ForensicCloud provides real-time (big) data analysis of networks, transactions and risk signals. Multiple detection mechanisms can be combined. The results are presented in an easily accessible manner and within an understandable context. As a consequence, companies and institutions can detect these risks early and take immediate actions, which are aimed at limiting possible damages as much as possible and optimizing possible recovery options.
ForensicCloud consist of five different modules to prevent financial crime:
A Know Your Customer (KYC/CDD) module where you collect, verify, and validate all information about your clients to easily generate and assign a risk rating.
An AML/CFT & Sanctions Surveillance module consisting of transaction surveillance and payments monitoring covering all the regulatory monitoring requirements in force under the relevant laws or regulations for AML, CFT, and Sanctions.
A Fraud & Integrity Risk Surveillance module which covers event monitoring, with the more diffuse scope of identifying fraud & integrity risk scenario’s or ‘methods of operation’.
A Special Investigations module that supports extended due diligence processes, strong visualizations, integration of data sources and case management. Enabling you to follow-up and investigate on any alert, irregularity or risk, either through a straight forward work flow or as a more flexible, data driven investigation.
A Client Risk Intelligence module which combines all four modules and aggregates all identified risks to calculate a single integrity risk score per client by means of a sophisticated scoring model.
Since the foundation in 2010 BusinessForensics has been proving itself as an innovative Fintech/RegTech solutions provider in regulatory compliance and integrity risk management. The BusinessForensics name comes from the initial ambition to help banks and insurance companies to better protect themselves against economic and financial crime risks, by providing them with inventive forensic solutions and helping them make better sense of their data.
