Why is simulating financial crime so valuable?
What are financial crime simulations?
Financial crime simulations are complex and dynamic models of criminal techniques, known as typologies. These include money laundering and fraud behaviours. Simulations of financial crime can be labelled within datasets for effective detection.
How are financial crime simulations created?
Financial crime techniques are complicated and evolving at a rate which makes them increasingly difficult to model using traditional methods. Simulation techniques such as Agent Based Modelling allows for complex financial crime behaviours involving sophisticated entity interactions to be modelled dynamically. Financial crime simulations can be based on real financial crime techniques and customised test scenarios.
Use financial crime simulations to fight against:
-
Known financial crime techniques
Simulate custom financial crime techniques to help tune your control systems. Calibrate your control systems to correctly alert against financial crime techniques that your organisation is aware of.
-
Unknown financial crime techniques
Access our library of financial crime typologies to calibrate your systems against techniques your organisation may be unaware of. Be prepared against unknown techniques before you are exposed to them through real criminal activity. Keep up to date as our library grows and is updated.
-
Financial crime techniques of the future
Use simulations to create forward looking financial crime scenarios to be one step ahead of criminals. Test your systems for potential weaknesses before criminals do. Protect yourself against future financial crime techniques before they become a reality.
Financial Crime Simulations to improve financial crime controls
Labelled financial crime typologies can be used to test, measure and improve financial crime control systems, such as transaction monitoring systems. Reduce false positive alerts and tune your control systems. Demonstrate financial crime control performance and strength.
Financial Crime Simulations to improve AI
Simulation allows for the effective labelling of financial crime. Creating superior data for AI training that greatly surpasses the potential of real data. This increases the utility and performance of machine learning in financial crime detection and prevention