Rules-based suspicious activity identification
The regulatory landscape is becoming increasingly complex. To effectively combat financial crime without incurring increasing costs, financial institutions must implement systems that can integrate new types and sources of data to support internal and external-facing business processes.
The ability to gain internal controls to improve anti-money laundering (AML) compliance while reducing costs is becoming increasingly challenging to financial institutions. The high volume of exceptions, new federal regulations, disconnected fraud detection systems, and cumbersome manual processes all pose significant threats to financial institutions and their clients.
By adopting flexible, innovative open source middleware, cloud, and container technologies, financial institutions can reduce risk, lower infrastructure costs, and gain insights from rules-based risk scoring engines. Red Hat can help financial institutions optimize their anti-money laundering processes while ensuring compliance.
Analyst paper: Open Source and Anti-Money Laundering Solutions: What Successful Financial Firms Know
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- Brochure: Enterprise development through production with Red Hat JBoss Middleware
- Whitepaper: The Business Value of Red Hat OpenShift
- Technology overview: Scalable, actionable, anti-money laundering infrastructure from Red Hat
- Solution brief: Protect financial transactions with CustomerXPs and Red Hat
Red Hat helped one of the nation’s most respected banks launch a rules-based decision service to provide real-time risk analysis and simplify production deployment.