Financial crime management programs are increasingly challenged by limited time and resources, with BSA/AML and Fraud investigators often spending more time manually collecting data than investigating potentially suspicious activity. Institutions should consider how artificial intelligence, such as machine learning and automated solutions, can improve internal processes and strengthen financial crime management programs, while ensuring regulatory compliance.
Institutions can leverage solutions that include Robotic Process Automation (RPA), which utilizes artificial intelligence and software robots, to perform automated tasks. Deloitte explains that with RPA, “software robots can open email attachments, complete e-forms, record and re-key data, and perform other tasks that mimic human action.” These solutions can automatically collect and analyze transactional information, financial data, and personal identification information that can be packaged and presented visually, improving the decision-making process for investigators. For compliance and fraud programs, RPA can reliably automate workflows, regulatory report completion and filing, and suspicious activity alert triage.
Solutions incorporating RPA can allow investigators more time to explore potentially suspicious activity, saving time and resources by automating routine, manual work.
Benefits of Automation for Financial Crime Management
Financial crime management solutions implementing RPA can provide myriad benefits, including:
- Reducing errors. Manual data collection and entry can be prone to human error, while RPA can automatically populate documentation and transfer information accurately.
- Providing consistent information. Forms are populated and submitted in a timely and consistent manner.
- Improving job satisfaction for investigators. Manual and mundane tasks can be completed by the RPA solution, while investigators probe potentially suspicious activity.
- Integrating data: While APIs or ETL processes are the preferred methods to import data into applications, RPA can also be a reliable option to integrate multiple data sources automatically.
While RPA offers great benefits, such as automating burdensome manual processes, financial institutions should consider solutions that augment RPA with cognitive processes such as machine learning. As a static solution, RPA cannot identify or adjust to user interface changes or software updates. Likewise, RPA cannot automatically adjust to changes in regulatory or reporting requirements. Augmenting RPA with dynamic forms of artificial intelligence such as machine learning analytical agents can provide more complete financial crime solutions.
Verafin offers a suite of analytical agents that combine RPA with machine learning to deliver dynamic financial crime management solutions.
Our library of proven RPA agents includes analytics that can:
- Validate that the information populated in a CTR or SAR is correct, and automatically submit those reports.
- Intelligently package related alerts together, reducing the number of overall items and then automatically assigning work to the appropriate team or investigator.
- Automatically triage high-risk customer alerts, classifying them in the appropriate high-risk category.
Verafin’s Financial Crime Management platform can help financial institutions increase efficiency and productivity in everyday banking operations, while maintaining BSA/AML regulatory compliance and conducting thorough financial crime investigations. With automated solutions to collect data and effectively perform routine tasks, Verafin helps financial institutions operate more effectively, saving valuable investigator time and resources.