Regulatory reporting: From compliance to value

Caroline Béguin: Regulatory reporting has expanded massively in scope and complexity. From your perspective, what is the biggest structural shift financial institutions need to understand as we enter 2026?

Sébastien Polèse: There are several important trends, but if I had to highlight one for 2026, it would be the pressure around time to comply. Institutions are expected to deliver reports faster than ever while maintaining high levels of quality. On top of traditional reporting requirements from the EBA, the ECB, and national central banks, regulators are increasingly introducing ad hoc requests. Banks may now be asked to provide specific information within days or even hours. To answer these requests efficiently, they need access to accurate, structured, and high-quality data at all times.

Caroline Béguin: Banks are expected to handle unprecedented data volumes and faster turnaround cycles. How should they rethink their data foundations to stay ahead?

Sébastien Polèse: Data is at the heart of regulatory reporting. Without data, there is nothing.

Historically, data has been managed in silos. Different reports required similar information, but structured in different ways. According to a study by the Banque de France, the same data is reported on average eleven times, often with different formats and requirements. The challenge for banks is to break down these silos and build a common data layer that reflects the activity of the institution. Once that foundation is in place, banks can better manage data quality and address the challenge of time to comply.

Caroline Béguin: Cloud, automation, and AI have finally reached maturity. How will they transform regulatory reporting by 2030?

Sébastien Polèse: The biggest shift is a change in mindset. Regulatory reporting will move from being reactive to becoming proactive. Until now, institutions have simply responded to requests. In the future, technology will enable them to anticipate changes and rely on a common data layer to make better decisions. Cloud technologies provide the flexibility and processing power needed to handle growing volumes of information. AI will also play a key role by helping institutions interpret data, learn from previous reports, and suggest ways to optimize reporting processes.

Caroline Béguin: There is a growing idea that regulatory data can become a competitive asset. How can institutions move from reporting to comply to reporting to gain insights?

Sébastien Polèse: Once you have built a common data layer and fully mastered your data, you are sitting on a gold mine. You have access to qualified, regulator-approved information covering all aspects of your activity. This gives you a complete view of your clients and your business. From there, regulatory data becomes much more than a compliance requirement. It becomes a tool for strategic decision-making. For example, if a bank wants to focus on green assets or specific customer segments, it can rely on trusted data to make informed choices. In that sense, regulatory reporting can become a real accelerator for business growth.

Caroline Béguin: If you imagine the regulatory reporting function in 2030, what does a best-in-class solution look like, and what should banks start doing now to get there?

Sébastien Polèse: The best-in-class solution will undoubtedly be a SaaS-based technology platform. Regulatory reporting is a perfect candidate for SaaS because institutions do not need maximum processing power all the time. Elastic cloud capabilities allow them to scale resources when necessary and optimize costs. This is becoming increasingly important as reporting moves toward more granular data and larger volumes. With the right technology foundation, institutions can also move toward real-time reporting. Real-time capabilities make it possible to model scenarios, run stress tests, and support business ambitions more effectively. And of course, AI will play a central role. AI depends on data, and regulatory reporting contains some of the richest and most valuable datasets within a bank. AI will help institutions better understand their models, become more proactive, and identify new opportunities to improve their business.

Caroline Béguin: Thank you for these insights. They will certainly be useful. And thank you for making such a complex topic crystal clear.

Sébastien Polèse: Thank you very much. And thank you again for the opportunity.