InsurTech4Good.com Weekly Newsletter – #27, 2025

I don’t know about you, but I’m rested, full of energy and ready for autumn! But what should we expect from the EU side? Which key areas should insurers, InsurTechs and FinTechs be following from a regulatory perspective?

First, of course, the Financial Data Access (FIDA) discussions. The negotiations continued last week under the Danish Presidency. There is still a lot of work to do, but some preliminary agreements have been reached, and it will definitely be an interesting autumn.

What else? While perhaps less obvious, I would personally also recommend keeping an eye on the Digital Fairness Act. The European Commission’s 2024 fitness check on digital fairness identified gaps in consumer protection online.

The next step is most probably the development of a Digital Fairness Act (although consultation is still on-going). Building on the existing EU digital rulebook, this initiative aims to address problematic practices such as:

1. Unfair commercial practices related to dark patterns

2. Misleading marketing by influencers

3. Addictive design of digital products

4. Unfair personalisation practices

It also seeks to ensure a level playing field for online traders, strengthen enforcement, and introduce possible simplifications.

It’s still early days, but given the recent push to make the Consumer Rights Directive more applicable to financial services and the potential relevance of issues like influencer marketing, addictive design, and dark patterns (which are very much an issue in insurance too) this initiative could have significant implications for the insurance and financial sector overall.

And as the EU consumer agenda is sector-agnostic, this is one I will personally be focusing on this autumn, including in my blog and newsletter. 

I would also keep an eye on the Savings and Investment Union discussions. Whether on pensions including pension dashboards and the PEPP review (EIOPA by the way just published its technical input and I will reflect on that in coming days) or consumer financial literacy, there is plenty of room for innovation and business opportunities.

Of course, there is more: governance around AI (see article below from the BIS on AI explainability and recent work from EIOPA and the IAIS), the application of existing regulations such as DORA and the Data Act, and the evolving political agenda. 

We’ll also get a clearer picture on 10 September after the State of the Union (SOTEU) address. For those less familiar, SOTEU is an annual speech by the President of the European Commission to the European Parliament, setting out the priorities for the year ahead. 

It is a key moment in the EU’s democratic process, an opportunity to:

1. Reflect on the past year

2. Outline the EU’s priorities

3. Announce new initiatives

I will of course keep you updated on all these developments in my newsletter. And if you want a real deep dive on these topics, I also run tailored workshops, trainings and webinars for organisations and teams. Let’s talk!

Now to the news! 

Artificial Intelligence in Estonia

Curious about the Estonian AI ecosystem, including its links to financial services, insurance, and innovation facilitation?

Have a look at this just-published report, which I had the pleasure of co-authoring with esteemed colleagues.

Estonia fosters AI innovation through a vibrant start-up scene and strong research partnerships, with government support accelerating adoption across both the public and private sectors.

This includes sandboxes to trial AI in public services, testbeds for companies to experiment with new technologies beyond current regulation, and targeted grants and programmes that help businesses adopt AI, boost competitiveness, and secure long-term economic growth.

Drawing on my experience shaping digital finance policy and regulation at both European and global levels, I see Estonia as uniquely positioned to lead.

With its e-state infrastructure, agile regulation, and commitment to trust and human-centricity, Estonia provides an enabling environment to test, start, and scale AI-powered financial and insurance solutions.

Notably, the financial and insurance sectors are already among the most active adopters of AI technologies in Estonia. This is a clear signal that innovation here is both real and responsible.

Keen to learn more about e-Estonia, or thinking about starting your AI-related financial or insurance business here but need help navigating the landscape? Let’s talk.

Read more here. 

Open Finance and protection Gap 

1.3 billion people worldwide still lack access to formal financial services. Open finance offers a promising approach to closing these gaps by enabling individuals and businesses to securely share their financial data with third-party providers of their choice, while fostering more competitive and inclusive financial markets.

CGAP’s research identifies six critical policy levers that determine whether open finance becomes a true driver of inclusive and competitive markets: clear objectives, reciprocity, inclusive participation, proportional regulation, pricing, and governance.

Done right, open finance can give consumers more choice, control, and value, while fostering financial ecosystems that are competitive, inclusive, and resilient.

One could argue that the situation in the European Union is better. We don’t face the basic bank account problem as such. However, challenges clearly remain around competition and financial inclusion. 

I would also add the insurance and pensions protection gaps, which are areas where a well-designed open finance and open insurance framework could make a difference.

So, my FiDA friends – on both sides and in between – let’s keep this in mind as summer draws to a close and discussions on our own Financial Data Access (FiDA) proposal resume at the political level.

Read more here. 

What have we learned from open banking?

This article by Bill Roberts, whom I greatly respect, considers what regulators can learn from the experience of open banking implementations to date, in particular the relative merits of market-driven versus regulator-led approaches.

It concludes that if the regulator’s policy objective is to address a competition problem, then a market-led approach is unlikely to succeed, since the market is, by definition, not well-functioning.

The same principle, do not rely on market forces to deliver the desired results if the market itself is not well-functioning, also applies when setting rules on charging third-party providers (TPPs) for access to data held by banks, and when considering which approaches are appropriate at different stages of implementation.

And I think again, we should keep this in mind in our own discussions on the Financial Data Access (FiDA) regulation here in Europe.

P.S. If you agree that autumn is a good time to deepen your understanding of open insurance and the EU’s FiDA regulation, whether as a company or on an individual basis, let me know, and let’s see what we can do!

Read more here. 

Agentic AI in insurance and finance

Banking, Financial Services and Insurance (BFSI) institutions have significantly increased their spending on innovation, but ROI still lags.

Tenity’s recent report argues that the next wave of competitive advantage will come from execution at scale, driven by agentic AI.

The next wave of competitive advantage won’t come from experimentation. It will come from real-world impact at scale.

At the heart of this shift is the rise of agentic AI: systems that move beyond assistive support to autonomously execute workflows, adapt to context and deliver outcomes with minimal human intervention.

Read more here. 

AI in insurance - it’s time to scale

Insurance leads in AI adoption. Now it’s time to scale.

The insurance industry has outpaced many other sectors in its early embrace of artificial intelligence. Something that may surprise those who do not usually consider insurance among the most innovative industries.

However, few insurers have succeeded in delivering value at scale. Many AI programs, whether predictive or generative, have stalled due to organizational and individual resistance.

Key challenges include limited business engagement, unclear roles and responsibilities, inconsistent leadership support, and the probabilistic nature of AI, which often clashes with the risk-averse culture of the industry.

The insurers that succeed at scale are those that think big, execute effectively day to day, foster a culture of change and accountability, and focus on the few areas that generate the greatest enterprise-wide value.

This article outlines how insurance organizations can overcome these hurdles and unlock the unique opportunities of scaling AI in this sector.

Read more here. 

How insurance and financial services regulators can address AI explainability?

The limited explainability of complex AI models (especially deep learning and LLMs) poses challenges for financial institutions and regulators. 

Explainability is vital for transparency, accountability, compliance and consumer trust, yet current techniques remain imperfect, often inaccurate or unstable.

Most existing model risk management (MRM) guidance is high-level and not designed with advanced AI in mind. 

Provisions on governance, documentation, validation and monitoring implicitly touch on explainability, but complex models often struggle to meet these requirements. The use of third-party AI models adds further complexity.

As AI adoption expands into critical business areas, regulators will need to adapt MRM practices, balancing explainability with performance. 

As the authors state, allowing the use of complex AI models with limited explainability but superior performance could enable financial institutions to better manage risks and enhance client experiences, provided that adequate safeguards are introduced.

They further clarify that, for regulatory capital use cases, complex AI models may be restricted to certain risk categories and exposures or be subject to output floors. 

Regulators must also invest in upskilling staff to evaluate AI models effectively, ensuring that financial institutions can harness AI’s potential without compromising regulatory objectives.

Read more here. 

Hope you enjoyed the read!

Andres

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