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.
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