As money laundering schemes continue to proliferate, it’s crucial that financial institutions examine their anti–money laundering (AML) compliance guides and strengthen their compliance management programs to defend against bad actors. These crimes can take an immeasurable toll on communities, damaging human lives, wildlife, and the environment, and regulators are increasingly penalizing organizations for noncompliant AML programs. Given the current environment, chief compliance officers (CCOs) must upgrade their program’s effectiveness and efficiency, and now is the perfect time to embark on a journey toward AML program modernization.
Upgrading compliance management processes with innovative methods is critical to thwarting financial crime. This ebook looks at how AML program modernization can help financial institutions bolster customer satisfaction and optimize ROI.
AML programs wrestle with several challenges. For example, transaction monitoring solutions can lack logic and flexibility, resulting in a large number of false positive reports. Moreover, disparate systems and isolated datasets can limit transparency and cause operators to lose valuable time when attempting to rapidly respond to indicators of illicit activity. Banks can eliminate these types of challenges by making sure compliance management protocols and technologies stay up to date. This will help reduce the possibility of compliance costs, suboptimal outcomes, and elevated risk across the AML compliance process.
|Group||Business||AM/Analytics||AML Operations||Financial Investigative Unit||AML Operations|
|AML Program Stage||Customer Onboarding||AML Transaction Monitoring||Case Management||Investigation||Regulatory Reporting||Management Reporting|
|High false positives, due to outdated tools and models||High false positives, due to outdated tools and models||Labor-intensive due to high volume of false positive||Manual data collection due to data in multiple systems||Manual creation of reports||Manual creation of reports|
|Incomplete data/Lack of holistic entity view||Incomplete data/Lack of holistic entity view||Large case workload||No holistic entity view, due to lack of single source of information and lack of visualization tools||Lack of integration with case management||Data in multiple systems|
|Data in multiple systems||Data in multiple systems||Large backlog||Manual case narratives||Expensive||Lack of intuitive tools|
|Lengthy onboarding||Incomplete monitoring coverage||N/A||Inefficient||N/A||N/A|
|Poor customer experience||Inefficient and expensive model simulation||N/A||Expensive||N/A||N/A|
|Lack of common data model||Lack of common data model||Lack of common data model||Lack of common data model||Lack of common data model||Lack of common data model|
|Lack of scalability||Lack of scalability||Lack of scalability||Lack of scalability||Lack of scalability||Lack of scalability|
Disparate legacy AML systems can pose a real risk to financial institutions because they
False positives, which can account for more than 80% or 90% of alerts, present a prominent challenge to AML programs. Banks must allocate time, manual effort, and budget to thoroughly investigate every false positive. This can spark customer frustration as transactions can be unnecessarily halted. Financial institutions can unlock the true power of automation and tap into efficiencies by reducing the false positive rate.
Progressive banks understand their AML compliance guides should no longer be restricted to the risk department but embraced across the entire organization. They are also taking advantage of machine learning technologies. A modern AML mindset means that compliance is no longer thought of as a mandatory exercise but rather a process that can help an organization secure its future. Financial institutions that prioritize AML program modernization can reap extensive benefits, including the following:
With the right set of software solutions, banks can boost the accuracy and efficiency of their financial crime investigations. Learn more about how Oracle’s AML solutions can help minimize risk and provide seamless customer service.
A consolidated back end: When modernizing an AML program, banks must first combine back-end systems to create a single platform equipped to handle KYC/customer due diligence, monitoring, detection, investigation, and reporting. Using a unified platform provides a wealth of benefits and helps AML investigators make accurate decisions by facilitating a holistic analysis of events. Furthermore, it provides cost-saving opportunities by reducing the training required to keep staff up to date on various systems. Lastly, unified platforms can help CCOs visualize compliance operations from end to end and manage operations using a single dashboard.
Unified and context-appropriate data: Modern AML programs require a common data foundation capable of receiving information from any type of data source, including third-party data feeds and fragmented data. This creates a way to compile unified and context-appropriate data, which helps develop consistent, transparent, and auditable operations. Additionally, this modern method of data collection allows organizations to source data only once and use it for other initiatives, instead of repeatedly performing extensive ETL cycles for various business units. Most importantly, unified data helps financial institutions identify new criminal patterns and engineer advanced analytics applications that can improve monitoring, detection, and investigation results.
Advanced analytics: Banks can tap into a variety of advanced analytics solutions at the pace that best works for their organization. Advanced analytics innovations to consider when modernizing an AML program include the following:
When updating AML compliance guides, banks will experience positive operational changes. For example, managers can more easily train staff members when the institution uses a single system, and a common data foundation creates a quicker way to share information. Other operational improvements to consider include the following:
In the face of ever-changing compliance regulations and rapidly evolving financial criminals, Oracle Financial Crime and Compliance Management helps institutions detect, investigate, and report suspected financial crimes. This solution leverages automated, comprehensive, and consistent surveillance to monitor various parties across all business lines. Furthermore, machine learning technologies, including graph analytics and NLP, strengthen organizational accuracy and efficiencies.