Applying advanced data science techniques to analyse and model data
Financial crime is an ever-changing and illusive enemy. There is a lot known about money laundering and other types of financial fraud, but also a lot unknown. RiskQuest has experience in developing models to tackle both the known and unknown aspects of financial crime.
To create value from data requires the use of mathematical models. RiskQuest has substantial experience in developing and validating all kinds of models, ranging from simple spreadsheet calculations to deep learning algorithms.
Unsupervised models for Anti-Money Laundering
Development of unsupervised models to detect money laundering
Applying clustering techniques to global retailor
Applying unsupervised clustering techniques to rationalise products across the globe
Development of a Healthcare Fraud Detection at a bank
Development of a supervised machine learning model to identify healthcare fraud