Why is a combined view of risk and fraud aspects paramount?
Risks, such as payment default, can be assessed at best by verifying the identity and checking existing payment histories.
Conversely, fraudsters usually misuse good and inconspicuous identities to avoid classic risk assessments. Therefore, looking at purely physical data such as address, name or date of birth cannot effectively and sufficiently prevent fraud.
CRIF looks far beyond the physical data of a person and includes digital information such as usage data, movement data, and behavioural data in the analysis.
HYBRIGHT offers you a combined and comprehensive view of risk and fraud aspects to both minimise classic risks and prevent fraud at an early stage.

Simply unique: The Decision Engine is the heart of HYBRIGHT and combines machine learning algorithms with rule-based processes in a hybrid approach. It ensures custom, real time decisions while retaining full control over your key figures, helping you tweak the process at any time to meet your needs.
Within only milliseconds, the engine analyses highly complex regulations, taking into account all available data. Positive and negative information from millions of transactions flow into the risk and fraud pattern detection. With intelligent decision logic, you can apply various risk and fraud tools using customer-specific rules.

Our innovative and individually adaptable dashboard prepares your most important key figures in real time and offers the best possible management options using facts. Monitoring transactions and fine-tuning individual rules are simple and intuitive. The transparent presentation of fraudulent transactions allows for the quick and cost-effective processing of clarification cases. From the automatic checking of blacklists to smart filter options and integrated Google Maps search, to the straightforward integration of your customer data, our cockpit offers a comprehensive overview and holistic control.