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Regulations & models

The creation of each Compact edition generally starts with a broad theme that is currently relevant in Business and/or IT, such as our previous edition around IT hypes & trends. For this (and spoiler, the next) edition, we decided to try an open invitation call for papers. Authors overwhelmed the Compact editors with articles addressing a range of various topics from different areas of expertise.

As we started editing the articles, a broader theme emerged, so in this edition of Compact Magazine, we present a selection of articles that cover regulations and models. In the first article on Control by Design, where risk-free processes are the holy grail, we showcase a case study in the financial sector to demonstrate the application of Control by Design in practice. In the second article, “DORA: an impact assessment”, we dive into the Digital Operational Resilience Act (DORA), regulation created by the European Commission to unify digital operational resilience in the European financial sector. And in the third article,”The Digital Actuary”, we discuss digitization in the core of an insurance company by providing a model and example for an integrated insurance platform.

A topic that was featured in the 2022/1 edition and that will likely require its specific Compact edition again, is ESG. “Measuring circularity: how to gain insights with Circular Transition Indicators” dives into the challenges and opportunities new regulatory and reporting requirements put forward. This article predominantly discusses how to measure circularity by application of Circular Transition Indicators (CTI).

Next up, we have two articles that dive into the use of algorithms. The first, “Thorough model validation helps to achieve or safeguard public trust”, discusses the risks and undesirable consequences that can be associated with the use of algorithms and how to independently validate these risks. The other article, “Operationalization of Machine Learning models in (audit) innovation projects”, describes the current state and difficulties of Machine Learning (ML) in the context of financial audits.

This edition concludes with a review of the book Everyday Chaos by David Weinberger, in which he describes the evolution of prediction and how to manage uncertainty.

We wish you an enjoyable read. In case you like to further discuss any of the thoughts and visions shared in the various articles, do not hesitate to contact us at