Unlock Deep Identity Insights with Socure’s New Graph Intelligence

Thousands of businesses rely on Socure every day to make critical risk and trust decisions. 

Today, when a high-risk identity is flagged, our customers receive a score ranging from 0 to 1 — 1 indicating the highest likelihood of identity fraud — as well as detailed Reason Codes that help teams understand the primary factors contributing to that score.

For example, a Sigma Identity Fraud score of .97 might be accompanied by reason codes such as:

• R113: Phone number on Alert List 
• R616: Phone number is prepaid
• R575: Input email is a possible tumbled email 
• R561: Email address is less than 180 days old 
• R566: Email not previously encountered

But that’s just the tip of the identity iceberg. 

Beyond these scores and reason codes lies a wealth of unique, deep identity signals and insights that drive our hyper-accurate risk models and industry-leading performance.

Imagine having the ability to go even deeper to understand how individual identity attributes and PII connect, evolve, and surface over time within Socure’s Network Identity Graph, allowing you to answer complex questions such as:

• “How many different email addresses have been seen together with this applicant’s name and phone combination?”
• “Does the usage pattern of this phone and address together correspond to how each has been used individually, or is there an abnormal deviation that indicates risk?”
• “How many times has this phone number been seen with reported or confirmed identity fraud?”

With Socure’s Graph Intelligence, now you can. 

Introducing Graph Intelligence: Your All Access Pass to Socure’s Powerful Network Identity Graph

In today’s complex risk and regulatory environment, rapidly responding to emerging threats while meeting the unique needs of your users is essential.

And no one understands your user population better than you do. Paired with Socure’s industry-leading fraud and identity solutions, Graph Intelligence unlocks your ability to make more data-driven decisions tailored to your specific population.

It equips fraud and data science teams with tools to quickly refine decision logic, adjust thresholds, and prioritize high-risk behaviors, helping you adapt to your unique fraud landscape and stay agile as new threats emerge.

With exclusive access to unique, deterministic signals that reveal how identity attributes connect and evolve across thousands of organizations and industries, your team can quickly and effectively:

• Fine-tune fraud and onboarding strategies: Create custom rules, prioritize high-risk behaviors, and tailor fraud and customer onboarding strategies to address your organization’s unique fraud landscape. 
• Optimize internal models: Enhance the accuracy and predictive power of your custom models using Graph Intelligence’s unique, high-impact signals.
• Adapt to emerging threats: Uncover new fraud patterns and quickly adjust tactics to mitigate concerns without having to wait on model governance review processes.
• Streamline manual reviews: Equip your fraud operations teams with a detailed view of identity behaviors and connections for quicker, more accurate assessments.
• Enhance model transparency: Receive clear, explainable signals that correlate to Socure’s risk scores to effortlessly justify decisions.

Transforming Complex Identity Connections into Actionable Insights

Graph Intelligence offers three simple ways to view and analyze and act on these deep identity connections and insights:

1. A clear, comprehensive list of over 220 features, returned for 15 unique identity attribute inputs available both via API and directly in your dashboard.
2. Customized analytics views for quick, visual discovery of trends and anomalies within your user base.
3. Detailed graph visualizations that offer a complete view of how various identity attributes are interconnected.

While other vendors and identity solution providers offer limited, siloed views of identity data, Graph Intelligence taps into Socure’s vast cross-industry network, with insights from over 2,700 organizations across sectors like financial services, gaming, and eCommerce. 

This breadth and depth of data provides a comprehensive view of identity behaviors and connections, allowing your team to capture the full spectrum of identity activity. 

When a Pattern of Fraud Emerges: A Case Study

Let’s look at how good identities compare to bad identities. In many cases, clear differences emerge in the patterns of the identities’ PII connections.

For instance, many good identities display strong, consistent historical connections among the PII they provide. Take a Social Security Number (SSN) and phone number, for example: in a legitimate identity, these elements are frequently seen together over time and rarely, if ever, associated with other, different phone numbers or SSNs.

By placing different individual pieces of PII at the center of a graph-based view, we can uncover patterns that reinforce identity authenticity or in contrast, signal potential identity fraud — illustrated in the example below.

x

x

The identity above displays strong, consistent links between name, date of birth, SSN, phone number, and email address. This is represented via the thick edges connecting these elements, indicating correlations that have continued to persist over time. While people may accumulate more physical addresses and IP addresses over time as they move or use different devices, overall high consistency is a positive signal that reduces indicators of third-party risk.

Now, let’s examine another identity. At the time of application, we observe the following connections for a given name and date of birth combination:

x

What do we see? No connections. This name and date of birth combination has not been seen before within Socure’s network. This is not necessarily bad yet, as this can occur for identities with limited interactions across our network’s organizations in recent years. Now, let’s examine their other PII. For the phone number, we observe a similar pattern.

However, when we examine the email address, a very different picture emerges:

x

The email address is linked to numerous different identities, addresses, and IPs. While some individuals — typically family members — may share an email address, these connections do not resemble familial patterns. Instead, this web of associations aligns more closely with third-party fraudsters using stolen identities, with the graph clearly indicating a high level of risk.

It’s Time to Supercharge Your Fraud and Onboarding Strategy

Graph Intelligence adds a powerful new layer of actionable intelligence to Socure’s industry-leading risk scores, providing the depth and clarity needed to understand the full scope of your fraud landscape and user population. It empowers your team to make more precise, data-driven decisions and adapt your strategies as threats evolve.

Are you ready to elevate your fraud prevention and customer onboarding strategies? Schedule a demo today to see Graph Intelligence in action today.