Zabit offers a money laundering prevention platform that employs real-time transaction monitoring and compliance analytics to ensure regulatory adherence for financial institutions. By enabling compliance teams to efficiently identify suspicious activities, the platform mitigates the risk of financial penalties and reputational harm.
Funding
Funding not disclosed
Founders
Product
Problem
Financial institutions face increasing challenges in detecting and preventing money laundering activities, requiring them to adhere to complex and evolving regulatory requirements from bodies like BACEN, CVM, and SUSEP. Traditional methods often struggle to efficiently identify suspicious transactions and manage the associated risks, leading to potential financial penalties and reputational damage.
Solution
Zabit PLD offers a comprehensive anti-money laundering (AML) platform that enables financial institutions to streamline compliance processes and mitigate the risk of financial crime. The platform provides real-time transaction monitoring, risk-based client classification, and integrated screening against international watchlists such as OFAC and ONU. By leveraging machine learning and parallel processing, Zabit significantly reduces screening times and enhances the accuracy of anomaly detection. The system facilitates efficient case management, dossier maintenance, and communication with COAF (Council for Financial Activities Control), ensuring adherence to regulatory standards and promoting a secure financial environment.
Target Audience
Zabit PLD primarily targets financial institutions, fintech companies, and other regulated entities in Brazil that are required to comply with AML regulations and report to COAF.
Features
- Real-time transaction monitoring to detect anomalous patterns and behaviors
- Risk-based client classification aligned with risk analysis approaches
- Screening against international lists, including OFAC and ONU
- Dossier management for maintaining records of analyses, processes, and approvals
- Automated report generation for suspicious activity to COAF
- Integration with cloud environments
- Adaptable workflow to align with existing processes
- Machine learning-driven analysis to reduce screening times