In version 1.24 of the IdentityMind platform, we introduced the concept of a risk and compliance dashboard. Our new dashboards were designed to help you improve operations by providing a quick overview of the operational aspects of the risk and compliance efforts that you are most focused on.
The dashboards are a combination of user-chosen widgets that formed a personalized view for one or more fraud analysts. The goal was to allow you to optimize our platform to match for their workflow.
As part of the version 1.25 release of the IdentityMind platform, we released the “eDNA widget”. This widget presents, in a consolidated form, the value of our IdentityLink and Machine Learning. It is designed to help you in three areas:
- First, it helps with automation.
- Second, it improves manual reviews, by helping validate that you are making the right decisions.
- Third, it helps you identify and prevent large issues.
Before going into these three areas in more detail, let’s start by defining IdentityLink API™. IdentityLink analysis is a technique that allows you to evaluate the relationships between the entities of a network. Through IdentityMind’s IdentityLink API™ you can leverage these insights to evaluate and understand the associations within transactional data. The result is that you can better predict the risk of doing business with a particular digital identity.
1. The Automation
The first part of the widget is the eDNA Reputation and the Graph Score – side by side.
IdentityMind’s eDNA Reputation is a very good predictor of good and bad behavior. Our eDNA engine assembles identity attributes, correlates them, and captures the context of their use to produce the Reputation score. Also, this score is calculated differently depending on your industry. Digital identities with a Trusted reputation are accepted 99.7% of the time, with a negligible fraud rate. On the other hand, digital identities with a Suspicious reputation are rejected 80% of the time, and Bad reputations 90%. The usage of eDNA reputations along with a Graph Score and a fraud policy further strengthens the automation capabilities of the platform, taking clients to a manual review rate below 2%, with minimal fraud.
Both the Reputation and the Graph Score represent the power of our core technology and the predictive analytical value of supervised machine learning. In addition, both leverage our database of hundreds of millions of identities and the aggregated value of evaluating billions of financial transactions.
2. The Review
We are preoccupied with the ability to operationalize and provide efficiencies to review teams. While you could prevent fraud and risk automatically by blocking all high-risk transactions, we know that’s not how to operate a business. So, we help minimize manual reviews and automate the review process, presenting the data so that you can quickly and efficiently evaluate transactions.
The second part of the widget puts the reputation and the graph score in an operational perspective. We provide historical decisions, fraud events (false negatives), customer complaints (false positives), so that manual reviewers can understand the historical performance for this type of transaction. This gives the fraud, risk, and financial crime analysts reasonable guidance to use, in addition to the data already in the user interface. Since fraud/risk shifts we provide different time perspectives that are aligned with the fraud indicators shifts in their environment.
3. Preventing a catastrophe
The last part of the widget present the properties of the graph that summarize complexity and the potential risk of dealing with complex scenarios like identity theft rings, fraud rings, structured layering, smurfing, and other cases that may affect your organization deeply if they are not dealt with quickly.
One of our first clients, years ago, was consistently hit by a fraud ring. They were losing an important percentage of their ecommerce business to the same ring who would resell the goods online. Within weeks of using our technology they identified and stopped the ring that was hitting them. All of it! The graph can help uncover the scope of a problem before it becomes a catastrophe. It doesn’t happen often, but sometimes one fraud ring can bring down a business.