How RPA Helps With AML Compliance?
Updated: Jun 16, 2020
To counter the rising cost of AML (Anti-Money Laundering) compliance, many financial institutions are making smart use of RPA (Robotic Process Automation) to deliver superior performances. Continue reading to know more about what RPA is and how RPA helps with AML Compliance.
What is RPA?
RPA is a form of A.I work automation technology. What makes it distinct from more traditional workflow automation tools is how the system ‘learns’ the process of carrying out tasks. Rather than scripting the automation process, in the case of RPA, the robots develop the list of actions to perform a task by ‘watching’ and mimicking a user perform that task in the application’s graphical user interface (GUI). The most obvious benefit is the tremendous lowering of barriers to automation in applications where purpose-built API (Application programming interface) may not be available.
How RPA Helps With AML Compliance
Rising costs and increasing complexity of the KYC (Know Your Customer) or AML regulatory environment means that businesses and financial institutions have an incentive to outsource the more mundane and repetitive tasks to digital solutions so that their human employees can focus on what is truly relevant to their expertise. The repetitive and systematic nature of KYC/AML procedures, coupled with the versatility of RPA when it comes to automating tasks, makes the implementation of RPA solutions particularly attractive in the industry.
Not only does RPA help save labor costs and enhance productivity, but it also allows for a more secure KYC/AML system. By limiting the human element in the collection and monitoring of data, there is less room for inconsistency, allowing for greater accuracy and refreshes can be done on a much more regular basis.
Furthermore, RPA allows for the processing of vast amounts of data in extremely short time spans that cannot be matched by any human input. This can allow for real-time AML monitoring and faster identification of potential AML risk factors. This, of course, can further aid in improving the efficiency and efficacy of EDD (Enhanced Due Diligence). To reduce the risk of false positives, NLP (Natural Language Processing) can be employed alongside the process.
Additionally, RPA can reduce transaction costs of activity in the KYC/AML environment in other ways as well. The paperless nature and scalability of RPA can allow for quick adaptation in the rapidly changing regulatory environment, and allow for the integration of the AML/KYC frameworks across business lines and geographies fairly quickly.
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