Article

Adapting to the new data requirements

The upcoming Basel IV changes have sent many organizations scrabbling as they prepare to address the vast implementation challenges on the horizon.
In this article, Regnology’s Product Director Anh Chu shares her perspectives on different areas of challenges introduced by Basel IV and best practices for a smooth transition to the new regulatory framework.

Topics include: 

  • From a risk and data perspective, what are the major changes introduced by Basel IV that Banks are having the most challenging time implementing?   
  • For global organizations, what are the main challenges due to the added complexity when operating across jurisdictions? 
  • Given the increased data and reporting requirements of Basel IV, how might technology play a role in compliance and reporting for banks?  
  • What could be the use cases of AI that could aid banks in adapting to the changes introduced by Basel IV? 
  • Looking beyond Basel IV, what trends might emerge or have emerged that financial institutions should consider when implementing and upgrading their system for the current iteration of Basel IV? 

Download the article

Author

Anh Chu

Anh Chu

Product Director Regnology

You might also be interested in

  • DPM 2.1: Building the foundation for integrated statistical and supervisory reporting

    Insight

    DPM 2.1: Building the foundation for integrated statistical and supervisory reporting

    The Data Point Model (DPM) 2.1 is creating a unified supervisory data ecosystem in the EU by establishing a machine-readable and legally traceable metadata environment. This evolution is designed to improve data consistency, enhance traceability, and unlock powerful AI use cases for automated impact analysis and regulatory change management. The consultation is open till 30 September 2026.

    Read more
  • Transforming modern supervision

    Insight

    Transforming modern supervision

    Financial supervisory authorities are increasingly leveraging cloud-native infrastructure, granular data, and AI-enhanced oversight to transition toward a more data-driven, and forward-looking approach to supervision.

    Read more
  • From Risk to Regulatory Distribution: Building an Integrated Value Chain

    Insight

    From Risk to Regulatory Distribution: Building an Integrated Value Chain

    As regulatory pressures grow, risk, finance, and reporting must evolve from fragmented data silos to an intelligent, integrated value chain. Our new whitepaper with Chartis outlines the path to building a more efficient & resilient regulatory operating model.

    Read more

Contact us