Transaction monitoring systems generate many alerts that must be investigated to identify suspicious activity. For example, most of the processes involved in resolving and closing AML alerts are semi-automated or manual, leading to delays in review and remediation. Also, most of the work involved in resolving alerts is standardized and repetitive, which is ideal for RPA solutions embedded with cognitive capabilities.
By automating judgement-based tasks related to suspicious activity alert investigation, cognitive RPA can speed up issue resolution and improve overall fraud management within banks.
Source: TCS
