captive owners.
As a result, more companies are more comfortable putting more risk on their balance sheets and keeping it there. Super captives are now capable of assuming huge amounts of risk, for example by covering their own supplier networks. They’ve matured their use of reinsurance to reduce portfolio risks and volatility. And they’re well positioned to build out ecosystem platforms and unique forms of embedded insurance.
Too often in the past, insurers have focused ESG and other societal value programs on the realms of corporate social responsibility units or regulatory teams. Societal value objectives should be
factored into insurers’ overall growth strategies. Attractive products and a brand that resonates with customers are also key. Indeed, insurers would be well served by considering entire communities as actual customers, rather than as just important constituencies. The strongest brands in the future will be built around specific practices (e.g., transparent reporting, progressive sourcing) that are verified by third parties.
Senior leaders will need a crisp and persuasive narrative regarding the relationship between profitability targets and social impact. Capital markets will want to know that the two are not in conflict. New reporting standards may help in this regard: the CSRD’s double materiality” concept requires companies to specify how sustainability issues can create financial risks (financial materiality) and the company’s own impacts on people and the environment .
Ultimately, embracing societal value as a worthy goal also requires making purposeful strategic choices about what type of business an insurer wants to be. Many organizations in many sectors like to view themselves as technology companies. But that doesn’t mean every firm should aim to replicate the valuation patterns and growth trajectories of the biggest tech companies.
Stable, predictable, consistent returns, like those typically produced by utilities, are a financial aspiration better aligned to the nature of the insurance business, as well as its traditional purpose and brand positioning (i.e., Uas reliable partners in times of need). The ability to produce significant
benefits for all parts of society should be a pillar of the industry’s value
proposition — for customers, investors and regulators alike.