This course takes an Agile sprint approach where teams from participating NCAs encompassing different areas of competence come together to work on specific issues and technical solutions (e.g., IT, Business/Law Unit and SupTech division, in line with the NCAs organisational structure). Participants work intensively in cross-functional teams to create innovative solutions, often focusing on problem-solving and/or prototyping.
Before the prototype phase, the course will cover advanced theoretical lectures and presentations on use cases in other SupTech projects. The goal is to encourage creativity, teamwork, and the development of functional prototypes, with opportunities for learning, networking and celebrating failures and successes.
This training week is specifically designed for participants actively designing SupTech application proofof-concepts or possessing robust coding experience. The program aims to advance both the theoretical understanding and practical skills of participants in SupTech.
NLP for greenwashing deception
Macro forecasting
DTL/Crypto-assets supervision
GenAI chatbot
Tool for AML/CFT supervision
Data visualisation and dashboard
Social media sentiments analysis with NLP
Monitoring publicly available information (news, discussion platforms, social media, etc)
Digital twin
Graph analysis tool for systemic propagation of IT and cyber risk
Synthetic data tool
Agent-based modelling for suptech
Tools for AI for insider‑trading coalition activity and behavioural‑anomaly detection
Applying advanced AI and ML techniques in Python
Recognizing the organisational impact of SupTech applications
Identifying the resources to take the SupTech applications into the production phase
Developing a SupTech application proof of concept
Essential: General exposure to SupTech.
Essential: Advanced experience in coding (preferably Python or R) and/or close involvement in the development of a SupTech project.
Recommended: Prior exposure to the design of SupTech application proof-of-concepts.
Recommended: Prior exposure to NLP, tree models and cluster analysis.
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