9 Hypotheses on the future of insurance advice

With 2025 already in full swing, we embrace the arrival of Generation Beta but also see changes in the insurance industry landscape profoundly shaped by more uncertainty¹, evolving risks², and high asset volatility³.  

The evolving risk landscape is reshaping both the demand for and supply of insurances. In this article, we provide an overview of the key drivers of change and their implications for the insurance industry. At its core, the article explores nine bold hypotheses about the future of the advisory and sales process. These nine hypotheses are intended to create room for discussion and innovative thinking.

• Geopolitical instability & economic challenges: Heightened political conflicts, transformative political changes, and a growing sense of uncertainty among the public on the one hand. And on the other, sluggish economic growth or even recession in some countries, high asset volatility, and increasing public deficits. These developments lead to increasing consumer anxiety, and a growing desire for safety, higher saving rates coupled with tighter household budgets.
  
  
• Technological advancements: Continued breakthroughs in AI and life science will impact the whole industry, from process efficiency, risk assessment, advice services to claim cost & settlement. APIs, connecting distributors, but also suppliers, for example risk data services, are becoming even more critical and are shaping a growing financial ecosystem. Advanced algorithms and increased data availability lead to deeper customer insights, based on strong CRM systems.  Combined with political conflicts the rapid technological progress continues to amplify cybersecurity risks. We will see a shift in operational costs from labor to technology, but also efficiency gains.
  
  
• Climate change: Climate change will have the strongest impact in the medium to long term, with more floodwater events, prolonged droughts, and devastating wildfires. This not only results in rising insurance costs and uninsurability but also further growing protection gaps.
  
  
• Regulatory developments: Dora, review of Solvency, FIDA, AI-Act, more ESG, accessibility and maybe even an EU-wide climate catastrophe insurance scheme? Regulatory updates will keep the insurers and their suppliers busy. Most of the regulations will lead to additional operational costs.
  
  
• Demographic shifts: An aging population, shaped by retiring baby boomers and reduced immigration, paired with younger generations who prioritize different life goals and demonstrate different online shopping preferences.
  
  
• Increased competition: Saturated markets and lower economic growth/limited household budgets offset the growing desire for safety. Private capital consolidated brokers and multi-agents demand a larger share of the market profit. We see competition from neo-brokers in the life insurance segments and underwriting agencies/MGAs in the non-life markets. Additionally, the FIDA regulation will increase the market dynamic. These developments will increase competition keep pressure on efficiency and innovation high.

1. Increasing holistic financial advice: Holistic financial advice defined as covering banking, asset management and insurance products, is driven by consumer expectations, technological advancements (APIs, algorithms) and regulations (FIDA).
   We will see more comprehensive advisory services that generate personal balance sheets, household budgets and existing policies. This leads to greater transparency regarding the consumers’ financial situation. The advantages for consumers (convenience, overview) and the provider (stickiness and x-selling) are obvious. Even if some insurance companies still struggle to advise their consumers holistically across their product portfolio, we cannot imagine advisors selling only a few types of products in the retail market soon.
   
   
2. Increased product transparency and enhanced comparisons: AI is set to unlock the potential of analyzing and efficiently comparing third-party policies that are currently only available in PDF format. This will pave the way for tailored optimization recommendations at marginal cost, unlocking new opportunities and transforming dynamics for brokers and agents. It will also drive greater transparency and intensify competition within the market. An interesting question we are currently examining is whether product comparison (new to old, but also within the market) will evolve into a standard feature of the insurance sales process and how it could redefine agents' service offerings in comparison to brokers.
   
   
3. AI-powered customer insights, advice and guidance: LLM models, advanced algorithms and increased data availability allow deeper customer insights across all channels. AI-based agents will not only thrive in and around the CRM ecosystem but also directly on mobile phones supporting the end customer and the advisors in real-time. Imagine Google’s Gemini coordinating not only your next restaurant visit but also orchestrating your finances across various financial apps. Basic advice will be available at marginal costs. This also supports risk warnings and prevention as a service and enhances the acceptance of on-demand products.
   
   
4. Advancement of hybrid and self-service models: An increasing portion of the sales process will be digitized and shifted directly to customers. Tasks such as risk assessments and annual checkups will be modernized and fully digitized for self-service. Technology will enable a smaller number of advisors to efficiently serve a larger customer base.
   
   
5. Personal advice will remain essential in the foreseeable future: While self-service options and hybrid advisory models are on the rise, advisors can remain confident about their job security. Factors such as consumer preferences (the long-standing principle that “insurance is sold, not bought”), the high level of complexity of many insurance products compared to banking products, and the ongoing shortage of skilled professionals will ensure a sustained need for advisors. For change to occur, breakthroughs in digital, personalized customer engagement are necessary (e.g. personalized outbound campaigns, apps).
   
   
6. Increased advisory quality: With the leveraging of more customer data (e.g. FIDA, see above) and advanced algorithms, insurers can offer advice on basic products and coverage recommendations at no additional cost. Bots for advisors and consumers to answer contract-related questions regarding coverage will be the new normal.
   
   
7. Increased product standardization: Given the high level of complexity in products with numerous configuration options (such as coverages and sub-limits), even in retail offerings, there is a clear move toward greater standardization. This approach aims to streamline processes, lower IT costs, and fully harness the potential of AI-driven capabilities.
   
   
8. Protection gaps and evolving role as risk managers: As certain risks (e.g., natural catastrophes) become increasingly expensive or even uninsurable, insurers and advisors have an opportunity to shift towards acting as risk managers for individuals, providing mitigation strategies as part of their services. Rising prices and questions around insurability will also affect property/home values and influence consumer purchasing behavior. While we do not foresee the implementation of a European catastrophe scheme (such as mandatory insurance) in the near future, we do anticipate more restrictive regulations for building new homes in high-risk areas. Addressing these uninsurabilities with existing customers will pose a significant challenge for insurers, potentially leading to unexpected and negative outcomes for many consumers.
   
   
9. Shift from initial commissions to service/advice-based commissions and “fee schemes”: The industry is moving towards ongoing commissions and transparent fee structures, particularly in life insurance, driven by evolving customer expectations and regulatory requirements. These commissions will increasingly reflect the value of continuous support and advice services. Challenges, such as presenting real portfolio values to customers through apps post-purchase without requiring extensive explanations, are likely to be resolved. While the long-term benefits of fee-based models, especially for independent distributors, are still not widely embraced within the industry, increased transparency will improve the competitiveness of life insurance products compared to asset management alternatives. As holistic financial advice becomes more common, a unified compensation model across banks, asset management firms, financial distributors, and insurance companies will be necessary. Insurers are expected to align their practices more closely with those used by banks and asset managers.

In a nutshell: AI will play a critical role in enhancing product comparisons, delivering personalized, real-time advice, and enabling hybrid/self-service models, allowing advisors to focus on complex cases while maintaining their relevance in an evolving market. Additionally, shifts toward standardized products, service-based commissions, and the role of insurers as risk managers addressing uninsurable risks will create a more transparent, efficient, and customer-focused insurance landscape.

I look forward to engaging in discussions and hearing diverse perspectives on the article. I also hope it inspires more innovative thinking within the industry. Feel free to reach out if you'd like to dive deeper into any of the topics mentioned.

Ralf Widtmann 

Special thanks to Nikolai Dördrechter, Wolfgang Petschko, Christian Voith, Xaver Wölfl, and Jochen Zöschg for generously sharing your insights. Any errors remain my own.

---

^{1 In this article, “uncertainty” refers to situations where risks cannot be precisely calculated.
2 While some risks, such as accidents are decreasing, natural catastrophes are increasing in frequency and intensity. For example, flood events demand significant upward adjustments in probability models. Other risks like drought-driven wildfires or cyber threats lack sufficient data, making cumulative events particularly challenging to assess. 
3 Volatility in the sense of “swing “}