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Staying compliant and preventing financial crime is more challenging than ever. Organizations face pressure from all sides – soaring transaction volumes, rapidly evolving regulations, aggressive enforcement, and strained budgets. Legacy compliance tools developed decades ago are ill-suited to the demands of today’s complex and dynamic compliance environment, failing to accurately classify consumers resulting in high false positive and negative rates. 

Section 326 of the USA PATRIOT Act went into effect more than two decades ago. The regulation directed financial institutions to “have a reasonable belief” that the person or entity is who they say they are by collecting four pieces of information: name, address, national ID number, and date of birth. The institutions should then verify this information with known datasets.

The Quest for Verification

The directive from regulators was to create a definition around what was considered “verified.” Many FIs have centered around requiring three of four data elements to be “verified.” Additional risk overrides are part of the policy as well as documentary verification in certain channels and situations. 

Today, in an era of data breaches, phishing attacks, and cyber infiltration, these four data elements have been compromised for nearly every consumer. A whole datamart on the dark web makes a vast amount of data available for very little money. The definition of an “identity” as only four data elements is not a strategy that offers ANY resistance to nefarious behavior. The bad actors have certainly changed their repertoire to leverage tools like generative AI, synthetic identity creation, and other mechanisms to commit fraud.

In a post-COVID world, transactions have shifted to digital channels. Regulation and business processes that are based on such a low barrier are no longer sufficient. In addition to a changing fraud landscape, many of the Customer Identification Program (CIP) solutions used today still feature rules-based technology. 

The Foundation of Accurate Identity Verification

How well a solution can verify identities is based on two solid foundations:

  • The data that is used.
    Creating a view of data attributes that are accurate for an entity is a critical component of a solid identity solution. Associating the wrong data to the wrong identity WILL result in inaccuracies. And while there is no “perfect” solution, a solution based on accurate entity resolution will result in better onboarding experiences and stronger risk identification processes for organizations. The goal? Onboarding the most desirable customers while managing the risk appropriately.
  • How well that data is leveraged using state-of-the-art technology with entity resolution.
    Data is only useful if you can leverage actionable insights from it and solve problems. More data can be better, but only to an extent. By utilizing machine learning algorithms that excel at handling vast amounts of data you can unlock the power of data and dynamically identify potential risks that may go unnoticed by traditional rule-based matching methods that are inaccurate, and don’t have a holistic view of the customer.

To accurately perform customer verification and assure compliance with CIP/KYC regulations, your organization must move beyond name matching in favor of clearly identifying the risk of a complete entity profile. Incorporating additional data points and risk indicators enable compliance teams to go beyond basic name matching by considering contextual information, such as addresses, transaction history, and relationship networks to build a comprehensive risk profile for each entity, and distinguish between individuals with similar names. 

This approach ensures organizations can prioritize their compliance efforts, focusing on true risks and ensuring no one slips through without detection. Mismatches in customer data, deceased status, and high risk addresses are just a few of the conditions a good identity solution should flag.

Demonstrable Controls

Many organizations struggle with their customer onboarding decisioning that is often manual, time-consuming, and error-prone, which escalates operational and reputational risks and makes demonstrating regulatory compliance difficult.

In a regulatory exam, demonstrating accurate adherence to compliance scorecards and providing context for why a customer decision was made are key to a smooth process and avoiding regulatory penalties. 

Leveraging a single, case management and decisioning platform integrated with your compliance toolset is essential to solving these ongoing operational challenges. If your approach consists of a waterfall of disparate solutions, you don’t have a complete picture of why decisions are made and will struggle to prove to a regulator that you do. Why put yourself in that position?

Socure Delivers the New Standard for Compliance

Today’s compliance challenges are more complex than ever, but thankfully there is a better option than the old approaches of the past that aren’t up for the task.

Socure’s Compliance Suite delivers best-in-class non-documentary identity verification, watchlist screening with continuous monitoring, streamlined case management, customer decisioning, document verification, and more – all orchestrated through one API.

Our AI-powered solutions help drive seamless user experiences that minimize friction and maximize security. Socure provides the radical accuracy that our customers demand to face today’s new challenges and rewriting long held best practices.

This means your organization can securely onboard good customers, protect your organization from risk and regulatory enforcement action, all while achieving game-changing operational efficiencies in the process.

Discover how Socure can put your organization on the path to confident compliance with less effort – get in touch with our team here. 

Debra Geister
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Debra Geister

Debra Geister

With more than two decades of experience in the banking compliance and anti-money laundering industries, Geister is a recognized leader in the financial crime detection field. She has worked with many of the largest financial institutions as well as technology and data companies, both global and domestic, to help eliminate and reduce money-laundering, fraud, and related financial risks.