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Apply Robotic Process Automation in AML & FIU Operations to Increase Efficiency, Lower Risk, and Trim Your Overhead

By Anshul Arora, Managing Director, Matrix-IFS

Anshul Arora, Managing Director, Matrix-IFS

Every financial institution faces costly challenges managing fraud and AML. False Positives (FP) are an especially problematic resource drain, typically ranging as high as 75 to 90 percent. Since each alert requires investigation, the waste of time, technology, manpower – and budget – is staggering. What’s more, every FP potentially delays detection and reporting of bonafide alerts and increases risk.

“Over half the time our investigators spend on an alert is simple data gathering.”

- Top 10 U.S. retail bank

Although the problem is industry wide, there are no standards for streamlining the process. Each institution is on its own to gather, sort data and investigate via external systems, many of which are decentralized.

"By utilizing software with AI and machine learning capabilities, RPA enables processing of high-volume, repeatable tasks with far greater speed and accuracy than manual processing"

With no decision standards, non-technical operations personnel rely on manual tasks and calculations, creating inconsistencies, errors and auditing gaps. This dysfunction between people, products and processes creates tedious work leading to high turnover and higher training costs.

Robotic Process Automation (RPA) offers institutions a fresh, efficient solution to this costly problem. By utilizing software with Artificial Intelligence (AI) and Machine Learning capabilities, RPA enables processing of high-volume, repeatable tasks with far greater speed and accuracy than manual processing. Industries with complex data gathering and processing needs are already adopting efficient RPA solutions from a variety of vendors.

RPA makes sense where tasks are:

• Repetitive
• High volume
• Manually performed
• Event-triggered
• Require documentation of task-related decision points

A case in point is AML Financial Investigation Unit (FIU), which faces processing similar to traditional financial institutions:

• Predefined decision points
• Predefined investigation workflow
• Triggered when laundering scheme suspected and/or confirmed
• Heavy manual interaction with the system
• AML alert volumes are higher than ever before

Evaluating and assessing FIU procedures uncovered multiple opportunities to streamline steps through automation, including:

• Internal database systems
• External RFI systems
• Customer historical information
• Auto SAR e-filing
• KYC verification
• One-stop ecosystem
• Cognitive suggestion

RPA Can Be a Self-funding Project

In operations, RPA builds automated data collection and availability. It becomes tactical by applying smart data representation, scripting and macros to operation procedures. Providing BOT interfaces and information-sharing BOTs makes it scalable. Over time RPA becomes cognitive as BOTs get smarter, offer suggestions, and deliver quality analysis to achieve compliance.

If well designed and correctly applied, RPA can provide significant and immediate operational improvements in accuracy, workflow, resources, and budgetary impact, including:

• Cut FP alert volumes
• Reduce investigation intensity
• Lower manual task (operations) volume

These results apply directly to the bottom line, meaning Robotic Process Automation can be a self-funding project, maximizing both efficiency and ROI.

RPA Solution vs. RPA Service – Which is Right for Your Institution?

A successful self-funding RPA project must be carefully initiated, undertaken only after comparing short and long-term outcomes as well as ROI. At first glance, a vendor solution appears advantageous because it offers potentially faster delivery and more standard training. Features may include:

• BOTs development framework
• Pre-built external data integration connectors
• Integration layer rather than user interface
• Requires core product knowledge & support
• One-size-fits-all

Although service delivered by industry experts may take longer, and up-front resources seem at first to appear greater, the RPA approach provides immediate and long-term benefits. Time invested in customizing RPA to fit unique internal infrastructure, organization, and training needs can deliver highly-efficient and productive results from the beginning. The resulting resource will readily adapt to future needs. Choosing to develop RPA specific to your needs, infrastructure, and workflow provides uniquely flexible features:

• Builds BOTs using core technologies framework
• Customization to complement the product
• Bespoke configurations
• Covers integration and interface layers
• Smooth future case management upgrades
• Uses common languages (Java, XML, etc.)

Enhanced Operations Process Streamlines FP Identification and Investigation

Applying customized RPA speeds the review of detection system processes by incorporating a multitude of data sources. RPA can significantly cut resource-wasting FP, helping investigators identify and investigate high-probability alerts far faster. Management can be streamlined with a user-friendly, single-screen strategic alert dashboard providing investigative support information to initiate immediate alert/case review, further enhancing operational efficiencies.

Self-Funding Project – U.S. Commercial Bank Before and After Applying RPA to Investigations

Recently a U.S. commercial bank measured its operational efficiency before and after applying RPA to FP investigations. Results were immediate and significant.

Before applying RPA to processing FP, 50 dedicated employees averaged 400 alerts (30 minutes each), investigated 250 cases (48 minutes) daily.

By applying customized RPA, the same 50 employees cut average alert investigation time from 30 to 10 minutes, boosting daily alert processing from 400 up to 1,200. Case investigation averages dropped from 48 to 15 minutes, processing 800 cases daily – 550 more than before. Faster processing and timeliness of investigations streamlined tracking efficiency and identification of bonafide fraud and money-laundering alerts.

Where to Start – Steps to Design and Implement a Self-Funding RPA Project

Although one-size-fits-all solutions sound appealing, they lack full functionality, are hard to fit into existing infrastructure, and may not adequately address end-to-end needs or future-forward flexibility.

The more carefully you evaluate, test and launch, the more beneficial RPA can be to your institution. Thoroughly incorporating these three steps from the very beginning and throughout the rollout will help maximize RPA effectiveness on managing fraud and AML.

Piloting a Successful Project

The best way to determine the value RPA can bring to your institution is to run a pilot project. Let the numbers speak for themselves. If you invest the time up front to carefully plan and deploy a bespoke pilot RPA project, you can drive both operational and economic benefits of significantly improved efficiency and accuracy for your institution.

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