Algorithmic analysis of regulatory dependency graphs

We are offering a research opportunity that may interest students and doctoral candidates engaged in mathematics, finance, statistics, or financial law. Our LegTree system, part of the Regulatory Intelligence Service Portal (RISP), systematically tracks regulatory developments and connections worldwide. RISP continuously monitors and analyzes financial regulations through automated processes, while our experts provide structured assessments. Our systematic screening ensures timely detection of publications from supervisory authorities, industry representatives, and interest groups, allowing us to identify emerging regulatory trends early.

However, the numerous regulatory elements within LegTree are interconnected through complex dependency structures (Regulatory Dependency Graph). These dependencies vary in type and direction, which must be accounted for in a graph-theoretical representation.

Our solution is graph-theoretical modeling. We aim to develop approaches to systematically capture these connections using directed graphs, node invariants, and algorithmic analysis methods. Specifically, we seek to classify and analyze different types of regulatory dependencies, such as:

• Succeeding (subsequent regulations building on previous ones)
• Cited by (referenced in later regulatory texts)
• Affected by (modified or constrained by another regulation)
• Modified by (explicitly changed by a later amendment)
• Supported by (reinforced by related legal frameworks)
• Supposed by (assumed as a basis for interpretation)
• Specified by (further detailed in complementary guidelines)
• Related to (generally connected in thematic scope)
• Implemented by (translated into concrete enforcement mechanisms)

We are looking for researchers interested in exploring this topic as part of a thesis or a research internship. Anyone working with network analysis, graph algorithms, adjacent matrices or visualization techniques will find an opportunity here to apply theoretical concepts to a real-world challenge in financial regulation.