Network Analytics Big Data & Machine Learning in RegTech & SupTech

Central Banking Publications

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Central Banking and Kimmo Soramäki have designed this two-day training course to provide practitioners with the latest developments and good practice methods to utilise network theory and analytics to:
<ul><li>Improving fraud detection and AML with network theory
</li><li>Analyse and real time monitoring of risk exposures
</li><li>Application of stress testing correlation networks
</li><li>Using network simulations to model FMIs
</li></ul>The first day of the course covers the building blocks and essential elements used in the analysis: scenario generation and monitoring of risk exposure networks; visualisation of dynamics of market correlations; development of advanced stress testing procedures.
The second pivots towards the practical with sessions detailing applications of techniques in payment analytics through network theory and agent-based modelling; design and oversight of financial market infrastructures; detection and investigation of financial and cyber-crime.
Throughout the course, each session features interactive hand-on exercises that will enable delegates to apply their newly acquired skills to real-life market scenarios, and conduct analysis' of data via digital dashboards provided by the tutor.

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Network Analytics Big Data & Machine Learning in RegTech & SupTech

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