AML 101: How to Use Our Advanced Fraud Detection Model
In today's dynamic financial landscape, staying ahead of regulatory expectations and combating financial crimes is more crucial than ever. Our advanced AML fraud detection model empowers companies with greater control, visibility, and efficiency in their AML programs.
This blog post will guide you through the key insights and functionalities discussed in the session, ensuring you can leverage our detection modeling platform to its fullest potential.
The Unit21 Advantage: Leading the Way in AML Fraud Detection
Over the past few years, regulatory actions and fines have increased, making it essential for companies to adopt more dynamic and nimble solutions. Staying compliant requires innovative tools that can adapt to evolving threats and regulatory demands.
Unit21's platform allows customers to file SARs quickly and efficiently, reducing investigation times and false positives. By streamlining the reporting process, our platform ensures compliance and enhances the overall effectiveness of your AML program.
By leveraging our flexible Risk & Compliance Infrastructure, you can ingest data from various sources, including transaction data, banking platforms, and third-party systems. Our Network Analysis feature helps identify fraud and money laundering rings, while our Case Management solution offers advanced process and workflow automation.
AML Fraud Detection Modeling: Our Powerful Solution
Our detection modeling platform offers a robust solution for monitoring transactions and identifying suspicious behaviors. We categorize our models into three distinct types:
- Live Models: Actively run and flag your customers in real-time, providing immediate alerts and enabling swift action against suspicious activities.
- Validating Models: Perform discreet historical backtesting, allowing you to create and execute rule configurations on existing data for immediate analysis and fine-tuning.
- Shadow Models: They operate in the background to produce hypothetical flagging data, which is useful for validating and testing your program's efficiency, reducing false positives, and refining detection strategies.
Crafting Effective Rules for Superior AML Fraud Detection
Our platform provides several ways to build rules, each tailored to different needs:
- Dynamic Rule: The most powerful option, allowing for complex configurations and detailed criteria to capture sophisticated fraud patterns.
- Scenario Rule: The easiest to get started with, ideal for straightforward scenarios and quick deployment, making it perfect for common fraud cases.
- Real-Time Rule: Used for immediate fraud detection and transaction decision-making, ensuring instant response to suspicious activities.
Example of a Scenario Rule
In a layering scenario, you might create a rule to flag any customer receiving over $2000 and spending 95% of those funds within a month. These parameters are adjustable, and you can create multiple versions of this rule for different periods or filter entities as needed.
Example of a Dynamic Rule
The Dynamic Rule Builder lets you identify structuring behavior by choosing variables such as Transaction, Action, and Entity. This flexibility allows for more nuanced and compelling fraud detection.
Identifying and Mitigating Account Takeovers
Our platform excels at identifying compromised accounts, a critical aspect of AML. To tailor your detection efforts, you can edit variables like Suspicious Logins, Changes to Account Information, and Outgoing ACH transactions.
For instance, you might look for unusual behavior by calculating the volume of transactions in one day and comparing it to the prior 90 days. This helps identify customers with significantly higher transaction volumes than expected.
AML Fraud Detection: Rigorous Testing and Validation
Testing and validating a rule's effectiveness is crucial before deploying it. Our platform allows you to test rules using historical data, analyze the results, and make necessary adjustments. Once satisfied, you can activate the model as a live rule or in shadow mode.
Our Customer Risk Rating Platform
Our risk rating platform gives you precise control over your risk assessment process. You can build a risk model with categories like Alert & Case Risk, Custom Data Risk, and Rule Risk, assigning values and weights to each variable. This enables you to calculate an aggregate risk score for each customer and configure settings for low, medium, and high-risk categories.
You can also set up enhanced due diligence flows for high-risk customers, ensuring they are reviewed regularly. The Alert Review tab provides a comprehensive view of all alerts, making it easier to manage investigations.
Advanced Investigation Features
When starting an investigation, our platform offers a suite of features:
- Summary feature
- Flagged Entities feature
- AI Findings feature
- Transaction Analysis feature
- Network Analysis feature
The AI Findings feature leverages advanced artificial intelligence to enhance fraud detection. At the start of fiscal year 2023, the U.S. Department of the Treasury recovered over $375 million using an AI-enhanced fraud detection process. This highlights AI's significant impact on identifying and mitigating fraud.
Customizable Workflow buttons streamline the investigation process, and you can submit cases to the L2 Review Queue team for further review. Once completed, you can create and submit FinCEN SARs and CTR cases efficiently, keeping a detailed record of all filings.
Elevate Your AML Program with Our Advanced Detection Model
The importance of a robust AML fraud detection model in today's financial landscape cannot be overstated. Our platform provides the tools and flexibility to stay ahead of regulatory expectations, reduce false positives, and streamline investigations. Adopting our advanced AML fraud detection model ensures your AML program is efficient and effective, giving you the control and visibility you need to combat financial crimes.
Join our workshop to simplify and automate AML compliance with Unit21. Discover how our solutions can transform your approach to AML compliance!
